JP2000057336A - Method and device for processing image - Google Patents

Abstract

PROBLEM TO BE SOLVED: To attain both the suppression of granulation and the emphasis of sharpness by controlling sharpness intensity and the suppression degree of granulation on each pixel position based on granulation identification(ID) signal obtained by applying granulation ID processing including mophology filter processing to a prescribed picture signal. SOLUTION: An image processing block 70 applies sharpness emphasis processing and granulation suppression processing to an original picture signal f0 to obtain an output signal fout. A low frequency component fL is extracted from the signal f0 through a low pass filter(LPF) 72. The signal f0 is converted into a granulation ID signal fgranu by a granulation ID processing means 74 including a mophology filter processing part and gain (gain H) to be multiplied with a high frequency component fH is obtained from the signal fgranu through a lookup table(LUT) 76 as a LUT (fgranu). A product of the gain and the high frequency component fH is added to the low frequency component fL to obtain an output signal fout.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing method and apparatus, and more particularly to an image processing method and apparatus for performing predetermined image processing such as grain suppression and sharpness enhancement on an image signal.

[0002]

2. Description of the Related Art A color image recorded on a negative film, a reversal film, a color print, or the like is converted into a CC image.
An image signal is read photoelectrically by a photoelectric conversion element such as D to obtain image signals for each of the three primary colors red (R), green (G), and blue (B), and converted into digital signals. 2. Description of the Related Art A digital photo printer has been put into practical use as a digital color image reproducing system that performs various image processings and reproduces it on a recording material such as color paper or a display means such as a CRT.

According to this digital photo printer, even if a color image is photographed under inappropriate photographing conditions such as underexposure or overexposure and recorded on a negative film, a reversal film or a color print,
By performing image processing on the obtained original image signal, it is possible to reproduce a color image having a desired color and gradation. In addition, a color image recorded on a negative film, a reversal film, a color print, or the like can be reproduced as a color image having different colors and gradations, if desired.

As such image processing, for example, a predetermined image processing is performed on an image signal representing a given image to enhance the sharpness of the image (sharpness enhancement).
And a method of suppressing graininess (smoothing processing) for suppressing graininess of a film to reduce roughness of an image.

At this time, conventionally, the edge is detected by the edge detecting means, and the degree of sharpness enhancement and the degree of graininess suppression are controlled based on the detected signal. That is, for the part detected as an edge part,
Sharpness is emphasized, and control is performed so as to suppress the granularity of a portion determined not to be an edge portion as a flat portion.

[0006]

However, in the conventional method, since the accuracy of discriminating between the edge portion and the flat portion of the image is low, no satisfactory result can be obtained with respect to both suppression of graininess and enhancement of sharpness. In other words, it is difficult to obtain a good reproduced image because edges are crushed when trying to suppress graininess effectively, and roughness (granularity) is also emphasized while trying to enhance sharpness. There was a problem.

The present invention has been made in view of the above-mentioned conventional problems, and provides an image processing method and apparatus capable of achieving both suppression of graininess of an image, particularly roughness caused by a film, and enhancement of sharpness. That is the task.

[0008]

According to one aspect of the present invention, there is provided an image processing method for performing a predetermined image processing on an image signal representing a predetermined image. On the other hand, there is provided an image processing method characterized by controlling a sharpness intensity or a degree of granular suppression at each pixel position based on a granular identification signal obtained by performing a granular identification process including a morphology filter process.

Further, the image signal is separated into at least two or more frequency components, and for each frequency component other than the lowest frequency component, the gain is controlled based on the granularity identification signal, thereby enhancing sharpness enhancement and granularity suppression. It is preferred to do so.

It is preferable that the granular identification signal is constituted by a difference between a signal subjected to morphological filtering and an original signal.

It is preferable that the sharpness intensity or the degree of granular suppression at each pixel position is controlled based on an edge detection signal obtained by performing an edge detection process on a predetermined image signal in addition to the granular identification signal. .

According to another aspect of the present invention, there is provided an image processing apparatus for performing predetermined image processing on an image signal representing a predetermined image. An image processing apparatus comprising: a granular identification processing unit including a morphology filter processing unit; and a control unit configured to control a sharpness intensity or a degree of granular suppression at each pixel position based on the granular identification signal. provide.

Further, the control means separates the image signal into at least two or more frequency components, and controls the gain of each frequency component other than the lowest frequency component based on the granular identification signal to thereby sharpen the image signal. It is preferable to perform emphasis and graininess suppression.

It is preferable that the granularity identification processing means constitutes the granularity identification signal based on a difference between the morphologically filtered signal and the original signal.

Further, it is preferable that an edge detecting means is provided, and the sharpness intensity or the degree of graininess suppression at each pixel position is controlled based on the granularity identification signal and the edge detecting signal from the edge detecting means.

[0016]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, an image processing method and apparatus according to the present invention will be described in detail based on preferred embodiments shown in the accompanying drawings.

FIG. 1 is a block diagram schematically showing a digital photo printer to which an image processing apparatus for executing an image processing method according to a first embodiment of the present invention is applied. A digital photo printer (hereinafter, referred to as a photo printer) 10 shown in FIG. 1 includes a scanner (image reading device) 12 that photoelectrically reads an image photographed on a film F, and an edge portion of the image data read by the scanner 12. Image processing device 14 that performs image processing such as detection, sharpness enhancement (sharpness enhancement), and smoothing process (granularity suppression), and operation and control of the entire photo printer 10, and an image output from the image processing device 14. And an image recording device 16 for exposing a photosensitive material (photographic paper) to an image with a light beam modulated in accordance with data, developing the image, and outputting the image as a print. The image processing apparatus 14 includes an operation system 18 having a keyboard 18a and a mouse 18b for inputting various conditions such as input, setting, processing selection and instruction, and color / density correction, and the like. The monitor 20 is connected to display an image read in the above, various operation instructions, a setting / registration screen for various conditions, and the like.

The scanner 12 is a device that photoelectrically reads an image photographed on a film F or the like one frame at a time.
A variable aperture 24, a diffusion box 26 for making the reading light incident on the film F uniform in the surface direction of the film F, a carrier 28 of the film F, and an imaging lens unit 30
, An image sensor 32 having a three-line CCD sensor corresponding to reading of image densities of R (red), G (green), and B (blue), an amplifier (amplifier) 33, and an A / D (analog / digital). ) A converter 34.

In the photo printer 10, a dedicated carrier 28 that can be freely mounted on the main body of the scanner 12 includes a film F such as a new photographic system (advanced photo system) or a 135 size negative (or reversal) film.
Are prepared in accordance with the type and size of the film, the form of the film such as strips and slides, and the like, and can be adapted to various films and processes by replacing the carrier 28. An image (frame) photographed on a film and provided for printing is conveyed by the carrier 28 to a predetermined reading position. Also, as is well known, a magnetic recording medium is formed on the film of the new photographic system, and a cartridge ID, a film size, an ISO sensitivity, and the like are recorded. Various data such as date and time, exposure level, model of camera and developing machine can be recorded. The magnetic information reading means is arranged on the carrier 28 corresponding to the film (cartridge) of the new photographic system. The magnetic information is read when the film is transported to the reading position, and the various kinds of information are subjected to image processing. It is sent to the device 14.

When reading an image photographed on the film F in such a scanner 12, a uniform reading light emitted from the light source 22 and adjusted in light amount by the variable aperture 24 and the diffusion box 26 is transmitted by the carrier 28. Incident on the film F located at the predetermined reading position,
By transmitting the light, projection light carrying an image photographed on the film F is obtained. The color image signal is not limited to a signal input by reading the light transmitted through the film as described above, and may be a reflection original or an image captured by a digital camera.

In the illustrated example, the carrier 28 is a 24
It corresponds to a long film F (strips) such as a 35-size film or a cartridge of a new photo system. The film F is positioned at the reading position by the carrier 28, and receives the reading light while being conveyed in the sub-scanning direction orthogonal to the main scanning direction, which is the extending direction of the RGB three-line CCD sensor. As a result, the film F is two-dimensionally slit-scanned, and the image of each frame captured on the film F is read.

The projection light of the film F is imaged on the light receiving surface of the image sensor 32 by the imaging lens unit 30. R, G and B output from the image sensor 32
Are amplified by an amplifier 33, sent to an A / D converter 34, and converted into, for example, 12-bit RGB digital image data in the A / D converter 34, respectively. Is output to

In the scanner 12, when reading an image photographed on the film F, a pre-scan (first image reading) for reading at low resolution and a fine scan (first image reading) for obtaining image data of an output image are performed. (2nd image reading). Here, the pre-scan is performed under preset pre-scan reading conditions so that the image sensor 32 can read all images of the film F to be scanned by the scanner 12 without saturation. On the other hand, the fine scan is performed under the fine scan reading conditions set for each frame from the pre-scan data so that the image sensor 32 is saturated at a density slightly lower than the minimum density of the image (frame). The prescan and fine scan output image signals are basically the same image data except that the resolution and the output image signal level are different.

Note that the scanner 12 used in the photo printer 10 is not limited to one that performs such a slit scan reading, and may be one that performs a planar reading that reads the entire surface of one frame of film image at a time. Good. In this case, for example, an area sensor such as an area CCD sensor is used, and means for inserting R, G, and B color filters are provided between the light source 22 and the film F, and inserted into the optical path of the light emitted from the light source 22. The reading light transmitted through the color filters is irradiated onto the entire surface of the film F, and the transmitted light is imaged on the area CCD sensor to read the entire image of the film by sequentially switching the R, G, and B color filters. Accordingly, the image photographed on the film F is separated into three primary colors and read.

As described above, the digital image data signal output from the scanner 12 is output to the image processing device 14 that performs the image processing method of the present invention. FIG. 2 is a block diagram of the image processing apparatus (hereinafter, referred to as a processing apparatus) 14. Here, the processing device 14 includes a scanner correction unit 36, a LOG converter 38, a pre-scan (frame)
Memory 40, fine scan (frame) memory 4
2. Pre-scan data processing unit 44, fine scan data processing unit 46 that performs sharpness enhancement processing, graininess suppression processing, and various other image processing features of the present invention.
And a condition setting unit 48. FIG. 2 mainly shows a portion related to image processing.
In addition, the photo printer 10 including the processing device 14
A CPU for overall control and management, a memory for recording information necessary for the operation of the photo printer 10 and the like are provided, and the operation system 18 and the monitor 20 are provided with the CPU (CPU).
Bus).

The R, G, and B image signals input from the scanner 12 to the processing device 14, for example, 12-bit digital image data, are input to the scanner correction unit 36.
The scanner correction unit 36 is provided with an RGB three-line CCD sensor of the image sensor 32 of the scanner 12,
In order to correct the sensitivity variation and dark current of each pixel of digital image data, data correction of read image data such as DC offset correction, dark time correction, defective pixel correction, shading correction and the like is performed. The digital image signal that has been subjected to the correction processing of the sensitivity variation and dark current for each pixel by the scanner correction unit 36 is output to the LOG conversion processor. LOG
The converter 38 performs a logarithmic conversion process to convert the digital image data into a gradation by converting the digital image data into digital image density data. For example, the converter 38 corrects the digital image data by a scanner correction unit 36 using a look-up table (LUT). For example, 10-bit (0 to 102) digital data of 12 bits
It is converted into digital image density data of 3).

The digital image density data converted by the LOG converter 38 is stored (stored) in the pre-scan memory 40 if it is pre-scan image data and in the fine scan memory 42 if it is fine scan image data. . The pre-scan memory 40 is obtained by pre-scanning the film F by the scanner 12,
This is a frame memory for storing or storing the low-resolution image density data of the entire frame of the film F subjected to various data correction and logarithmic conversion processing for each of the RGB colors. The pre-scan memory 40 stores at least the film F
It is necessary to have a capacity capable of storing image density data of one frame of three colors of RGB. However, a memory having a capacity capable of storing image density data of a plurality of frames may be used. It may be provided. The pre-scan image data stored in the pre-scan memory 40 is read by the pre-scan data processing unit 44.

On the other hand, the fine scan memory 42 stores the high-resolution image density data of the entire frame of the film F obtained by the fine scan of the film F by the scanner 12 and subjected to various data corrections and logarithmic conversion processes. This is a frame memory for storing or storing for each color. The fine scan image data stored in the fine scan memory 42 is read out by the fine scan data processing unit 46.

A prescan data processing unit 44 that performs various image processes required for display on the monitor 20 on the prescan image data stored in the prescan memory 40
Has an image processing unit 50 and an image data conversion unit 52. Here, the image processing unit 50 includes a condition setting unit 4 described below.
The image data read by the scanner 12 and stored in the pre-scan memory 40 in accordance with the image processing conditions set by the scanner 8 in the desired image quality,
In order to reproduce a color image on the RT display screen, predetermined processing such as gradation correction, color conversion, density conversion, and the like is performed by a lookup table (hereinafter, represented by LUT) or matrix (hereinafter, represented by MTX) calculation. This is for performing image processing. The image data conversion unit 52 includes the image processing unit 5
0 is thinned out as necessary to match the resolution of the monitor 20, and
Using a D (three-dimensional) LUT or the like, the data is converted into image data corresponding to the display on the monitor 20 and displayed on the monitor 20. The processing conditions in the image processing unit 50 are set by a condition setting unit 48 described later.

On the other hand, the fine scan image data stored in the fine scan memory 42 is added to the image recording device 1.
The fine scan data processing unit 46 that executes various image processing necessary for outputting as a color print from the printer 6 and the image processing method of the present invention includes an image processing unit 54 and an image data conversion unit 56. Here, the image processing unit 5
4 performs predetermined image processing on image data read by the scanner 12 and stored in the fine scan memory 42 in accordance with image processing conditions set by a condition setting unit 48, which will be described later. In color tone, on color paper, the present invention aims,
It is intended to reproduce a high-quality image with reduced sharpness and sharpness of a photograph. For this reason, the image processing unit 54 performs LUT, MTX operation,
Various image processing such as color balance adjustment, gradation adjustment, color adjustment, density adjustment, saturation adjustment, electronic scaling, and sharpness enhancement (edge enhancement; sharpening) are performed by a low-pass filter, an adder / subtractor, and the like. The details will be described later.

The image data conversion unit 56 includes an image processing unit 54
Is converted into image data corresponding to image recording by the image recording device 16 using a standard gradation lookup table such as a 3DLUT and supplied to the image recording device 16. Image recording device 16
Is for outputting as a finished print in which a color image is reproduced based on the image data output from the fine scan data processing section 46.

The processing conditions in the image processing section 54 are set in the condition setting section 48. The condition setting unit 48
Various processing conditions in the fine scan data processing unit 46 are set. The condition setting unit 48 includes a setup unit 58, a key correction unit 60, and a parameter integration unit 62. The setup unit 58 sets the fine scan reading conditions using the prescan image data and supplies the conditions to the scanner 12, and creates the image processing conditions for the prescan data processing unit 44 and the fine scan data processing unit 46. (Calculation) and supplies the result to the parameter integration unit 62.

More specifically, the setup section 58 reads out the pre-scan image data from the pre-scan memory 40, and creates a density histogram, average density, LATD (large area transmission density), and highlight from the pre-scan image data. Calculation of image feature amounts such as (lowest density) and shadow (highest density) is performed. From the calculated image feature amount, the scanning conditions of the fine scan, such as the light amount of the light source 22, the aperture value of the variable aperture 24, the image sensor 32, and the like, are set so that the image sensor 32 is saturated at a density slightly lower than the minimum density of the image. (Accumulation time of each RGB 3-line CCD sensor) is set. The fine scan reading condition may be such that all elements corresponding to the output level of the image sensor 32 can be changed with respect to the prescan reading condition, and only one of the elements such as the aperture value can be changed. Alternatively, only a plurality of factors such as the aperture value and the accumulation time may be changed. Further, the setup unit 58
Sets image processing conditions such as the color balance adjustment and the gradation adjustment described above in accordance with a density histogram, an image feature amount, and an instruction from an operator performed as necessary.

The key correction unit 60 includes an adjustment amount such as density (brightness), color, contrast, sharpness, and saturation set by a key (not shown) provided on the keyboard 18a and the operation system 18, and a mouse 18b. The amount of adjustment of image processing conditions (for example, LU
A correction amount of T) is calculated, parameters are set, and the parameters are supplied to the parameter integration unit 62. The parameter integration unit 62 receives the image processing conditions set by the setup unit 58, and transmits the supplied image processing conditions to the image processing unit 50 of the pre-scan data processing unit 44 and the image processing unit 54 of the fine scan data processing unit 46. After setting, the image processing condition set for each part is corrected (adjusted) or the image processing condition is reset according to the adjustment amount calculated by the key correction unit 60.

Next, the image processing unit 54 of the fine scan data processing unit 46 for performing image processing such as sharpness enhancement and graininess suppression, which is a feature of the present invention, will be described in detail. FIG. 3 is a block diagram schematically illustrating an embodiment of the image processing unit 54. As shown in FIG.
Are color density gradation conversion means 64 for converting the density, color and gradation of image data, saturation conversion means 66 for converting the saturation of image data, and digital magnification conversion (electronic conversion) for converting the number of pixels of image data. Double) means 68, and an image processing block 70 for performing various image processing such as sharpness enhancement and graininess suppression.

In the image processing section 54, the color density gradation conversion means 64 converts image data into density data, color data and gradation data according to an LUT or the like. Further, the saturation conversion means 66 includes a color density gradation conversion means 6.
4 is to convert the saturation data of the image data obtained in step 4 in accordance with MTX operation or the like. The electronic scaling unit 68 interpolates the image data subjected to the saturation conversion by the saturation conversion unit 66 according to the size of the color image output to the color paper in the image recording device 16 and according to the output pixel density. In this case, the number of pixel data of the image data is increased or decreased by thinning or thinning. The image processing block 70 performs image processing such as sharpness enhancement and graininess suppression.

FIG. 4 is a block diagram showing a schematic configuration of the image processing block 70 according to the first embodiment. The image processing block 70 is a portion that performs a sharpness enhancement process and a graininess suppression process on the original image signal f0 to obtain an output signal fout. From the original image signal f0, a low-frequency component fL is extracted by a low-pass filter LPF72, and a high-frequency component fH is obtained by subtracting the low-frequency component fL from the original image signal f0, and is separated into a low-frequency component fL and a high-frequency component fH. .

On the other hand, the original image signal f0 is converted into a granular identification signal fgranu by a granular identification processing means 74 including a morphological filter processing unit to be described later, and a gain (gainH) to be multiplied by the high frequency component fH is converted into a look-up table LUT76. Is obtained as an LUT (fgranu). An output signal fout is obtained by adding a value obtained by multiplying the high frequency component fH by the gain to a low frequency component fL. That is, the output signal fout is obtained by the following equation. fout = fL + fH × LUT (fgranu)

FIG. 5 is a block diagram schematically showing a morphological filter processing section 78 included in the granularity identification processing means 74. Hereinafter, the morphological filter processing will be described in detail.

The morphological filter processing unit 74 includes an opening processing unit 80 and a closing (Closing) processing unit.
It comprises a processing unit 82 and a morphological mixing unit 84. In the opening process performed by the opening processing unit 80, as described later, a dilation process is performed after an erosion process, and a dilation process is performed from the original image signal f0.
This is to obtain an output signal f1 in which positive noise is suppressed. The closing processing performed by the closing processing unit 82 is the reverse of the above-described opening processing, in which erosion processing is performed after dilation processing to obtain an output signal f2 in which negative noise is suppressed from the original image signal f0. .

First, the processing for the one-dimensional case will be described for simplicity. Morpholog
sets (masks) used in morphological operations in the field of y)
Is called a structural element, and there are various choices. Now, the structural element g is represented by a symmetric function symmetric to g (x) with respect to the origin, defined by the equation g ^S (x) = g (−x). In particular, its domain G = ｛− m , -M + 1, ...,-
, M-1, m}, g (x)
= 0. At this time, the basic form of the morphological operation is a very simple operation as shown in equations (1) to (4).

[0042]

(Equation 1)

That is, the dilation processing is performed in the range of ± m (a value determined according to the structural element g and corresponding to the mask size in FIG. 6) around the target pixel. This is a process of searching for a value. As shown in FIG. 6, the signal after the dilation process with respect to the original image signal f0 is represented by a broken line f 'in the figure. On the other hand, the erosion process is a process of searching for a minimum value within a range of ± m around the target pixel. As shown in FIG. 7, the signal after the erosion process is applied to the original image signal f0. This is represented by a broken line f ″ in the figure.

The opening process is a process of performing a dilation process after the erosion process, and is a process of searching for a maximum value after searching for a minimum value. That is,
As shown in FIG. 8, the signal after the opening process for the original image signal f0 is as shown by the broken line f1 in the figure, and the positive noise A is suppressed. Thus, the opening process is
An image signal (density curve) f (x) is smoothed from the low density side, and a convex density variation portion (a portion having a higher density than the surrounding portion) that fluctuates in a spatially narrower range than the mask size 2 m.
A is equivalent to suppressing A.

On the other hand, the closing process is a process of performing an erosion process after a dilation process, and is a process of searching for a minimum value after searching for a maximum value. That is,
As shown in FIG. 9, the signal after the closing processing on the original image signal f0 is as shown by the broken line f2 in the figure, and the noise B on the negative side is suppressed. Thus, the closing process
This corresponds to smoothing the original image signal f0 from the high density side and suppressing a concave density variation portion (a portion having a lower density than the surrounding portion) B which fluctuates in a space narrower than the mask size 2m.

Next, the morphological mixing section 84 outputs an output signal fmorph after the morphological processing from the signal f1 after the opening processing and the signal f2 after the closing processing as follows. That is, when the output signal f2 after the closing process is equal to the original image signal f0, the morphology mixing unit 84 sets the output signal f1 after the opening process to the output signal fmorph, and outputs the output signal f1 after the opening process to the original image signal fmorph. When the signal is equal to the signal f0, the output signal f2 after the closing processing is set as the output signal fmorph, and otherwise, the average of the output signals f1 and f2 is set as the output signal fmorph. This can be summarized as follows. fmorph = f1 (when f2 = f0) fmorph = f2 (when f1 = f0) fmorph = (f1 + f2) / 2 (other cases) In this way, an output signal fmorph as shown in FIG. 10 is obtained.

The granularity identification processing means 74 calculates the following equation:
By calculating the difference between the original image signal f0 and the signal fmorph after the morphological filter processing, a granular identification signal fgranu as shown in FIG. 11 is output. fgranu = | f0-fmoph | Thus, morphology is an effective method for detecting graininess, and is particularly effective for detecting isolated points of film graininess.

Next, the morphological processing in the two-dimensional case will be described. FIG. 12 schematically shows the opening processing unit 80 and the closing processing unit 82. In the figure,
Symbols encircled by-represent erosion processing, and symbols encircled by + represent dilation processing.
Also, b1 to b4 are structural elements of the morphological filter, and FIG.
(B) shows a case of a 3 × 3 size. Here, x is -∞ in principle. However, when the original signal is 10 bits, the signal value ranges from 0 to 1023, and therefore x is set to −1023 in the present embodiment. These structural elements b1 to b1
b4 is for extracting only the direction in which 0s are arranged, and b1, b2, b3, and b4 correspond to the vertical, horizontal, main diagonal, and sub-diagonal directions, respectively.

Whether the 5 × 5 size or the 3 × 3 size is used is switched in accordance with at least one of information of a film size, an ISO sensitivity, a print magnification, an exposure level, and a gradation correction level. Can be
That is, specifically, when the granularity is large, a filter having a large size is used, and when the granularity is small, a filter having a small size is used. For example, when the film size is large, the print magnification is small, and the granularity is small. When the sensitivity is high or the exposure is underexposed, the granularity becomes large. The reason for the large grain size in the case of underexposure is that only high-sensitivity emulsions having large grains in the photographic material develop color. Further, in the case of an under-negative tone, when gradation is set, the contrast is restored and the appearance is improved, but there is a side effect that the granularity is emphasized. Therefore, it is preferable to set the filter size according to the gradation correction level. In addition, as for the information, for example, the film size, the ISO sensitivity, the exposure level, and the like can be recorded as magnetic information on the film by using an APS-compatible camera, and these may be read. Further, the print magnification, the level of gradation correction, and the like may be input by the operator.

FIG. 14A shows the flow of the erosion process, and FIG. 14B shows the flow of the dilation process. Now, it is assumed that a filter of 5 × 5 size is selected. At this time, a 5 × 5 region D as shown in FIG. 15A is set around the target pixel f (x, y). The opening processing unit 80 in FIG. 12 performs an erosion process and a dilation process on the original image signal f0. This is because the morphological structure elements b1 to b4 shown in FIG. 13A are applied to an area D as shown in FIG. 15A centering on the original image signal f0 (x, y) of interest. Then, an operation as described below is performed.

As shown in FIG. 14A, each pixel value f0 (x + u, y + v) of the area D and each element b1 of the structural element b1
The difference from (u, v) is obtained, and the minimum value in the area D is output. This is erosion processing. In the case of the 5 × 5 size, u and v take values of −2, −1, 0, +1 and +2. Next, a dilation process is performed on the minimum value as a result of the erosion process. That is, FIG.
As shown in FIG. 4 (b), the sum of the minimum value and each element of the structural element b1 is calculated, and the maximum value in the area D is output. The erosion process and the dilation process are similarly performed for the other structural elements b2 to b4. as a result,
Four output values are obtained, and the maximum value is output as the output signal f1.

The closing processing section 82 in FIG. 12 performs dilation processing and erosion processing on the original image signal f0. That is, the original image signal f0
Then, the maximum value in the area D is obtained by taking the sum of the element and the element of each structural element bi, and then the difference from the element of each structural element bi is obtained, and the minimum value in the area D is output. Further, a minimum value among the four values obtained from these four structural elements b1 to b4 is output as an output signal f2. As described above, the closing process is the same as the opening process except that the order of the two processes of erosion and dilation is interchanged. When the morphological structural element is not 5 × 5 but 3 × 3, the area D
A 3 × 3 as shown in FIG. 15B is also used.

Thus, the output signals f1 and f2 are obtained by the opening process and the closing process, respectively.
Are mixed by the morphological mixing unit 84 in FIG. 5 as in the case of the above-described one-dimensional processing.
It is output as an output signal fmorph.

As described above, the granularity identification processing means 74
Generates and outputs a granular identification signal fgranu from the output signal fmorph. Lookup table LUT76
Is a high frequency component fH from the granular identification signal fgranu.
Is calculated, gainH = LUT (fgranu).
FIG. 16 shows the look-up table LUT76. As shown in the figure, in portions where the granular component fgranu is large, the gain is made smaller than 1 to suppress graininess, and in portions where the granular component fgranu is small, the gain is made larger than 1 to emphasize sharpness.

As described above, this gain LUT (fgr
anu) is multiplied by the high frequency component fH of the original image signal f0 and added to the low frequency component fL to obtain an output signal fout. The processed image signal fout thus output
Is input to the image data conversion unit 56, converted into image output image data, and then output from the image processing device 14 to the image recording device 16. The image recording device 16 exposes the photosensitive material (printing paper) according to the input image data to record a latent image, performs predetermined processing on the exposed photosensitive material, and outputs it as a print (photograph). In the present embodiment, by controlling the sharpness gain based on the signal of the granularity identification processing means using morphology, it is possible to suppress the granularity and enhance the sharpness.

Next, a second embodiment of the present invention will be described. In the second embodiment, the image processing block 70 in the first embodiment is replaced with an image processing block 170 shown in FIG.

As shown in FIG. 17, the image processing block 170 of the second embodiment calculates a coefficient for changing the gain based on the edge detection means 190 and the edge detection signal in addition to the granularity identification processing means 174. A lookup table LUT 192 is provided, and the other configuration is the same as that of the first embodiment.

As shown in FIG.
Is connected in parallel with the low-pass filter LPF 172 and the granularity identification processing means 174, receives the original image signal f0, and outputs the edge detection signal E. Lookup table LUT
192 calculates the edge detection signal E or a coefficient LUT (E) for changing the gain. This coefficient LUT (E)
Is multiplied by the gain LUT (fgranu) obtained by the lookup table LUT 176 from the granularity identification signal fgranu, which is the output signal of the granularity identification processing means 174. As a result, the gain is gainH = LUT (fgranu) × LUT
(E). Therefore, in the present embodiment, the output signal fou
t is given by the following equation. fout = fL + fH × LUT (fgranu) × LUT
(E) The lookup table LUT according to the present embodiment
176 is shown in FIG.
The UT 192 is shown in FIG. In the present embodiment, the output of the conventional edge detecting means and the output of the granularity identifying means using morphology are used together, so that granularity suppression and sharpness enhancement can be performed more accurately.

Next, a third embodiment of the present invention will be described. The third embodiment is different from the first embodiment in that the image processing block 70 shown in FIG.
Is replaced by

The third embodiment is a low-pass filter LPF
1 and another low-pass filter LPF2 is provided,
The original image signal is separated into three components, a low frequency component fL, a middle frequency component fM, and a high frequency component fH. That is, the low-pass filter LPF1 is converted from the original image signal f0.
The low frequency component fL is separated by the
The low frequency component fM is separated from the low frequency component fL by subtracting the low frequency component fL from the low frequency component fL. The low frequency component fL is subtracted from the original image signal f0, and the high frequency component fM is further subtracted. fH is separated.

On the other hand, with respect to the granular identification signal fgranu output from the granular identification processing means 274, the medium frequency component f
Lookup tables LUTM276 and LUTH2 for calculating gains M and gainH to be multiplied by M and the high frequency component fH, respectively.
77 are provided. This lookup table LU
TM276 and LUTH277 are both set as shown in FIG. For the granular identification signal fgranu, the gain LUTM (fgranu) calculated by the look-up table LUTM 276 is multiplied by the medium frequency component fM, and the gain LUTH (fgranu) calculated by the look-up table LUTH277 is converted to the high frequency component fH. Be multiplied.

After all, the output signal fout is given by the following equation. fout = fL + fM × LUTM (fgranu) +
fH × LUTH (fgranu) As described above, in the present embodiment, the frequency band of the original image signal is divided into three, and the gain to be multiplied for each of the medium frequency component and the high frequency component is determined by using morphology. By controlling according to the output signal of the processing means, it is possible to accurately suppress graininess and enhance sharpness.

Next, a fourth embodiment of the present invention will be described. In the fourth embodiment, the image processing block 70 of the first embodiment is replaced with an image processing block 370 shown in FIG. As shown in the figure, the image processing block 370 includes an edge detection unit 390 and two look-up tables LU in the image processing block 270 of FIG.
This is equivalent to the case where TM392 and LUTH393 are added. That is, the granular identification signal f which is the output signal of the granular identification processing means 374 including the morphology filter processing unit
From granu, the gain calculated by the look-up tables LUTM376 and LUTH377 is controlled by the edge detection signal.

The look-up table LUTM 392 is
Gain gai to be multiplied by medium frequency component fM of original image signal f0
The look-up table LUTH 393 is for calculating a coefficient for controlling nM, and for calculating a coefficient for controlling a gain gainH by which the high frequency component fH of the original image signal f0 is multiplied. FIG. 22A shows the look-up table LUTM 392, and FIG. 22B shows the look-up table LUTH 393. FIG.
As shown in (a), where the edge detection signal is small, the gain for the middle frequency component fM is reduced to suppress graininess. This is because the roughness caused by the film graininess is included in the middle frequency component.
Also, as shown in FIG. 22B, the sharpness is enhanced by increasing the gain for the high frequency component fH because the high frequency component contains many edges in the image.

In the case of this embodiment, the image processing block 37
The output signal fout of 0 is given by the following equation. fout = fL + fM × LUTM (fgranu) × LU
TM (E) + fH × LUTH (fgranu) × LUTH
(E) As described above, in the present embodiment, the frequency band of the original image signal is divided into three, and the gain to be multiplied for each of the middle frequency component and the high frequency component is determined by the morphology of the granular identification processing unit. When the control is performed in accordance with the output signal, the output signal of the edge detecting means is also taken into consideration, so that the granularity can be suppressed and the sharpness can be enhanced with higher accuracy.

In the third and fourth embodiments,
The original image signal is separated into three frequency bands, and the gain is controlled for the high frequency component and the middle frequency component. At this time, the gain control may be performed only for the high frequency component. . As described above, according to the present embodiment, the use of the morphological filter as the granularity identification means makes it possible to improve granularity identification accuracy and achieve both granularity suppression and sharpness enhancement.

Although the image processing method and apparatus of the present invention have been described in detail above, the present invention is not limited to the above examples, and various improvements and modifications may be made without departing from the gist of the present invention. Of course it is good.

[0068]

As described above, according to the present invention, it is possible to achieve both suppression of graininess and enhancement of sharpness.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating an embodiment of a digital photo printer to which an image processing apparatus that performs an image processing method of the present invention is applied.

FIG. 2 is a block diagram illustrating an example of an image processing apparatus of the digital photo printer illustrated in FIG.

FIG. 3 is a block diagram illustrating an example of an image processing unit of a fine scan image data processing unit of the image processing apparatus illustrated in FIG. 2;

FIG. 4 is a block diagram illustrating an example of an image processing block illustrated in FIG. 3;

FIG. 5 is a block diagram illustrating an example of a morphological filter processing unit included in the granularity identification processing unit illustrated in FIG. 4;

FIG. 6 is a diagram illustrating an example of a dilation process in the one-dimensional morphology process.

FIG. 7 is a diagram illustrating an example of an erosion process in the one-dimensional morphology process.

FIG. 8 is a diagram illustrating an example of an opening process in the one-dimensional morphology process.

FIG. 9 is a diagram illustrating an example of a closing process in the one-dimensional morphological process.

FIG. 10 is a diagram illustrating an example of an output signal obtained by one-dimensional morphological filter processing.

FIG. 11 is a diagram illustrating an example of a granular identification signal in one-dimensional morphological processing.

12 is a block diagram illustrating an example of an opening processing unit and a closing processing unit illustrated in FIG. 5;

FIG. 13A is an explanatory diagram showing 5 × 5 structural elements of a morphological filter, and FIG.
It is explanatory drawing which shows the structural element of.

14A is an explanatory diagram showing a flow of an erosion process, and FIG. 14B is an explanatory diagram showing a flow of a dilation process.

FIG. 15 (a) shows 5 corresponding to a 5 × 5 structural element;
It is explanatory drawing which shows the * 5 area | region, (b) is explanatory drawing which shows the 3 * 3 area | region corresponding to a 3 * 3 structural element.

FIG. 16 is a diagram showing a lookup table for calculating a gain of a high frequency component in the first embodiment.

FIG. 17 is a block diagram illustrating an image processing block according to the second embodiment of the present invention.

FIG. 18A is a diagram showing a look-up table for calculating a gain of a high frequency component in the second embodiment, and FIG. 18B is a diagram showing a coefficient for controlling the gain by an edge. FIG. 4 is a diagram illustrating a lookup table calculated from a detection signal.

FIG. 19 is a block diagram illustrating an image processing block according to a third embodiment of the present invention.

FIG. 20 is a diagram showing a lookup table for calculating gains of middle and high frequency components in the third embodiment.

FIG. 21 is a block diagram showing an image processing block according to a fourth embodiment of the present invention.

FIG. 22A is a diagram showing a lookup table for calculating a coefficient for controlling a gain of a middle frequency component in the fourth embodiment, and FIG. 22B is a diagram for controlling a gain of a high frequency component as well. FIG. 4 is a diagram illustrating a lookup table for calculating coefficients.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 10 Digital photo printer 12 Scanner 14 (Image) processing device 16 Image recording device 18 Operation system 18a Keyboard 18b Mouse 20 Monitor 22 Light source 24 Variable diaphragm 26 Diffusion box 28 Carrier 30 Imaging lens unit 32 Image sensor 34 A / D converter 36 Scanner correction unit 38 LOG converter 40 Prescan (frame) memory 42 Fine scan (frame) memory 44 Prescan data processing unit 46 Fine scan data processing unit 48 Condition setting unit 50, 54 Image data conversion unit 58 Setup unit 60 Key correction Unit 62 parameter integration unit 64 color density gradation conversion unit 66 saturation conversion unit 68 electronic scaling (digital magnification conversion) unit 70 image processing block 72 low-pass filter LPF 74 granular identification processing unit 76 Look-up table LUT 78 Morphological filter processing unit 80 Opening processing unit 82 Closing processing unit 84 Morphological mixing unit

Claims (8)

[Claims] 1. An image processing method for performing predetermined image processing on an image signal representing a predetermined image, wherein the granularity is obtained by performing a granular identification process including a morphological filter process on the predetermined image signal. An image processing method comprising controlling a sharpness intensity or a degree of granular suppression at each pixel position based on an identification signal. 2. The image signal is separated into at least two or more frequency components, and for each frequency component other than the lowest frequency component, a gain is controlled based on the granularity identification signal, thereby enhancing sharpness enhancement and granularity suppression. The image processing method according to claim 1, wherein the image processing is performed. 3. The image processing method according to claim 1, wherein the granular identification signal is constituted by a difference between a signal subjected to morphological filtering and an original signal. 4. The image processing method according to claim 1, wherein an edge detection process is performed on a predetermined image signal in addition to the granular identification signal. An image processing method, comprising: controlling a sharpness intensity or a degree of granular suppression at each pixel position based on a signal. 5. An image processing apparatus for performing predetermined image processing on an image signal representing a predetermined image, comprising: a morphological filter processing means for obtaining a granular identification signal from the predetermined image signal. An image processing apparatus comprising: a control unit configured to control a sharpness intensity or a degree of granular suppression at each pixel position based on the granularity identification signal. 6. The sharpness by separating the image signal into at least two or more frequency components and controlling the gain of each frequency component other than the lowest frequency component based on the granular identification signal. The image processing apparatus according to claim 5, wherein emphasis and graininess suppression are performed. 7. The granular discrimination processing means according to claim 5, wherein said granular discrimination processing means constitutes said granular discrimination signal by a difference between a signal subjected to morphological filter processing and an original signal. An image processing apparatus according to claim 1. 8. The image processing apparatus according to claim 5, further comprising an edge detection unit, wherein the edge detection unit receives the granularity identification signal and an edge detection signal from the edge detection unit. And controlling the sharpness intensity or the degree of granular suppression at each pixel position.