JPH0659089B2 - Image signal processing method - Google Patents

Description

Description: TECHNICAL FIELD The present invention relates to an image processing method for binarizing an image signal obtained by scanning an image with an image sensor.

(Technical background of the invention) It has been conventionally practiced to read an image by an image sensor such as a CCD line sensor or a CCD area sensor and to binarize the image signal. In this case, it is conceivable to set the binarization level as a fixed value, but in reality, since the images have different densities, the binarization level cannot be set constant. Therefore, it is considered that a histogram of an image is obtained before the binarization process and the binarization level is determined from this histogram. For example, the appearance frequency for each density level is sequentially added from the background density side, and the density level at which the added value becomes a fixed ratio (for example, 80%) of the total number of pixels is used as the binarization level ( JP-A-56-1660
issue).

However, in this case, the binarization level is greatly affected by the shape of the background mountain, that is, the extent of the mountain extension, and the optimum binarization level may not be set depending on the image. Therefore, there is a problem in that the image quality is deteriorated due to background noise being included or the image being skipped.

(Object of the Invention) The present invention has been made in view of such circumstances, and it is possible to always set the optimum binarization level with high accuracy even if the image changes, and to obtain the image quality after binarizing the image. It is an object of the present invention to provide an image signal processing method capable of improving the image quality.

(Structure of the Invention) According to the present invention, an object of the present invention is to provide an image signal processing method for binarizing an image signal obtained by scanning a film projection image with an image sensor according to a predetermined binarization level. A histogram for the density is obtained, and a certain density level is set to the density level on the density level side including the image among the density levels in which the mountain corresponding to the background of the histogram has a frequency of about 1/40 of the total number of pixels of the image sensor. This is achieved by an image signal processing method characterized by setting the added or subtracted density level to the binarized level.

That is, by using the density level on the density level side including the image as a reference among the density levels having a frequency of about 1/40 of the total number of pixels, even if the mountain width of the histogram corresponding to the background changes, the effect It is hard to receive.

(Embodiment) FIG. 1 is a block diagram of an embodiment of the present invention, FIG. 2 is a conceptual diagram of a part of a concrete example thereof, and FIGS. 3A to 3C are diagrams showing signal waveforms during processing, and FIG. Shows a 3 × 3 matrix, and FIG. 5 shows a histogram for a negative film.

In FIG. 1, reference numeral 10 is a light source. Light from the light source 10 is guided to an image sensor 20 via a condenser lens 12, a film 14, a projection lens 16 and a mirror 18, and a projected image of the film 14 is directed to the image sensor 20. Form an image. The image sensor 20 is a CCD line sensor or C
It is formed of a CD area sensor or the like and is driven by a pulse supplied from a pulse circuit (not shown) to scan an image and output a time-series image signal a. The image signal a has an output waveform as shown in FIG. 3A when the film 14 is negative. 3A to 3C, the horizontal axis represents time t or pixel order, and the vertical axis represents output (density) level.

The image signal a for one scanning line or one screen is temporarily stored in the semiconductor memory 22 such as a line memory or a frame memory. This image signal a is input to the histogram means 24 composed of a CPU (not shown), and the histogram A for the density is obtained here as shown in FIG. The CPU has a background noise cut level detecting means 26 and a binarization level detecting means 2 which the CPU itself has.
7, the background noise cut level b and the binarization level f are obtained from this histogram A.

In the histogram A, the horizontal axis represents the output (density) level V of the image signal a and the vertical axis represents the frequency H.
For No. 4, a mountain B corresponding to the background appears on the low output level side. CPU is mountain B of this histogram A
On the right side, that is, near the skirt on the high output (density) level side including the image, the background noise cut level b and the binarization level f on the higher output level side are determined.

These levels b and f are determined as follows. That is, when the total number of pixels of the image sensor 20 is N, about N /
A constant density level β is added to the density level α of the point C, which is closer to the image signal, among the output levels having a frequency of 40, and α + β is determined as the background noise cut level b. Further, a constant density level γ is added to the density level α at the point C to obtain α +
Let γ be the binarization level f. For example, when a line sensor of 4000 pixels is used and the density level can be set in 64 steps (corresponding to 6 bits), the density level α at the point C at which the frequency is about 100 is obtained, and the density level α for two steps is obtained. The density levels can be added to make α + 2 the base cut level b, and the density levels for 8 levels can be added to α to make α + 8 the binarization level f. Here, the frequency N / 40 is determined based on experiments. Further, the constant values β and γ should be set to optimum values based on experiments.

The image signal a and the background noise cut level b are input to the background noise cut circuit 28, where noise included in the background region is removed. That is, this circuit 28
Is, for example, a comparator 30 and a switch 32 as shown in FIG.
The comparator 30 compares the image signal a with the background cut level b. Also, the switch 32 is the comparator 3
When 0 is judged to be a <b, the background cut level b is selected, and when a ≧ b, the image signal a is selected. As a result, the output C of this circuit 28 is sliced at the background noise cut level b, and the noise in the background region is cut, as shown in FIG. 3B. In this way, the background cut level b is close to the background level d (Fig. 3A),
It is set to a level slightly higher than this.

Reference numeral 34 is a blur correction circuit, for example, the high-frequency emphasis filter 3
6 is used to emphasize the high frequency component of the signal c and to emphasize the edge of the image.

The high-frequency emphasis filter 36 functions to emphasize the center pixel when the image space is an odd matrix in which the center pixel appears. As the high-frequency emphasis filter 36, for example, when each pixel data of a 3 × 3 matrix is set to a to i as shown in FIG. 4, the data e for the central pixel is obtained by using the data of the four pixels around it. = 5e- (b + d + h + f), and E is used as a new image signal. In this case, the high-frequency emphasis filter 36 is set as shown in FIG. 2, and each element of this matrix has a perimeter 4 centered on the central pixel.
The image data of one pixel is integrated and the sum E of the integrated values is obtained. The image signal e thus emphasized is compared with the binarization level f in the comparator 38 to obtain the binarization signal g.

In this embodiment, since the background noise is removed by the background noise cut level b and the blur correction processing by high-frequency emphasis is performed, the fluctuation due to the fine noise of the image signal, especially in the background area, is excessive during the blur correction processing. Never be expanded to. Therefore, it is not affected by background noise. However, the present invention also includes the case where the blur correction is not performed and the case where the noise cut based on the background noise cut level b is not performed.

The present invention does not add the appearance frequency of each density level from the background side of the histogram and set the density level at which the added value becomes a constant ratio of the total number of pixels as a binarization level, but about the total number of pixels. Concentration level C with a frequency of 1/40
With reference to
Since it is determined by adding, the appropriate binarization level f can always be determined even if the width or height of the peak of the histogram with respect to the background changes depending on the image.

As the smoothing circuit 50 of this embodiment, it is possible to use, for example, a median filter that adopts an intermediate value (median) of a 3 × 3 matrix centered on the center pixel as image data of the center pixel.

Further, the background noise cut level b and the binarization level f are set to a higher density level side than the background d as in the above embodiment when an image formed by a negative film is used, but when a positive film is used. On the contrary, it is, of course, set to a lower density level side than the background, and in this case, the density level α to the density level β, which is located on the left side of the histogram peak and has a frequency of about N / 40,
By subtracting γ, the background noise cut level b = α-β and the binarization level f = α-γ are determined. The present invention also includes such a thing.

(Effect of the Invention) As described above, the present invention sets the binarization level to a certain density level on the signal side of the image among the density levels having a frequency of about 1/40 of the total number N of pixels of the image sensor. Since the density level is obtained by adding or subtracting the level, the binarization level can be determined based on the position near the foot of the histogram corresponding to the background. Therefore, even if the width of the peaks of the histogram changes, the binarization level can be determined without being greatly affected, and even if the image changes, the binarization level can always be set to an appropriate level. Therefore, high-quality binarization processing is possible.

[Brief description of drawings]

FIG. 1 is a block diagram of an embodiment of the present invention, FIG. 2 is a conceptual diagram of a specific example thereof, FIGS. 3A to 3C are diagrams showing signal waveforms in a processing process, and FIG. 4 is a 3 × 3 matrix. FIG. 5 is a diagram showing a histogram. 20 ... Image sensor, 24 ... Histogram means, 27 ... Binarization level detection circuit, a ... Image signal, f ... Binarization level, A ... Histogram.

Claims (3)

[Claims] 1. An image signal processing method for binarizing an image signal obtained by scanning a film projection image with an image sensor according to a predetermined binarization level, wherein a histogram for density is obtained from the image signal, and the histogram of the histogram is calculated. The density level obtained by adding or subtracting a constant density level to or from the density level on the density level side including an image among the density levels in which the peak corresponding to the background has a frequency of about 1/40 of the total number of pixels of the image sensor. An image signal processing method characterized by setting to a digitization level. 2. A film projection image is a projection image obtained by a negative film, and the binarization level is set in the vicinity of the skirt of the high density level side of the mountain of the histogram with respect to the background. The image signal processing method according to claim 1. 3. The film projection image is a projection image obtained by a positive film, and the binarization level is set in the vicinity of the skirt of the low density level side of the mountain of the histogram with respect to the background. The image signal processing method according to claim 1.