JP3476641B2 - Image processing method and image processing apparatus - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing apparatus for smoothing an input image, and more particularly to an image processing method capable of converting an image quality of an input image by using smoothing processing and creating an image suitable for a user's image. And an image processing apparatus.

[0002]

2. Description of the Related Art As a function of application software or a word processor on a personal computer, an image such as a photograph is input using an input device such as a color scanner, and the image is subjected to various image processing to convert the image quality. This realizes a function that allows each user to create an image that matches his or her own image from the input image.

As one of those image processing techniques, a smoothing process is used in which the brightness of a pixel of interest is replaced with an average value of the brightness of neighboring pixels in a certain range. As a result of the process, the image is slightly blurred. You can get a soft image.

[0004]

However, when the same processing is performed on the entire screen, for example, in a region where a high-luminance portion and a low-luminance portion are adjacent to each other, the high-luminance portion is adjacent to the low-luminance portion. By taking the average value of and, the brightness decreases, and conversely, the low brightness part increases the brightness by taking the average value with the adjacent high brightness part. There was a problem that it faded.

For example, in the "image processing device" of Japanese Patent Application Laid-Open No. 3-54679, peripheral pixels for which an average value of pixel signals is to be determined and weighting calculation are performed based on the density and contrast of an input image including a target pixel. An apparatus is disclosed which comprises means for setting the coefficient. In the above apparatus, for example, the range of peripheral pixels to be averaged in the shadow portion and the highlight portion of the image data is changed, the weighting calculation coefficient is changed, and smoothing processing suitable for each area is performed. I am trying. Specifically, the above processing mainly removes noise by enlarging and averaging the range of peripheral pixels on the low density and high contrast side, and reduces the range of peripheral pixels on the high density and low contrast side and averages them. It is described that the deterioration of edges is mainly prevented.

[0006] However, although it is described that the above-mentioned device is basically intended to reduce noise and that the processing method is not limited, it is only the density and contrast that determine the range of peripheral pixels. Therefore, for purposes other than simple noise reduction, it is difficult to create an image that gives a new impression while leaving the original image.

The present invention provides an image processing method and an image processing apparatus capable of obtaining various kinds of soft image images without reducing the sharpness of the image.

[0008]

In order to solve the above-mentioned problems, an image processing method according to the invention of claim 1 relates to an input image, pixel data of a pixel of interest and each pixel of pixels surrounding the pixel of interest. In an image processing method for smoothing the pixel of interest on the basis of data, an arbitrary feature amount from a plurality of types of feature amounts obtained from pixel data of the pixel of interest or pixel data of the pixel of interest and pixels in the vicinity of the pixel of interest. And when changing the range of the surrounding pixels according to the size of the selected feature amount of the target pixel , at least
Is also set as the color of the pixel of interest as one of the above feature values.
It is characterized by using the color difference from possible colors .

In order to solve the above-mentioned problems, the image processing method according to the invention of claim 2 is based on the pixel data of the target pixel and each pixel data of the peripheral pixels of the target pixel for the input image. In the image processing method for smoothing the target pixel, an arbitrary feature amount is selected from a plurality of types of feature amounts obtained from pixel data of the target pixel or pixel data of the target pixel and pixels in the vicinity of the target pixel, The weighting ratio given to the pixel data after the smoothing process by the pixel data of the target pixel and the pixel data of the surrounding pixels is changed according to the size of the selected feature amount of the target pixel.
In this case, at least one of the above feature values
It is characterized by using a color difference between the color of the color and the color that can be set arbitrarily .

In the above method, the range of surrounding pixels for smoothing the target pixel and the weighting distribution from the surrounding pixels are changed depending on the size of the feature amount of the target pixel determined by the pixel data of the target pixel and the surrounding pixels. I am letting you. The value of this feature amount is, for example, the brightness calculated from the luminance of the pixel,
The variance of brightness, the edge strength, the color difference for a specific color, etc., is determined by the pixel data of the pixel of interest to be smoothed or the relative relationship between the pixel data and the pixel data of neighboring pixels, It depends on the characteristics of the image.

As a result, the quality of an image can be changed depending on which feature is strengthened or weakened. At this time, since it is possible to arbitrarily select from a plurality of feature amounts, it is possible to obtain an output image obtained by performing various smoothing processing on the input image. Although the specific contents of the smoothing process are different, for example, the smoothing process may be deeply applied to the region of the image that is soft to the sense so that it becomes softer. It is possible to perform processing such as not to hang up.

In order to solve the above problems, the image processing apparatus according to the third aspect of the invention is based on the pixel data of the target pixel and each pixel data of the peripheral pixels of the target pixel for the input image. In an image processing device for performing the smoothing process on the target pixel, a feature amount calculating means for calculating the feature amount of the target pixel from the pixel data of the target pixel or the pixel data of the target pixel and pixels in the vicinity of the target pixel; a feature quantity selection means for selecting features for the process, according to the value of the selected feature quantity, and smoothing processing means for controlling to change the range of the peripheral pixels are provided, the feature quantity calculation
The output means is at least one of the feature quantities
It is characterized in that a color difference between a base color and a color that can be arbitrarily set is calculated .

In order to solve the above-mentioned problems, the image processing apparatus according to the present invention is based on the pixel data of the target pixel and each pixel data of the peripheral pixels of the target pixel for the input image. In an image processing device for performing the smoothing process on the target pixel, a feature amount calculating means for calculating the feature amount of the target pixel from the pixel data of the target pixel or the pixel data of the target pixel and pixels in the vicinity of the target pixel; Feature amount selecting means for selecting a feature amount used for processing, and pixel data of the target pixel and the pixel data of the surrounding pixels are given to the pixel data of the pixel after the smoothing process according to the value of the selected feature amount. Smoothing processing means for changing the weighting is provided, and the feature amount calculating means is provided for at least the feature amount.
One is the color of the pixel of interest and the color that can be set arbitrarily.
The feature is that the difference is calculated .

With the above configuration, the smoothing processing unit changes the range of the smoothed pixel or the weighting of the pixel data of the smoothed pixel to the target pixel according to the value of the feature amount regarding the target pixel calculated by the feature amount calculation unit. I am letting you. That is,
Since the degree of smoothing can be changed according to the value of the above feature amount, without reducing the sharpness of the image,
You can get a soft image. Moreover,
Since a plurality of feature amounts can be selected by the feature amount selecting means, various image smoothing processes can be performed from one input image by selecting the feature amount.

In the image processing apparatus according to claims 3 and 4,
Is characterized in that the feature amount calculating means calculates a color difference between the color of the pixel of interest and a color that can be arbitrarily set , as at least one of the feature amounts.

With the above configuration, it is possible to select whether to apply the smoothing processing deeply or lightly with reference to a color that can be arbitrarily set. For example, it is possible to suppress the degree of smoothing processing for the set color by reducing the range of surrounding pixels as the color difference from the set color is smaller or by concentrating the weighting distribution on the target pixel. Become. In the opposite case, the closer to the set color, the deeper the degree of smoothing processing.

[0017]

BEST MODE FOR CARRYING OUT THE INVENTION [First Embodiment] The following will describe one embodiment of the present invention with reference to FIGS. 1 to 10.

First, the configuration of the image processing apparatus according to this embodiment will be described.

As shown in FIG. 2, the image processing apparatus 10 described above.
A control unit 1 and a program memory 2 storing a program used by the control unit 1 are provided in the. Also,
It has an input image memory 3 for storing an input image and an output image memory 4 for storing an image after the smoothing process. These include a control unit 1 to a control bus 6
And a data bus 7 for exchanging image data. Further, the control bus 6 is provided with a selection input key 5 so that the user can support what kind of image processing is performed on the input image.

Further, the control bus 6 and the data bus 7 are connected to image input means for inputting an image from the outside to the input image memory 3, for example, a scanner 8. The image input means is not limited to the scanner 8 and may be, for example, the image data stored in a storage medium (not shown), which is not limited to the above.

The image processing apparatus 10 of the present embodiment is provided with a plurality of smoothing processes that the user can select.
Basically, these smoothing processes consist of a simple luminance of all pixels in a region composed of a pixel (pixel of interest) for which the smoothing process is to be performed and surrounding pixels, for example, as shown in FIGS. Calculated as an average. If such a region is called a region F, the region F depends on the feature amount P and the distance function described in detail below.

At the stage when the type of smoothing processing is selected, the distance function is determined from among those prepared in advance, but since the feature amount P is different for each pixel of interest, attention is paid in accordance with the change of the feature amount P. The area F changes for each pixel.
That is, the range of the smoothing process is changed according to the characteristics of the pixel itself, and as a result, various effects can be obtained.

In the following description, the size of the input image is (horizontal pixel number) × (vertical pixel number) = X × Y, and the pixel of interest is represented by i.

Further, as shown in FIG. 3, for the target pixel i to be smoothed, eight neighboring pixels are designated as k ₁ to k ₈ . Although not shown, the surrounding pixels that influence the smoothing of the pixel of interest i described above are j _n .

Further, since the pixels handled in this embodiment are constituted by the RGB color system, the input image memory 3
Alternatively, when the image is stored in the output image memory 4, from the upper left pixel on the input or output image, the red of each pixel,
The green and blue luminances R, G, and B are stored in this order. For example, if the image is 24-bit color, pixel A (x,
The luminances R _A , G _A , and B _A in y) are (x + X × y) × 3 + 1st, (x + X × y) × 3 + 2nd, and (x + X × y) of the memory, respectively. )
1 [byte] (8 [bit
]) Units, and the image memory capacity required at this time is X × Y × 3 [byte].

Next, the feature amount P and the distance function will be described.

The feature amount P is calculated from the features of the pixel of interest i itself or the pixel of interest i shown in FIG. 3 and the eight neighboring pixels k _{1 to} k ₈ , specifically, the brightness. The lightness Y _i , the lightness distribution D _i , the edge strength E _i , the color difference C _{i, and the} like are used.

The brightness Y _i is the brightness R _{i of the} pixel of interest _i ,
It is a value obtained from the following equation from G _i and B _i .

Y _i = 0.30 × R _i + 0.59 × G _i + 0.11 × B _i (1) The region F is widened according to the value of the lightness Y _i obtained by the equation (1). By narrowing or narrowing, the following effects can be obtained. For example, if the area F is narrowed when the lightness Y _i is large, and the area F is widened when the lightness Y _i is small, the smoothing is shallow and dark for the bright pixel of interest i. The smoothing is deepened for the pixel i. As a result, at the same time as the smoothing process, it is possible to provide an effect that the brightness gradually propagates from a bright area to a dark area in the image. of course,
If the change of the region F with respect to the change of the lightness Y _i is set in the opposite direction to the above, the opposite effect can be obtained.

Further, the dispersion D _i of lightness, and requests distribution of the brightness Y _n lightness Y _i and the neighboring pixel k _n of the pixel of interest i, the pixel of interest i and eight neighboring pixels k ₁ shown in FIG. 3 in to k ₈ Prefecture, when obtaining the variance D _i lightness, is as follows.

[0031]

[Equation 1]

However, Y _M is an average value of lightness and is given by the following equation.

[0033]

[Equation 2]

[0034] Depending on the degree of dispersion D _i of the brightness, for example, to narrow the region F when the dispersion D _i of brightness is large, varied to broaden the region F when the dispersion D _i of lightness is small You can do it.

In the input image, when a region having a large variance D _i of lightness and a region having a small variance D _i of lightness coexist on the same image, even if the same processing is performed, it is compared with a region having a small variance D _i of lightness. Since the influence of the smoothing on the area having the large brightness distribution D _i is large, the area where the brightness distribution D _{i is} relatively large is more blurred.

[0036] Therefore, as described above, a large area of the dispersion D _i of brightness, reducing the range of the peripheral pixels j _n such that influence from surrounding pixels j _n decreases, easily dispersed D caused by the smoothing process _{It is possible} to suppress blurring of an image in a region where _i is large, and to form an image after the smoothing process with an image as if the smoothing process was performed perceptually uniform.

Further, the edge intensity E _i are those obtained from the brightness Y ₁ to k ₈ Tokyo brightness Y _i and 8 neighboring pixels k ₁ to k ₈ of the pixel of interest i, can be calculated by the following equation.

[0038]

[Equation 3]

[0039] Depending on the degree of the edge intensities E _i, for example, such as narrowing the space F if the edge intensity E _i is large, I'll be varied so as to widen the region F when the edge intensity E _i is less do it. In this case, it is possible to obtain the effect of suppressing the blur in the region having a high edge strength. That is, since the degree of smoothing becomes small in a region having high edge strength, it is possible to perform smoothing processing on the entire image while leaving the edges.

The color difference C _i is calculated from the difference between the brightnesses R _i , G _i , B _{i of the} pixel of interest _i and the brightnesses R _C , G _C , B _C of the specific color C designated in advance. This is a matter of sought, and can be calculated by

[0041]

[Equation 4]

[0042] Depending on the degree of the color difference C _i, for example, to narrow the region F in the case where the color difference C _i is small, may be such'll be varied to broaden the region F in the case where the color difference C _i is greater . In this case, a pixel having a specific color or a color closer to the specific color has a smaller degree of smoothing, and blurring can be suppressed. For example, when a skin color is set as a specific color and an image containing a person is processed, the influence of surrounding pixels is reduced in the color close to the skin color, so that it is possible to suppress blurring of the person's face or the like. This specific color may be set appropriately according to the purpose and the image.

On the other hand, the area F is calculated from the distance function according to the type of the selected smoothing process, the feature amount P (lightness Y _i , lightness distribution D _i , edge strength E _i , color difference C _i ) and the like. determined by a threshold T _h of the determined distance.

The distance function indicates the relationship between an arbitrary pixel and the distance between the pixel of interest and the arbitrary pixel. For example, Euclidean distance, city block distance, chessboard distance, etc. are generally known. . In the following description, the coordinates of the pixel of interest i are (x _i , y _i ) and the coordinates of the surrounding pixels j _n are (x _jn , y _jn ).
And

For example, in the case of the above Euclidean distance, the area F is constituted by the surrounding pixel j _n satisfying the following expression and the target pixel i with respect to the coordinates of the target pixel i.

[0046]

[Equation 5]

In the above, the region F when T _h = 3 is shown in FIG.

In the case of the above city block distance, the area F is constituted by the peripheral pixel j _n satisfying the following expression and the target pixel i with respect to the coordinates of the target pixel i.

| X _i −x _j | + | y _i −y _j | ≦ T _h (7) In the above description, the region F when T _h = 3 is shown in FIG.

In the case of the above chessboard distance, the area F is composed of the peripheral pixel j _n satisfying the following expression and the target pixel i with respect to the coordinates of the target pixel i.

| X _i −x _j | ≦ T _h , | y _i −y _j | ≦ T _h (8) In the above, region F when T _h = 3 is shown in FIG.

In addition to the generally known distance function as described above, for example, a distance function satisfying the following equation may be set.

[0053]

[Equation 6]

Alternatively, x _j = x _i + k, y _j = y _i ± k (-T _h ≤k ≤T _h ) ... (10) Area F (T when the above equation (9) is selected as the distance function.
_h = 3) is as shown in FIG. Further, the region F (T _h = 3) when the above formula (10) is selected is as shown in FIG.

The numbers inside the target pixel i and the surrounding pixels j _n in FIGS. 4 to 8 indicate the distances between the target pixel i and the surrounding pixels j _n indicated by the corresponding distance functions.

[0056] The distance the threshold T _h of, for example, by the feature P, may be calculated by the following equation or the like.

T _h = To / P (11) or T _h = P / Td (12) However, the above is the threshold value of the distance required in the relationship between the feature amount P and the region F. This is merely an example for obtaining T _h , and is not limited to the above formula.

Further, in the above, To and Td are fixed values depending on the type of feature quantity in a series of smoothing processing, but by making these values arbitrarily settable,
It is also possible to adjust the depth of the smoothing process based on the value of the feature amount.

Smoothing processing by the image processing apparatus 10 according to the present embodiment will be described based on the above-described configuration and the flowcharts shown in FIGS. 1, 9, and 10. The image processing apparatus 10 described below has the above-mentioned brightness Y _i , brightness distribution D _i , edge intensity E _i , and color difference C _i as the types of the feature amount P, and the Euclidean distance as a distance function. , City block distance, chessboard distance.

As shown in FIG. 1, when the image processing in this embodiment is started, first, the image data input from the scanner 8 or the like is stored in the input image memory 3 (S1). Next, what kind of smoothing processing is to be performed is selected by the selection input key 5 (S2). Here, the type of the feature amount P and the distance function are determined depending on the type of the smoothing process selected.

Then, in S3, the characteristic amount P determined above is determined.
The process is branched according to. For example, the feature amount P is the brightness Y.
If it is _i , the process proceeds to S4. If the feature amount P is the variance D _i of brightness, the process proceeds to S5. If the feature amount P is the edge strength E _i , S is performed.
If the feature amount P is the color difference C _i , the process proceeds to S7, where the smoothing process is performed. At the stage where any one of the processes of S4 to S7 is completed, the output image memory 4 stores the images for which the respective smoothing processes have been completed.

The smoothing process in S4 to S7 will be described.

When the smoothing process based on the lightness Y _i in S4 is started, the smoothing process subprogram shown in FIG. 9 is started. Then, first, the coordinates (x, y) = (0, 0) are set in S10 and S11, and the brightness R _i , G _i , B _i is taken out with the pixel at this coordinate as the target pixel i (S12).

Next, the extracted brightnesses R _i , G _i and B _i are substituted into the equation (1) to obtain the lightness Y _i (S13). The calculated brightness Y _i is used as the feature amount P, for example, in equation (11) to obtain the distance threshold T _h (S14).

[0065] In the next S15, as shown in FIG. 10, the distance function determined in S2 of FIG. 1, by the threshold T _h of distances determined above S14, determined is surrounding pixels j _n. That is, in S21, the process is branched to a process according to the distance function. For example, if the distance function is the Euclidean distance, the process proceeds to S22, and the Euclidean distance to the pixel of interest i is calculated by the equation (6) as a distance threshold T. Pixels having a value of _h or less are obtained as the surrounding pixels j _n . If the distance function is the city block distance, the process proceeds to S23, and the pixel satisfying the distance threshold T _h in the equation (7) is obtained as the surrounding pixel j _n , and in the case of the chessboard distance or the like, S24. Then, the pixels satisfying the distance threshold T _h in the equation (8) are obtained as the surrounding pixels j _n .

The luminance R _i , G _i , B _{i of the} pixel of interest _i and the luminance R _jn , G _jn , B _{jn of} all the surrounding pixels j _n obtained are averaged for each color, and the output image memory 4 (S16).

Next, 1 is added to x (S17), and y = 0
If the smoothing process has not been completed for all the pixels in the X direction in (S18), the process returns to S12 again, and from S12 to
The processing up to S17 is repeated. As a result, smoothing processing can be performed for all pixels (X pieces) in the X direction at y = 0.

When the smoothing process of all pixels in the X direction at y = 0 is completed in S18, 1 is added to y (S1
9), the process proceeds to S20, and the processes of S11 to S19 are repeated until the smoothing process of the Y pixels in the Y direction is completed.

When all the processing in S4 is completed,
This means that all the image data stored in the input image memory 3 are stored in the output image memory 4 in the state in which the selected smoothing process has been performed. This image data may be output by a printer, displayed on a display, stored, and the like, and may be subjected to other processing depending on the purpose.

Further, in S3 of FIG. 1, the lightness dispersion D
_{When i} , edge strength E _i , and color difference C _i are selected,
In S14 of FIG. 9, the variance D of lightness is obtained.
_i, the edge strength E _i, as well as to obtain the color difference C _i, so causing seek distance threshold T _h corresponding to each feature amount P by using a formula (11) (12) step S15 do it.

As described above, various kinds of smoothing processing can be obtained by variously combining the value of the distance threshold T _h and the condition (distance function) for setting the area F. Although Umidaseru a new effect that goes beyond the mere smoothed if caused to continuously change the threshold T _h distance depending on the value of the characteristic amount P, even spread around the pixel to be smoothed , The distance threshold T _h can be obtained by calculation, so that the smoothing value can be easily obtained by a simple average.

It should be noted that the lightness Y _i , the lightness distribution D _i , the edge intensity E _i , the feature amount P other than the color difference C _i used in the present embodiment, and the distance function other than the above-mentioned distance function are set. As a result, it becomes possible to perform image processing capable of producing a wider variety of effects simultaneously with the smoothing processing.

[Second Embodiment] The following will describe another embodiment of the present invention in reference to FIG. 2, FIG. 3, FIG. 11 and FIG.
For the sake of convenience of description, configurations having the same functions as those shown in the drawings of the first embodiment will be designated by the same reference numerals, and the description thereof will be omitted.

The image processing apparatus of the present embodiment also has the same configuration as the image processing apparatus of the first embodiment shown in FIG. 2, but the contents of the program stored in the program memory 2 are different. Therefore, in the present embodiment, a plurality of smoothing processes that can be selected by the user are prepared, and these smoothing processes are performed depending on the distance between the pixel of interest and the surrounding pixels in the fixed area. Then, it is obtained by changing the weight given to the pixel after the smoothing processing by the target pixel or the surrounding pixels.

Smoothing processing by the image processing apparatus 10 according to the present embodiment will be described with reference to the above-described configuration and the flowcharts shown in FIGS. 11 and 12.

As shown in FIG. 11, when the image processing in this embodiment is started, first, the image data input from the scanner 8 or the like is stored in the input image memory 3 (S31). Next, specify what kind of smoothing process
Selection is made by the selection input key 5 (S32).

Then, in S33, the processing is branched according to the characteristic amount P determined above. For example, if the feature amount P is the lightness Y _i , the process proceeds to S34, and the feature amount P is the lightness distribution D _i.
If so, the process proceeds to S35, and if the feature amount P is the edge strength E _i , the process proceeds to S36, and if the feature amount P is the color difference C _i , S37.
Then, the smoothing process is performed for each. Above S34-S3
When any of the processes of 7 is performed, the output image memory 4 stores the images for which the respective smoothing processes have been completed.

The smoothing processing in S34 to S37 will be described by taking the case of S34 as an example.

In S34, the smoothing process subprogram shown in FIG. 12 is started.

First, in S41 and S42, the coordinates (x,
y) = (0,0), the pixel at this coordinate is set as the pixel of interest i, and the luminances R _i , G _i , and B _i are extracted (S4).
3).

Next, the brightness Y _i is obtained from the extracted brightnesses R _i , G _i and B _i (S44). The weighting parameter Vs is calculated using the calculated lightness Y _i as the characteristic amount P (S4).
5).

Using the obtained weighting parameter Vs,
A weighted average of the luminances of the target pixel i and the surrounding pixels j _n is calculated and stored in the output image memory 4 (S46).

Next, 1 is added to x (S47), and y = 0
If the smoothing process has not been completed for all pixels in the X direction in (S48), the process returns to S43 again, and from S43 to
The processing up to S47 is repeated. As a result, smoothing processing can be performed for all pixels (X pieces) in the X direction at y = 0.

When the smoothing process for all pixels in the X direction at y = 0 is completed in S48, 1 is added to y (S4
9) The process proceeds to S50, and the processes of S42 to S49 are repeated until the smoothing process of the Y pixels in the Y direction is completed.

When all the processes in S34 are completed, all the image data stored in the input image memory 3 is stored in the output image memory 4 in the state where the selected smoothing process is performed. Become.

In the above process, the weighting given to the target pixel i of the brightnesses R _j , G _j , and B _j is changed according to the distance T _jn between the _target pixel i and the surrounding pixels j _n .

The weighting parameter Vs used in the weighting calculation of the smoothing process may be obtained by using, for example, the following equation for the feature amount P of the pixel obtained from the target pixel i and the surrounding pixels j _n .

Vs = To / P (13) Vs = P / Td (14) (To and Td are both fixed values according to the type of feature quantity) In the case of the expression (10), the value of the feature quantity P Is larger, Vs is smaller, and conversely, in the case of the formula (11), Vs is larger as the value of the feature amount P is larger.
s becomes large. The characteristic amount P includes the lightness Y _{i for} each pixel, the lightness distribution D _i , the edge strength E _i , the color difference C _i with a predetermined color, and the like described in the first embodiment.

Then, as a specific calculation method of the weighting calculation, the luminance R _jn , G _jn , and B _jn of the peripheral pixel j _n becomes larger as the distance T _{j from the} target pixel i to the peripheral pixel j _n increases. The average values of brightness R _M , G _M , and B are set so as to reduce the influence.
Seeking _M.

For example, the average value R _{M of} brightness is obtained by the following equation.

[0091]

[Equation 7]

However,

[0093]

[Equation 8]

It is Similarly, using the above equation, the brightness G
_M and B _M can also be obtained.

In the above, the chess board distance is adopted as the distance function, and T _h used below means the maximum value of T _j in the chess board distance. Further, the value of the threshold value T _h is always fixed for the same processing.

In the above equation, the larger the parameter Vs, the higher the ratio of the component of the pixel of interest i before the smoothing process to the pixel of interest i after the smoothing process, and the degree of smoothing decreases. The average values R _M , G _M , and B _{M of the} calculation results are stored in the output image memory 4 as the brightness of the pixel after the smoothing process.

In the case of the present embodiment, the range of the surrounding pixels j _n is not changed by the feature amount P, but as can be seen from the above equations (15) and (16), the surrounding pixels j _n and the pixel of interest are The degree of weighting according to the distance from i is changed, and when the feature amount P of the target pixel i is large,
For example, by increasing the parameter Vs based on the equation (14), the influence from the surrounding pixels j _n can be reduced. At this time, conversely, if the feature amount P is small, the parameter Vs becomes small and the influence from the surrounding pixels j _n becomes large. Thereby, although strictly different, the above formula (13) can obtain an effect similar to the effect when the formula (2) is used in the first embodiment, and according to the above formula (14), It is possible to obtain an effect similar to that obtained by using the formula (1) in the first embodiment.

As in each of the above-described embodiments, the range and weighting for performing the smoothing process on the target pixel i are changed by using the feature amount P determined by, for example, the brightness of the target pixel i and the surrounding pixels j _n of the target pixel i. By doing so, it becomes possible to intentionally change the size of the area affected by the surrounding pixels, or the size of the area affected by the surrounding pixels.
Accordingly, it is possible to realize smoothing processing closer to the user's image or smoothing processing for giving a new image.

The image processing described in the first and second embodiments.
In the processing device, the feature amount calculation means is at least the above feature amount.
As one of the
Then calculate the variance of the brightness of the pixel of interest and neighboring pixels.
Good.

For example, when noise is included, the partial
Although the variance of the brightness becomes large, this noise is removed.
In the case of
Then, the deterioration of the image quality becomes large. Therefore, with the above configuration
Range of surrounding pixels and weighting according to the variance of brightness.
If you change the distribution, the brightness distribution in the input image
Image quality changes, even when the
Prevented smoothing processing is performed, or conversely, image quality
It can also be emphasized.

Therefore, the user has an image of the dispersion of lightness.
Depending on when you want to leave
And change the image of the overall brightness distribution.
it can.

Further , as described in the first and second embodiments.
In the image processing device, the feature amount calculation means is at least
As one of the above-mentioned feature quantities,
Area including the pixel of interest and neighboring pixels determined based on the brightness
The edge strength of the area may be calculated.

With the above structure, the edge strength is high.
The area of surrounding pixels is reduced or weighted with respect to the area.
By concentrating the distribution of
It is possible to perform smoothing processing while holding the error. Also,
Blurring only the edges while preserving the original image
It also becomes possible.

Therefore, with the presence or absence of edges as the target,
The edges of the image while preserving the image
You can perform processing such as doing.

[0105]

The image processing method according to the invention of claim 1 is
As described above, an arbitrary feature amount is selected from a plurality of types of feature amounts obtained from the pixel data of the target pixel or the pixel data of the target pixel and the pixels in the vicinity of the target pixel, and the size of the selected feature amount of the target pixel is selected. If the range of the surrounding pixels is changed according to the
One is the color of the pixel of interest and the color that can be set arbitrarily.
This is a configuration that uses the difference .

Therefore, the range of the smoothed pixels is changed according to the size of the feature amount, that is, according to the change of the feature,
It is possible to create an image that gives a new impression according to the feature amount while leaving the image of the input image. For example, as the feature amount increases, the range of the smoothed pixel is widened or narrowed to increase or decrease the ratio of the pixel data of the pixel of interest given to the pixel after the smoothing process. To do. That is, it is possible to obtain the effect of intentionally strengthening or weakening the characteristics of the target pixel. In addition, since the feature amount can be selected from among a plurality of features, it is possible to obtain a plurality of smoothed images having various impressions with respect to one input image.

As described above, the image processing method according to the second aspect of the present invention arbitrarily selects from a plurality of types of feature amounts obtained from the pixel data of the target pixel or the pixel data of the target pixel and its neighboring pixels. Of the target pixel and the pixel data of the target pixel and the pixel data of the surrounding pixels are changed in weighting ratio given to the pixel data after the smoothing process according to the size of the selected target pixel. In this case, at least one of the above feature values
This is a configuration that uses a color difference between a base color and a color that can be set arbitrarily .

Therefore, the weighting ratio given by the pixel data of the surrounding pixels is changed according to the size of the feature amount, that is, according to the change of the feature amount, and a new image is left according to the feature amount while leaving the image of the input image. Create impressive images. For example, as the feature amount increases, the weighting ratio of the surrounding pixels is decreased or increased, thereby increasing or decreasing the ratio of the pixel data of the pixel of interest given to the smoothed pixel. Or As a result, an effect similar to that of claim 1 can be obtained, that is, an effect of intentionally strengthening or weakening the characteristics of the target pixel can be obtained. Further, also in the above configuration, since the feature amount can be selected from a plurality of features, it is possible to obtain a plurality of smoothed images having various impressions with respect to one input image.

As described above, the image processing apparatus according to the third aspect of the present invention calculates the feature amount of the pixel of interest from the pixel data of the pixel of interest or the pixel data of the pixel of interest and the pixels adjacent to the pixel of interest. Amount calculating means, feature amount selecting means for selecting a feature amount used for smoothing processing, and smoothing processing means for controlling so as to change the range of pixels around the pixel of interest according to the value of the selected feature amount. door is provided, above
The feature amount calculation means is at least one of the above feature amounts.
Calculates the color difference between the color of the pixel of interest and the color that can be set arbitrarily
This is the configuration.

Therefore, it is possible to perform a smoothing process that gives a new impression, without damaging the image of the input image, by changing the range of the smoothing process according to the data originally possessed by the pixel called the feature amount. Play. The feature amount can be selected according to the image that the user wants to strengthen or weaken.

As described above, the image processing apparatus according to the invention of claim 4 calculates the feature amount of the pixel of interest from the pixel data of the pixel of interest or the pixel data of the pixel of interest and the pixels adjacent to the pixel of interest. Quantity calculation means, feature quantity selection means for selecting a feature quantity used for smoothing processing, and pixel data of a target pixel and pixel data of surrounding pixels of the target pixel are smoothed according to the value of the selected feature quantity. Smoothing processing means for changing the weighting given to the pixel data of the pixel after the smoothing processing is provided, and the feature amount calculating means is at least
As one of the feature values, it can be set arbitrarily with the color of the pixel of interest
This is a configuration for calculating a color difference from another color .

Therefore, similar to the third aspect of the invention, there is an effect that the smoothing process that gives a new impression can be performed without damaging the image of the input image.

The feature amount calculating means of the image processing apparatus according to the third and fourth aspects of the present invention is configured to calculate a color difference between the color of the pixel of interest and a color that can be set arbitrarily as at least one of the feature amounts. Is.

Therefore, in accordance with the color of the target area,
By defining the color, it is possible to change the degree of smoothing processing for a specific area depending on the color while maintaining the image of the entire image.

[Brief description of drawings]

FIG. 1 is a flowchart showing a flow of image processing according to an embodiment of the present invention.

FIG. 2 is a functional block diagram showing a configuration of an image processing apparatus according to the present invention.

FIG. 3 is an explanatory diagram showing a correspondence between 8 neighboring pixels and a brightness of the 8 neighboring pixels for a target pixel.

FIG. 4 is a diagram showing surrounding pixels and their regions in which the Euclidean distance T _h from the target pixel is 3 or less.

FIG. 5 is a diagram showing surrounding pixels and a region in which the city block distance T _h from the pixel of interest is 3 or less.

FIG. 6 is a diagram showing surrounding pixels and a region in which the chessboard distance T _h from the target pixel is 3 or less.

In [7] there condition is a diagram showing an example of a peripheral pixel distance T _h between the target pixel and the surrounding pixels is 3 or less and its region.

[8] In certain conditions, it is a diagram showing another example of a peripheral pixel distance T _h between the target pixel and the surrounding pixels is 3 or less and its region.

9 is a flowchart showing details of the smoothing process of S4 in FIG.

FIG. 10 is a flowchart showing details of a process of obtaining surrounding pixels in S16 of FIG.

FIG. 11 is a flowchart showing a flow of image processing according to another embodiment of the present invention.

FIG. 12 is a flowchart showing details of the smoothing process of S34 in FIG.

[Explanation of symbols]

1 control unit (feature amount calculating means / smoothing processing means) 2 program memory (feature amount calculating means / smoothing processing means) 5 selection input key (feature amount selecting means) R _i , G _i , B _i luminance (pixels Data) i target pixel j _n surrounding pixel k neighboring pixel Y _i lightness D _i lightness distribution E _i edge strength C _i color difference

─────────────────────────────────────────────────── ─── Continuation of the front page (56) Reference JP-A-6-348842 (JP, A) JP-A-63-253481 (JP, A) Endo Etsuro, Adobe Photoshops Hop AtoZ, Japan, BNN Co., Ltd.・ N, February 1993, first edition, p. 232-239 (58) Fields surveyed (Int.Cl. ⁷ , DB name) G06T 5/00-5/50 H04N 1/40

Claims (4)

(57) [Claims] 1. An image processing method for performing a smoothing process on a target pixel based on pixel data of the target pixel and each pixel data of pixels surrounding the target pixel in an input image, the pixel data of the target pixel or An arbitrary feature amount is selected from a plurality of types of feature amounts obtained from pixel data of the pixel of interest and pixels in the vicinity of the pixel of interest, and the range of the surrounding pixels is selected according to the size of the selected feature amount of the pixel of interest. When changing , note that at least one of the above features is
An image processing method using a color difference between a color of an eye pixel and a color that can be set arbitrarily . 2. An image processing method for smoothing a pixel of interest based on pixel data of the pixel of interest and pixel data of pixels surrounding the pixel of interest in an input image. An arbitrary feature amount is selected from a plurality of types of feature amounts obtained from pixel data of the pixel of interest and pixels in the vicinity of the pixel of interest, and pixel data of the pixel of interest is selected according to the size of the selected feature amount of the pixel of interest. When changing the weighting ratio given to the pixel data after the smoothing process with the pixel data of the surrounding pixels , at least
Is also set as the color of the pixel of interest as one of the above feature values.
An image processing method using a color difference from possible colors . 3. An image processing device for performing smoothing processing on a target pixel based on pixel data of the target pixel and pixel data of pixels surrounding the target pixel for an input image. Feature amount calculating means for calculating the feature amount of the target pixel from the pixel data of the target pixel and the pixels in the vicinity of the target pixel, feature amount selecting means for selecting the feature amount used for smoothing processing, and the value of the selected feature amount According to the above, smoothing processing means for controlling so as to change the range of the surrounding pixels is provided, and the feature amount calculating means is at least one of the feature amounts.
The color difference between the pixel of interest and the color that can be set arbitrarily.
Image processing device characterized by being output. 4. An image processing device for performing smoothing processing on a target pixel based on pixel data of the target pixel and pixel data of pixels surrounding the target pixel for an input image. Feature amount calculating means for calculating the feature amount of the target pixel from the pixel data of the target pixel and the pixels in the vicinity of the target pixel, feature amount selecting means for selecting the feature amount used for smoothing processing, and the value of the selected feature amount depending on the pixel data and the pixel data of the surrounding pixels are provided with smoothing processing means for changing the weighting given to the pixel data of the pixels after smoothing processing, the feature amount calculating unit of the pixel of interest, at least One of the above features
The color difference between the pixel of interest and the color that can be set arbitrarily.
Image processing device characterized by being output.