JP4720339B2 - Image processing apparatus, image processing program, and electronic camera - Google Patents

Description

  The present invention relates to a technique for setting a compression parameter for image compression.

  In general, an electronic camera or computer performs image compression in order to reduce the recording capacity of image data. In this type of image compression, the code amount after compression and the image quality after decompression vary greatly due to individual differences in image data. Therefore, in general JPEG compression or the like, the value of the scale factor is adjusted as appropriate while performing a plurality of trial compressions, so that the final compression code amount falls within a desired range.

  Further, Patent Document 1 below describes a technique for changing a compression parameter for trial based on conditions at the time of image data capture. As a result, trial compression can be started from a compression parameter near the correct answer, and the compression parameter can be estimated appropriately and accurately.

  In the present application, adjustable parameters that affect the compression code amount in image compression, such as the scale factor described above, are collectively referred to as “compression parameters”.

JP 2001-61148 A (paragraph 0112 etc.)

By the way, in recent electronic cameras, in order to improve the continuous shooting speed and the operability, it is desired to shorten the processing time required for image compression. Also in computer image processing programs, it is desired to reduce the processing time required for image compression in order to improve throughput.
By the way, in the image compression described above, it is necessary to set the compression parameter based on the result of the trial compression, and it takes time to set the compression parameter.
Accordingly, an object of the present invention is to provide a new technique for setting an appropriate compression parameter with a small processing load.

  The image processing apparatus according to claim 1, a pixel calculation unit that obtains a plurality of spatial differences that are pixel differences between neighboring pixels with respect to input image data, and a differential analysis that detects a degree of variation of the plurality of spatial differences. A compression control unit that sets a compression parameter that is a parameter that affects the compression code amount in image compression according to the degree of variation, and the image compression is performed on the image data using the set compression parameter. An image compression unit that generates compressed data, and the pixel calculation unit performs edge enhancement on the image data by adding the spatial difference to the image data at a weight ratio that can be adjusted in advance. The compression control unit sets a compression parameter according to the combination of the degree of variation and the weight ratio, and the image compression unit With contraction parameter, it performs the image compression on the image data of the contour-enhanced, and generates compressed data.

  The image processing program according to claim 4 functions as a computer, the pixel calculation unit, the difference analysis unit, the compression control unit, and the image compression unit according to any one of claims 1 to 3. Let

An electronic camera according to a fifth aspect includes the image processing apparatus according to any one of the first to third aspects, and an imaging unit that captures a subject image and generates image data. The image processing apparatus has a function of compressing the image data generated by the image processing apparatus using the image processing apparatus.

  The image processing device according to claim 6, a pixel calculation unit that obtains a plurality of spatial differences that are pixel differences between neighboring pixels with respect to input image data, and a differential analysis that detects a degree of variation of the plurality of spatial differences. A compression control unit that sets a compression parameter that is a parameter that affects the compression code amount in image compression according to the degree of variation, and the image compression is performed on the image data using the set compression parameter. And the difference analysis unit performs data compression on the plurality of spatial differences, and the greater the amount of data after data compression, the greater the degree of variation in the spatial differences. Is determined to be high.

  An image processing program according to a seventh aspect causes a computer to function as the pixel calculation unit, the difference analysis unit, the compression control unit, and the image compression unit according to a sixth aspect.

  An electronic camera according to an eighth aspect includes the image processing device according to the sixth aspect and an imaging unit that captures a subject image to generate image data, and the image data generated by the imaging unit is The image processing apparatus has a function of compressing an image.

According to the present invention , it is possible to provide a new technique for setting an appropriate compression parameter with a small processing load .

<< First Embodiment >>
[Description of Embodiment Configuration]
FIG. 1 is a block diagram showing an electronic camera 11 of the present embodiment.
In FIG. 1, a photographing lens 12 is attached to the electronic camera 11. The lens control unit 12a performs focus driving, aperture control, and the like of the photographing lens 12. In the image space of the photographic lens 12, the light receiving surface of the image sensor 13 is arranged. The imaging element 13 is driven by the imaging control unit 14. Image data output from the image sensor 13 is processed via the signal processing unit 15 and the A / D conversion unit 16 and then temporarily stored in the memory 17.
This memory 17 is connected to a bus 18. Also connected to the bus 18 are a lens control unit 12a, an imaging control unit 14, a microprocessor 19, a recording unit 22, a monitor display unit 23, an image compression unit 42, and an image processing unit 43.
The microprocessor 19 is connected to an operation unit 19a such as a release button and a focus detection unit 19b that performs focus detection at a plurality of locations in the object scene. The recording unit 22 is loaded with a recording medium 22a.

[Description of Operation of First Embodiment]
FIG. 2 is a flowchart showing the operation of the first embodiment. The operation of this embodiment will be described below along the step numbers shown in the drawings.

Step S1: When the microprocessor 19 detects a release operation of the operation unit 19a, the microprocessor 19 drives the image pickup device 13 via the image pickup control unit 14 or the like to perform an image pickup operation. Image data generated by the imaging operation is temporarily stored in the memory 17.

Step S2: The image processing unit 43 calculates the spatial difference between neighboring pixels for the image data in the memory 17 in units of pixels. Note that, for the calculation of the spatial difference here, it is preferable to use a primary operator that takes the difference between adjacent pixels in the vertical or horizontal direction, or a local operator such as a Laplacian filter.

Step S3: The image processing unit 43 performs edge enhancement on the image data by adding pixels of the spatial difference to the image data at a predetermined weight ratio. This weight ratio is selected according to the degree of contour emphasis that is custom-set by the user in advance.

Step S4: The image processing unit 43 calculates an absolute value sum for all or part of the spatial difference. This absolute value sum is a value indicating the degree of variation of the spatial difference.

Step S5: The microprocessor 19 acquires information on the sum of absolute values and the weight ratio from the image processing unit 43. The microprocessor 19 determines a compression parameter according to the combination of the absolute value sum and the weight ratio.
For example, the microprocessor 19 determines the compression parameter as follows, corresponding to the product of (absolute value sum of spatial differences) × (weight ratio of edge enhancement).

If (sum of absolute values of spatial differences) × (weight ratio of contour emphasis) ≦ threshold 1, compression parameter 1 is selected.
If threshold value 1 <(sum of absolute values of spatial differences) × (weight ratio of edge enhancement) ≦ threshold value 2, compression parameter 2 is selected.
If threshold value 2 <(sum of absolute values of spatial differences) × (weight ratio of edge enhancement) ≦ threshold value 3, compression parameter 3 is selected.
If threshold value 3 <(sum of absolute values of spatial differences) × (weight ratio of edge enhancement) ≦ threshold value 4, compression parameter 4 is selected.

  Further, for example, the microprocessor 19 may determine the compression parameter corresponding to the evaluation value of coefficient A × (sum of absolute values of spatial differences) + coefficient B × (weight ratio of edge enhancement).

As the product or evaluation value increases, the compression parameter is changed in the high compression direction (the direction in which the compression efficiency increases), thereby realizing image compression that is almost similar to fixed length compression.
Conversely, as the product or evaluation value increases, the compression parameter is changed to a lower compression direction (a direction with less compression distortion), thereby realizing image compression with priority on image quality.

Step S6: The microprocessor 19 sets the compression parameter determined in step S5 in the image compression unit 42. Using this compression parameter, the image compression unit 42 compresses the image data after the edge enhancement, and generates compressed data.

Step S7: The recording unit 22 saves and records the compressed data on the recording medium 22a.

[Effects of First Embodiment]
In the first embodiment, a spatial difference is obtained between neighboring pixels of image data, and an absolute value sum of these spatial differences is obtained. If this absolute value sum is small, it means that there is little undulation change (amount of spatial information) in the image data. In this case, the compression efficiency of the image data is increased. On the contrary, if the sum of absolute values is large, it means that there are many undulation changes (amount of spatial information) in the image data. In this case, the compression efficiency of the image data is low. As described above, in the first embodiment, the compression efficiency of image data can be easily estimated by a relatively light processing load of obtaining the sum of absolute values of spatial differences. Furthermore, in the first embodiment, it is possible to determine an appropriate compression parameter considering the amount of spatial information of image data by determining the compression parameter according to the sum of absolute values.

  In the first embodiment, the compression parameter is determined by diverting the spatial difference obtained for contour enhancement. Therefore, it is not necessary to newly add a calculation process for obtaining the spatial difference. As a result, the processing load added for determining the compression parameter is extremely reduced.

  Furthermore, in the first embodiment, the compression parameter is determined according to the combination of the sum of absolute values and the weight ratio of edge enhancement. Therefore, it is possible to set a compression parameter in consideration of a change in compression efficiency after contour enhancement.

  In the first embodiment, the compression efficiency can be estimated before image compression. Therefore, it becomes possible to abolish the conventional trial compression and finish the image compression at once. As a result, the time required for trial compression can be omitted, and the image compression time can be shortened.

<< Second Embodiment >>
Since the structure of 2nd Embodiment is the same as 1st Embodiment (FIG. 1), description here is abbreviate | omitted.
FIG. 3 is a flowchart showing the operation of the second embodiment. The operation of this embodiment will be described below along the step numbers shown in the drawings.

Steps S21 to S23: The same processing as steps S1 to S3 of the first embodiment.

Step S24: The image processing unit 43 attempts data compression such as run-length encoding for all or part of the spatial difference.
The image processing unit 43 obtains the compressed data amount of this spatial difference. This amount of compressed data is a value indicating the degree of variation in spatial difference.
In the case of run-length encoding, it is preferable to use code allocation in which the spatial difference value of zero is the shortest code. Furthermore, it is preferable to assign a shorter code as the spatial difference is closer to zero. By such code assignment, the compressed data amount of the spatial difference strongly shows a positive correlation with the undulation (spatial information amount) of the image data.

Step S25: The microprocessor 19 acquires information on the compressed data amount and the weight ratio from the image processing unit 43. The microprocessor 19 determines a compression parameter according to the combination of the compressed data amount and the weight ratio.
For example, the microprocessor 19 determines a compression parameter as follows, corresponding to a product of (compressed data amount of spatial difference) × (weight ratio of edge enhancement).

When (compressed data amount of spatial difference) × (weight ratio of contour emphasis) ≦ threshold 1, compression parameter 1 is selected.
If threshold value 1 <(compressed data amount of spatial difference) × (weight ratio of edge enhancement) ≦ threshold value 2, compression parameter 2 is selected.
If threshold 2 <(compressed data amount of spatial difference) × (weight ratio of edge enhancement) ≦ threshold 3, compression parameter 3 is selected.
If threshold 3 <(compressed data amount of spatial difference) × (weight ratio of edge enhancement) ≦ threshold 4, compression parameter 4 is selected.

  Further, for example, the microprocessor 19 may determine the compression parameter in accordance with the evaluation value of coefficient A × (space difference compressed data amount) + coefficient B × (weight ratio of edge enhancement).

As the product or evaluation value increases, the compression parameter is changed in the high compression direction (the direction in which the compression efficiency increases), thereby realizing image compression that is almost similar to fixed length compression.
Conversely, as the product or evaluation value increases, the compression parameter is changed to a lower compression direction (a direction with less compression distortion), thereby realizing image compression with priority on image quality.

Step S26: The microprocessor 19 sets the compression parameter determined in step S25 in the image compression unit 42. Using this compression parameter, the image compression unit 42 compresses the image data after the edge enhancement, and generates compressed data.

Step S27: The recording unit 22 saves and records the compressed data in the recording medium 22a.

[Effects of Second Embodiment, etc.]
In the second embodiment, a spatial difference is obtained between neighboring pixels of image data, and a compressed data amount of these spatial differences is obtained. It means that the smaller the amount of compressed data, the smaller the undulation change (spatial information amount) of the image data. In this case, the compression efficiency of the image data is increased. Conversely, the larger the amount of compressed data, the greater the undulation change (spatial information amount) of the image data. In this case, the compression efficiency of the image data is low. As described above, according to the second embodiment, it is possible to easily estimate the compression efficiency of the image data with a relatively light processing load of obtaining the compressed data amount of the spatial difference.

  Furthermore, in the second embodiment, it is possible to determine an appropriate compression parameter in consideration of the spatial information amount of the image data by determining the compression parameter according to the compressed data amount of the spatial difference.

  In the second embodiment, the compression parameter is determined by diverting the spatial difference obtained for contour enhancement. Therefore, it is not necessary to newly add a calculation process to obtain the spatial difference. As a result, the processing load added for determining the compression parameter is extremely reduced.

  Further, in the second embodiment, the compression parameter is determined according to the combination of the compressed data amount of the spatial difference and the weight ratio of the contour enhancement. Therefore, it is possible to set a compression parameter in consideration of a change in compression efficiency after contour enhancement.

  In the second embodiment, the compression efficiency can be estimated before image compression. Therefore, it becomes possible to abolish the conventional trial compression and finish the image compression at once. As a result, the time required for trial compression can be omitted, and the image compression time can be shortened.

<< Additional items of embodiment >>
In the present embodiment, the spatial difference is obtained for each pixel. However, the embodiment is not limited to this. In determining the compression parameter, a spatial difference may be calculated at predetermined thinning intervals. By such processing, it is possible to further reduce the processing load required for determining the compression parameter.

  In the present embodiment, the variation amount of the spatial difference is evaluated based on the sum of absolute values of the spatial difference and the compressed data amount. However, the embodiment is not limited to this. In general, the variation degree and frequency of the spatial difference may be evaluated to determine the variation degree. For example, the variance may be obtained by obtaining the variance of the spatial difference.

  For such a variation degree, it is preferable to adjust the compression parameter according to the tendency shown in FIG. In this case, it is possible to set a compression parameter for fixed length compression by following FIG. 4A. Further, by following FIG. 4B, it is possible to set compression parameters giving priority to image quality.

  In the present embodiment, the case where the trial compression is abolished has been described. However, the embodiment is not limited to this. The compression parameter described above may be used as a start parameter for trial compression. Such processing makes it possible to start trial compression from a location close to the correct answer. As a result, the trial compression can be the actual compression as it is, and the number of trial compressions can be reduced.

  In this embodiment, the compression parameter is determined based on a conditional expression, an evaluation value, and the like. However, the embodiment is not limited to this. For example, the compression parameter may be determined based on the degree of variation (or a combination of the degree of variation and the weight ratio) using a correspondence relationship (such as a lookup table or a function expression). In this case, a data compression experiment is performed on a plurality of image samples, and a standard correspondence relationship between the degree of variation (or a combination of the degree of variation and the weight ratio) and an appropriate compression parameter is experimentally determined in advance. preferable.

  In this embodiment, compression parameters are determined by directly analyzing image data to be compressed. However, the embodiment is not limited to this. For example, the monitor image and finder image before the main imaging may be analyzed as described above to determine the compression parameter used during the main imaging.

  In addition, the range of neighboring pixels when obtaining the spatial difference described above can be set as appropriate. For example, in the case of YCbCr image data, a difference between neighboring pixels may be obtained using only the Y plane, and compression parameters for each plane of YCbCr may be determined based on the degree of variation in the spatial difference. Alternatively, the difference between neighboring pixels may be obtained individually for each surface of YCbCr, and the compression parameter for each surface may be determined. Further, for example, in the case of RGB image data, a difference between neighboring pixels may be obtained using only the G plane, and compression parameters for each of the RGB planes may be determined based on the degree of variation in the spatial difference. Alternatively, the difference between neighboring pixels may be obtained separately for each RGB surface, and the compression parameter for each surface may be determined. For example, in the case of RAW data, a difference between neighboring pixels of the same color component may be obtained and used as a spatial difference. In the case of low-saturation RAW data, a difference between neighboring pixels of different color components may be obtained and used as a spatial difference.

  In the present embodiment, the case applied to the electronic camera 11 has been described. However, the same image processing as described above may be performed by a computer using an image processing program. Further, the image processing method described above may be provided for image data transferred via the Internet or the like.

  As described above, the present invention is a technique that can be used for an image processing apparatus, an electronic camera, and the like.

It is a block diagram which shows the electronic camera 11 of this embodiment. It is a flowchart which shows operation | movement of 1st Embodiment. It is a flowchart which shows operation | movement of 2nd Embodiment. It is a figure which shows the general relationship between the variation degree of a space difference, and a compression parameter.

Explanation of symbols

DESCRIPTION OF SYMBOLS 11 ... Electronic camera, 12 ... Shooting lens, 12a ... Lens control part, 13 ... Imaging device, 14 ... Imaging control part, 15 ... Signal processing part, 16 ... A / D conversion part, 17 ... Memory, 18 ... Bus, 19 ... Microprocessor, 19a. Operation unit, 22 ... Recording unit, 22a ... Recording medium, 23 ... Monitor display unit, 42 ... Image compression unit, 43 ... Image processing unit

Claims (8)

A pixel calculation unit in which a plurality obtaining the spatial difference component which is the pixel difference between neighboring pixels on the input image data,
A difference analysis unit for detecting a variation degree for the plurality of spatial differences;
Depending before Kiba variability index, and a compression control unit for setting a compression parameter is Rupa parameters affecting the compression code amount in images compressed,
An image compression unit that performs the image compression on the image data using the set compression parameter and generates compressed data ;
The pixel calculation unit performs edge enhancement on the image data by adding the spatial difference to the image data at a weight ratio that can be adjusted in advance.
The compression control unit sets a compression parameter according to the combination of the variation degree and the weight ratio,
The image compression unit performs the image compression on the contour-enhanced image data using the set compression parameter, and generates compressed data
The image processing apparatus according to claim and this. The image processing apparatus according to claim 1.
The difference analysis unit performs data compression on a plurality of the spatial differences, and determines that the variation degree of the spatial differences is higher as the amount of data after the data compression is larger . The image processing apparatus according to claim 1 .
The difference analysis unit calculates an absolute value sum for a plurality of the spatial differences, and determines that the degree of variation of the spatial difference is higher as the absolute value sum is larger . An image processing program for causing a computer to function as the pixel calculation unit, the difference analysis unit, the compression control unit, and the image compression unit according to any one of claims 1 to 3. An image processing apparatus according to any one of claims 1 to 3,
  An imaging unit that captures a subject image and generates image data;
  A function of compressing the image data generated by the imaging unit with the image processing apparatus;
  An electronic camera characterized by that. A pixel calculation unit that obtains a plurality of spatial differences that are pixel differences between neighboring pixels with respect to input image data;
  A difference analysis unit for detecting a variation degree for the plurality of spatial differences;
  According to the degree of variation, a compression control unit that sets a compression parameter that is a parameter that affects a compression code amount in image compression;
  An image compression unit that performs the image compression on the image data using the set compression parameter and generates compressed data;
  The difference analysis unit performs data compression on the plurality of spatial differences, and determines that the degree of variation in the spatial differences is higher as the amount of data after data compression is larger.
  An image processing apparatus.   An image processing program for causing a computer to function as the pixel calculation unit, the difference analysis unit, the compression control unit, and the image compression unit according to claim 6.   An image processing apparatus according to claim 6;
  An imaging unit that captures a subject image and generates image data;
  A function of compressing the image data generated by the imaging unit with the image processing apparatus;
  An electronic camera characterized by that.

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