JPH0659086B2 - Image signal processing method - Google Patents

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image signal processing method for binarizing an image signal obtained by scanning an image with an image sensor after blur correction processing. is there.

(Technical background of the invention) Various methods for reading an image by an image sensor such as a CCD line sensor or a CCD area sensor and binarizing the image signal have been conventionally proposed. For example, the applicant of the present application has proposed a method in which an image signal is defocused and then compared with a constant binarization level (Japanese Patent Laid-Open No. 62-130068).
No.). Also, in this case, a method has been proposed in which the binarization level is obtained by subjecting the image signal to smoothing, compression, and level shifting processes, so to speak, that the binarization level floats according to the image signal.

The blur correction here emphasizes the edges of the image by emphasizing the high frequency components of the image, and a high-frequency emphasis filter using first-order differentiation or Laplacian (second-order differentiation) is used. However, since such a high-frequency emphasis filter essentially uses differentiation, it is vulnerable to noise, and especially noise in the background region of the image signal is also emphasized, which significantly improves the image quality after binarization processing. There was a problem of lowering it. Therefore, it has been considered by the applicant of the present application that the image signal is sliced at a predetermined background noise cut level close to the background level to remove noise included in the background. However, in this case, since the background density level differs depending on the image, how to determine the background noise cut level becomes a problem. That is, if this setting is wrong, background noise cannot be sufficiently removed, or the fluctuation range (dynamic range) of the effective signal level of the image signal is narrowed, resulting in deterioration of image quality.

As a method of removing the background noise, a method has been proposed in which the background peak is obtained from the histogram, and the density level obtained by shifting a certain density level based on the density level at the top of the mountain is used as the noise cut level. (JP-A-55-56761). However, since the width of the background peak changes depending on the original, this method has a problem that a good noise cut level cannot be obtained if the width of the peak changes.

(Object of the Invention) The present invention has been made in view of such circumstances, and when the image signal is defocused by high-frequency emphasis prior to the binarization process, the background noise cut level close to the background level is used. Provides an image signal processing method that can always set the background noise cut level appropriately when slicing an image signal to remove background noise and improving the image quality after binarizing the image. The purpose is to do.

(Constitution of the Invention) According to the present invention, the object is to remove background noise by slicing an image signal obtained by scanning a film projection image with an image sensor at a background noise cut level close to the background level. After that, in the image signal processing method of sharpening the image signal by performing blur correction, and further binarizing the image signal by a predetermined binarization level, a histogram for the density of the image signal is obtained, and a mountain corresponding to the background of the histogram is obtained. Is a density level obtained by adding or subtracting a constant density level to or from a density level including an image among density levels having a frequency of about 1/40 of the total number of pixels of the image sensor. Is achieved by the image signal processing method.

That is, the background noise cut level is set based on the density level on the density level side including the image among the density levels having a frequency of about 1/40 of the total number of pixels instead of the density level at the peak of the histogram corresponding to the background. It is a decision.

(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 the pixel order, and the vertical axis represents voltage ν, that is, the output (concentration) 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 obtains the background noise cut level b from the histogram A by the background noise cut level detection means 26 of the CPU itself.

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
The background noise cut level b is determined on the right side of, i.e., near the skirt on the high output (density) level side.

This level b is determined as follows. That is, when the total number of pixels of the image sensor 20 is N, a constant density level β is added to the density level α at the point C, which is closer to the image signal, among the output levels having a frequency of about N / 40. α + β
Is determined as the background noise cut level b. For example 4000
Using the pixel line sensor, the density level is 64 levels (6
(Corresponding to a bit), the frequency is about 1
It is possible to obtain the density level α at the point C where 00 is reached, and add the density levels of two stages to this to obtain the background cut level b. Here frequency N / 40 and constant concentration level β
Are obtained as a result of various experiments on the film original.

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.

A blur correction circuit 34 emphasizes the high-frequency component of the signal c by using a high-frequency emphasis filter 36 as a high-frequency emphasis filter to perform edge emphasis 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 way, prior to the processing for blur correction by high-frequency emphasis,
Since the background noise is removed by the background noise cut level b, the fluctuation due to the fine noise of the image signal, especially in the background area, is not excessively enlarged during the blur correction processing. Therefore, it is not affected by background noise.

Further, since the background noise cut level b is determined based on the histogram A, it is possible to always determine an appropriate level b close to the background level even if the image changes.
Therefore, the level b is too low to remove noise, and the level b is too high to effectively use the output width (dynamic range) of the image signal a, resulting in deterioration of image quality.

FIG. 6 is a block diagram of another embodiment, and FIGS. 7A to 7D are output waveform diagrams of respective parts.

In this embodiment, the binarization level is changed by using the image signal a. That is, the image signal a is smoothed by the smoothing circuit 50 into a smoothed signal h (FIG. 7A), and this smoothed signal h is compressed by the compression circuit 52.
The voltage level of the compressed signal i (FIG. 7B) is further raised by k in the level shift circuit 54. The level-shifted signal j (FIG. 7C) is compared by the comparator 38 with the signal d whose blur correction has already been completed, and a binarized signal is obtained.

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.

According to this embodiment, since the binarization level j itself changes depending on the image signal a, it is suitable for highly accurate binarization processing of an image having a small contrast.

In each of the above embodiments, the high-frequency emphasis filter 3 is provided in the blur correction circuit.
However, the present invention is not limited to this.

Further, the background noise cut level b (= α + β) is set to be slightly higher than the background d as in the above embodiment when using an image formed by a negative film.
On the contrary, when using a positive film, it is, of course, set slightly lower than the background, and in this case, the density level α to a constant density is set on the left side of the histogram peak, that is, the skirt on the low output (low density) level side. It is set to (α-β) by subtracting β.

(Effect of the invention) As described above, the present invention uses the background noise cut level close to the background level to slice the image signal prior to the blur correction processing to remove the noise at the background level. For the noise cut level, a certain density level is added to or subtracted from the density level on the signal side of the image among the density levels at which the peaks of the histogram corresponding to the background have a frequency of about 1/40 of the total number N of pixels of the image sensor. The background noise cut level can be determined based on the position close to the foot of the mountain of the histogram corresponding to the background because the density level is set to the above-mentioned density level. Therefore, the background noise cut level can be determined without being greatly affected even if the width of the peak of the histogram changes, and the background noise cut level can always be set to an appropriate level even if the image changes. Therefore, in the binarization process after blur correction, the background noise cut level is too close to the background to remove noise sufficiently, or conversely, it is too far from the background level to sacrifice the dynamic range of the image signal. It is possible to perform high-quality binarization processing without causing inconveniences such as.

[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, FIG. 5 is a diagram showing a histogram, FIG. 6 is a block diagram of another embodiment, and FIGS. 7A to 7D are output waveform diagrams of respective parts. 20 ... Image sensor, 24 ... Histogram means, 28 ... Underground noise cut circuit, a ... Image signal, b ... Underground noise cut level, d ... Background level, f, j ... Binarization level , A ... Histogram.

Claims (6)

[Claims] 1. An image signal obtained by scanning a film projection image with an image sensor by slicing a background noise cut level close to the background level to remove background noise, and then correcting the blur. In the image signal processing method of sharpening, and further binarizing by a predetermined binarization level, a histogram for the density of the image signal is obtained, and the mountain corresponding to the background of the histogram is the total number of pixels of the image sensor. An image signal processing method, wherein a background noise cut level is a density level obtained by adding or subtracting a constant density level to or from a density level including an image among density levels having a frequency of about 1/40. 2. The image signal processing method according to claim 1, wherein the blur correction is performed by using a high-frequency emphasis filter. 3. The binarization level is obtained by smoothing the image signal, compressing the smoothed signal, and further performing level shift. Image signal processing method. 4. The image signal processing method according to claim 3, wherein the smoothing is performed using a median filter. 5. The film projection image is a projection image obtained by a negative film, and the background noise cut level is
The image signal processing method according to claim 1, wherein the image signal processing method is set in the vicinity of the skirt on the high density level side of the mountain of the histogram with respect to the background. 6. A film projection image is a projection image obtained by a positive film, and the background noise cut level is set in the vicinity of the base 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.