JP3405266B2 - Image processing method and apparatus - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing method and apparatus, and more particularly, to sharpness enhancement and graininess suppression for a color image signal obtained by photoelectrically reading a color image or a subject. The present invention relates to an image processing method and apparatus for extracting an edge portion for image processing such as.

[0002]

2. Description of the Related Art Color images recorded on a negative film, a reversal film, a color print, etc.
An image signal for each of the three primary colors of red (R), green (G), and blue (B) is obtained by photoelectrically reading with a photoelectric conversion element such as D, converted into a digital signal, and this image signal is converted. 2. Description of the Related Art A digital photo printer has been put into practical use as a digital color image reproducing system for performing various kinds of image processing and reproducing 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 unsuitable photographing conditions such as underexposure or overexposure and recorded on a negative film, a reversal film, a color print or the like,
By subjecting the obtained original image signal to image processing, a color image having a desired color and gradation can be reproduced. Further, 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 method of performing image processing on an image signal representing a given image to emphasize the sharpness of the image (sharpness emphasis),
There is a graininess suppressing method for suppressing graininess of a film to reduce roughness of an image. It is necessary to extract the edge part or the granular part before performing the sharpness enhancement or the granular suppression. Various methods have been conventionally known as a method for extracting an edge portion or the like.

As an edge extraction method, for example, a template
A method based on rate matching is known.
This is a function of the pixel values of the pixels around the pixel of interest to be determined.
For distribution, some shape, for example a 3x3 matrix
Prepare a template consisting of
It is to determine whether it is the closest to the template. now,
X is the pixel value of the pixel of interest and its surrounding pixels_j(J = 1, ...
, N), for which k templates are prepared
And the value of the i-th template is set to w_j ⁱ(J =
1, ..., N). At this time, i = 1, ..., k
Sum p expressed by_iTo calculate. p_i= Σ_jw_j ⁱ・ X_j  (Σ is j = 1, ..., n
Sum about) The largest of these p_iTemp play to match what gives
To

For example, for an image composed of a pixel of interest and eight peripheral pixels around it as shown in FIG. 11A, eight templates a1 to a8 as shown in FIG.
Is given. It is assumed that the directions of edges indicated by arrows b1 to b8 correspond to the templates a1 to a8. An operator (operator) represented by such a template is called a Sobel operator. At this time, the product sums p1 to p8 are calculated. First, the calculation for the template a1 is as follows. p1 = 1 × 1 + 2 × 2 + 1 × 3 + 0 × 9 + 0 × 10 + 0
X4 + (-1) x8 + (-2) x7 + (-1) x5 =-
19

Similarly, the product sums p2 to p8 are calculated for the other templates a2 to a8. p2 = -8, p3 = 11, p4 = 20, p5 = 19, p6 = 8, p7 = -11, p8 = -20.

As a result, p4 is the maximum, and FIG.
As shown in (b), the direction from the upper right to the lower left indicated by the arrow b4 of the template a4 is the edge direction of the target pixel 10 (density gradient, that is, the gradient direction), and the value 20 of the sum of products p4 is the intensity of the gradient. Becomes
In this way, the gradient (vector amount) of the pixel of interest is calculated. Next, the direction of this gradient and 90 °
With respect to the adjacent pixels 1 and 5 of the target pixel 10 in the direction of, the same calculation is performed using the templates a1 to a8 with respect to the 3 × 3 image centered on each pixel, and the adjacent pixels 1 and 5 of the adjacent pixels 1 and 5 are calculated. Calculate the direction of the gradient. Then, if at least one direction of the two adjacent pixels 1 and 5 is within 45 ° with respect to the direction of the target pixel 10, it is determined that the target pixel 10 is an edge portion, that is, has connectivity. .

[0009]

However, although the above-mentioned conventional edge part extraction method can extract the edge part to some extent, the granular part is detected as the edge part in some cases, and the quality of the finished image is deteriorated. There was a problem. For example, as shown in FIG. 9A, in addition to the white line which is the original edge portion, it is determined that the granular portion is the edge portion, and many white particles may remain.

The present invention has been made in view of the above-mentioned conventional problems, and an image processing method capable of improving the extraction accuracy of the edge portion and performing the edge portion extraction more accurately than in the prior art and improving the image quality. An object is to provide a device.

[0011]

In order to solve the above-mentioned problems , the present invention is an image processing method for performing predetermined image processing on a color image signal, the method comprising: From the pixel values of the pixel of interest and its peripheral pixels of the image to be constructed, a gradient representing the edge direction and intensity of the pixel of interest and its peripheral pixels is calculated and stored, and from the stored gradient direction, The RG of each pixel of interest is calculated by calculating the connectivity of the pixel of interest and its surrounding pixels and by calculating the gradient of the pixel of interest for each R, G, B channel.
An image characterized by performing edge part extraction by calculating the directionality of each B and determining whether or not the pixel of interest is an edge part from the connectivity and the directionality of each RGB. It provides a processing method.

Here, in calculating the connectivity between the target pixel and its peripheral pixels, the gradient direction of the target pixel is compared with the gradient direction of the neighboring pixel of the target pixel, and the When the directions of a predetermined number of pixels match a predetermined condition, it is preferable that the connection be made. Further, the case where the direction of a predetermined number of the neighboring pixels matches the predetermined condition means that the direction of the neighboring pixels is 5
It is preferable that 0% or more is within 45 ° with respect to the direction of the pixel of interest. Alternatively, when the directions of a predetermined number of pixels among the neighboring pixels match a predetermined condition,
60% or more, 70% or more, 80% in the direction of the neighboring pixels
Or more or 90% or more is 45 ° with the direction of the pixel of interest.
It is preferable that it is within 30 ° or within 30 °. Further, the neighboring pixels are centered on the target pixel,
1 × 3 pixels, 1 × 5 pixels, 3 × 5 pixels, which are more present in the direction orthogonal to the gradient direction of the pixel of interest,
It is preferably a pixel obtained by removing the central pixel from any one of the 3 × 7 pixels and the 5 × 9 pixels. In addition, the determination method of the neighboring pixels and the pixel connectivity determination condition including the predetermined number of pixels whose direction matches the predetermined condition and the predetermined condition where the direction of the predetermined number of pixels match are , The document size, the print magnification, the camera type, and the exposure conditions.
Furthermore, in calculating the connectivity between the pixel of interest and its peripheral pixels, the gradient direction of the pixel of interest and 9
It is preferable that the gradient directions of the adjacent pixels on both sides of the direction of 0 ° and the gradient direction of the pixel of interest are both connected within 45 °.

In order to solve the above-mentioned problems, the present invention is an image processing apparatus for performing a predetermined image processing on a color image signal, and an image formed by the color image signal to be image-processed. Means for calculating a gradient representing the edge direction and intensity of the target pixel and its peripheral pixels from the pixel values of the target pixel and its peripheral pixels, a means for storing the calculated gradient, and the stored A means for calculating the connectivity of the pixel of interest and its peripheral pixels from the direction of the gradient, and a gradient of the pixel of interest for each R, G, B channel to calculate the RGB of the pixel of interest. Means for calculating directionality, means for determining whether or not the pixel of interest is an edge portion based on the connectivity and the directionality of each of RGB.
The present invention provides an image processing device characterized by performing edge portion extraction by including the above.

Here, the means for calculating the connectivity between the target pixel and its peripheral pixels compares the gradient direction of the target pixel with the gradient direction of the neighboring pixels of the target pixel, and selects one of the neighboring pixels. When the directions of the predetermined number of pixels of (1) match the predetermined condition, it is preferable that the connection is made. Further, the case where the direction of a predetermined number of the neighboring pixels matches the predetermined condition means that the direction of the neighboring pixels is 5
It is preferable that 0% or more is within 45 ° with respect to the direction of the pixel of interest. Alternatively, when the direction of a predetermined number of the neighboring pixels matches the predetermined condition,
60% or more, 70% or more, 80% in the direction of the neighboring pixels
Or more or 90% or more is 45 ° with the direction of the pixel of interest.
It is preferable that it is within 30 ° or within 30 °. Further, the neighboring pixels are centered on the target pixel,
1 × 3 pixels, 1 × 5 pixels, 3 × 5 pixels, 3 × extending in a direction orthogonal to the gradient direction of the pixel of interest
It is preferably a pixel obtained by removing the central pixel from any one of 7 pixels and 5 × 9 pixels. In addition, the determination method of the neighboring pixels and the pixel connectivity determination condition including the predetermined number of pixels whose direction matches the predetermined condition and the predetermined condition where the direction of the predetermined number of pixels match are ,
It is preferably determined according to at least one of the document size, print magnification, camera type and exposure condition. Further, the means for calculating the connectivity between the target pixel and its peripheral pixels is such that the direction of the gradient of the target pixel and the direction of the gradient of adjacent pixels on both sides forming a 90 ° direction are
It is preferable that the pixel of interest has connectivity when both the angle with the gradient direction of the pixel of interest is within 45 °.

[0015]

BEST MODE FOR CARRYING OUT THE INVENTION The image processing method and apparatus according to the present invention will be described below in detail with reference to the preferred embodiments shown in the accompanying drawings.

FIG. 1 is a block diagram showing an embodiment of a digital photo printer to which an image processing apparatus for carrying out the image processing method of the present invention is applied. A digital photo printer (hereinafter referred to as a photo printer) 10 shown in FIG.
A scanner (image reading device) 12 that photoelectrically reads an image captured on the film F, image processing such as edge extraction of image data (image information) read by the scanner 12, operation of the entire photo printer 10, and An image processing device 14 that performs control and the like, and a photosensitive material (photographic paper) is image-exposed with a light beam modulated according to the image data output from the image processing device 14, and is subjected to development processing (finishing).
The image recording device 16 outputs an image as a print. Further, the image processing apparatus 14 is provided with a keyboard 18a and a mouse 18 for inputting various conditions, setting, selection and instruction of processing, instructions for color / density correction, and the like.
An operation system 18 having b is connected to a monitor 20 that displays an image read by the scanner 12, various operation instructions, a setting / registration screen for various conditions, and the like.

The scanner 12 is a device for photoelectrically reading an image photographed on the film F or the like frame by frame.
A variable diaphragm 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 3-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). ) And a converter 34.

In the photo printer 10, a dedicated carrier 28 that can be attached to the main body of the scanner 12 is a film F such as a new photographic system (Advanced Photo System) or a 135 size negative (or reversal) film.
It is prepared according to the type and size of the film, the form of the film such as strips and slides, etc., and various films and processes can be handled by exchanging the carrier 28. An image (frame) photographed on a film and used for print production is conveyed to a predetermined reading position by the carrier 28. Further, as is well known, a film of the new photographic system is formed with a magnetic recording medium, and a cartridge ID, a film take-off, etc. are recorded therein. Further, at the time of shooting or developing, shooting date and time of development, camera It is possible to record various types of data such as the type of developing machine and developing machine. In the carrier 28 corresponding to the film (cartridge) of the new photographic system,
This magnetic information reading means is arranged, the magnetic information is read when the film is conveyed to the reading position, and these various kinds of information are sent to the image processing device 14.

When reading an image photographed on the film F in the scanner 12 as described above, the carrier 28 emits uniform read light emitted from the light source 22 and adjusted in light quantity by the variable diaphragm 24 and the diffusion box 26. When incident on the film F located at a predetermined reading position,
By being transmitted, the projection light carrying the captured image on the film F is obtained. The color image signal input is
As described above, the invention is not limited to reading the light transmitted through the film, and may be a reflective original or an image captured by a digital camera.

The carrier 28 in the illustrated example is a 24-piece 1
It corresponds to a long film F (strips) such as a 35 size film or a cartridge of a new photographic system. As shown schematically in FIG. 2A, the film F is placed at a predetermined reading position. While the image sensor 32 is positioned, the reading position at which the longitudinal direction of the film F is conveyed in the sub-scanning direction orthogonal to the extending direction (main scanning direction) of the RGB 3-line CCD sensor, for example, is set. Conveying roller pairs 28a and 28 sandwiched in the sub-scanning direction
b, and a mask 28d having a slit 28c that extends in the main scanning direction and that corresponds to the reading position and that restricts the projection light of the film F into a predetermined slit shape. The film F is positioned at the reading position by the carrier 28 and is fed with the reading light while being conveyed in the sub-scanning direction.
As a result, the film F is two-dimensionally slit-scanned by the slit 28c extending in the main scanning direction, and the image of each frame photographed 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. As shown in FIG. 2B, the image sensor 32
Is a line CCD sensor 32 for reading the R image
Line CCD sensor 32G for reading R and G images
And line CCD sensor 32 for reading B image
In the so-called 3-line color CCD sensor having B, each line CCD sensor extends in the main scanning direction as described above. The projection light of the film F is separated into three primary colors of R, G and B by the image sensor 32 and photoelectrically read. The R, G, and B output signals output from the image sensor 32 are amplified by the amplifier 33 and sent to the A / D converter 34, and in the A / D converter 34, for example, RGB of 12 bits, respectively.
After being converted into digital image data, the image processing device 14
Is output to.

In the scanner 12, when the image photographed on the film F is read, a prescan (first image reading) for reading at a low resolution and a fine scan (first image reading for obtaining image data of an output image) are performed. The second image reading) and the second image reading are performed. Here, the prescan is performed under prescan reading conditions set in advance so that the scanner 12 can read all the images of the target film F without saturation of the image sensor 32. On the other hand, the fine scan is performed from the prescan data under the fine scan reading condition set for each frame 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 similar image data except that the resolution and the output image signal level are different.

It should be noted that the scanner 12 used in the photo printer 10 is not limited to such a slit scanning reading, and may be a plane reading for reading the entire surface of a film image of one frame at a time. Good. In this case, for example, an area sensor such as an area CCD sensor is used, insertion means for R, G, and B color filters is provided between the light source 22 and the film F, and is inserted in the optical path of the light emitted from the light source 22. Then, the reading light transmitted through the color filters is applied to the entire surface of the film F, the transmitted light is imaged on the area CCD sensor, and the entire film image is read by sequentially switching the R, G and B color filters. Thus, the image photographed on the film F is separated into the 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 which carries out the image processing method of the present invention. FIG. 3 shows 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, and a prescan (frame).
Memory 40, fine scan (frame) memory 4
2. It has a prescan data processing unit 44, a fine scan data processing unit 46 and a condition setting unit 48 that perform edge portion extraction and various image processing that are features of the present invention.
Note that FIG. 3 mainly shows a portion related to image processing, and the processing device 14 is a CP that controls and manages the entire photo printer 10 including the processing device 14 in addition to this.
U, 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 also provided.
Is connected to each part via this CPU or the like (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 section 36.
The scanner correction unit 36 corrects the DC offset in order to correct the sensitivity variation and dark current for each pixel of the RGB digital image data due to the 3-line CCD sensors 32R, 32G and 32B of the image sensor 32 of the scanner 12.
Data correction of read image data such as dark correction, defective pixel correction, and shading correction is performed. The digital image signal that has been subjected to correction processing of sensitivity variations and dark current for each pixel in the scanner correction unit 36 is output to the LOG conversion processor. The LOG converter 38 performs logarithmic conversion processing, gradation conversion of digital image data, and conversion into digital image density data. For example, a look-up table (LUT) is used for correction by the scanner correction unit 36. The converted digital image data of, for example, 12 bits is converted into digital image density data of 10 bits (0 to 1023).

The digital image density data converted by the LOG converter 38 is stored (stored) in the prescan memory 40 for the prescan image data and in the fine scan memory 42 for the fine scan image data, respectively. . The prescan memory 40 is obtained by prescanning the film F by the scanner 12,
It is a frame memory for storing or storing low resolution image density data of the entire one frame of the film F which has undergone various data correction and logarithmic conversion processing for each color of RGB. The pre-scan memory 40 needs at least a capacity to store image density data of RGB three colors of one frame of the film F, but may have a capacity to store image density data of a plurality of frames. A large number of memories each having a capacity for one frame may be provided. The prescan image data stored in the prescan memory 40 is read by the prescan data processing unit 44.

On the other hand, the fine scan memory 42 obtains high resolution image density data of one frame of the film F, which is obtained by fine scanning of the film F by the scanner 12 and has undergone various data correction and logarithmic conversion processing, in RGB format. A frame memory for storing or storing each color. The fine scan memory 42 has a capacity to store at least the image density data of three colors of RGB of the image of two frames of the film F, and while writing the image density data of one frame, the image density of another one frame is written. It is preferable that the data is read and various processes for performing the edge extraction, which is a feature of the present invention, are simultaneously performed in the fine scan data processing unit 46. However, the present invention is not limited to this and one frame It may have a capacity to store the image density data of 1) and process it frame by frame. Further, it may be a memory provided with a large number of memories each having a capacity for one frame and used as a toggle memory, for example. The fine scan image data stored in the fine scan memory 42 is read by the fine scan data processing unit 46.

A prescan data processing unit 44 for performing various image processing necessary for displaying 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 later.
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 C.
Predetermined gradation correction, color conversion, density conversion, etc. are calculated by a look-up table (hereinafter represented by LUT) or matrix (hereinafter represented by MTX) so that a color image can be reproduced on the RT display screen. It is for performing image processing. The image data conversion unit 52 includes the image processing unit 5
The image data processed by 0 is thinned out as necessary to match the resolution of the monitor 20, and similarly, 3
The data is converted into image data corresponding to the display on the monitor 20 by using a D (three-dimensional) LUT or the like and is displayed on the monitor 20. The processing conditions in the image processing unit 50 are set by the 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 performs various image processing necessary for outputting as a color print from 6 and edge extraction of the present invention includes an image processing unit 54 and an image data conversion unit 56. Here, the image processing unit 54
Is the image data read by the scanner 12 and stored in the fine scan memory 42 according to the image processing conditions set by the condition setting unit 48, which will be described later, on the color paper with desired density, gradation and tone as a color print. In order to be able to reproduce a color image, or a high-quality image in which sharpness enhancement, grain suppression, etc. have been performed after the edge portion extraction which is the object of the present invention, by LUT, MTX calculator, low pass filter, adder / subtractor It is for performing various image processing such as color balance adjustment, gradation adjustment, color adjustment, density adjustment, saturation adjustment, electronic scaling, and sharpness enhancement (edge enhancement; sharpening). Details thereof will be described later. To do.

The image data conversion unit 56 includes an image processing unit 54.
The image data processed by is converted into image data corresponding to image recording by the image recording device 16 using, for example, a 3DLUT, and is supplied to the image recording device 16. The image recording device 16 includes a fine scan data processing unit 46.
It is for outputting as a finished print in which a color image is reproduced based on the image data output from.

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

Specifically, the setup section 58 reads out the prescan image data from the prescan memory 40, creates a density histogram from the prescan image data, average density, LATD (large area transmission density), and highlight. Image feature quantities such as (lowest density) and shadow (highest density) are calculated. Based on the calculated image feature amount, the image sensor 32 is slightly lower in density than the minimum density of the image.
Fine scan reading conditions, for example, the light amount of the light source 22, the aperture value of the variable diaphragm 24, the (line CCD sensors 32R, 32G, 32B) of the image sensor 32 so that the (line CCD sensors 32R, 32G, 32B) are saturated.
Set the storage time etc. It should be noted that the fine scan reading conditions may be changed from all the elements corresponding to the output level of the image sensor with respect to the prescan reading conditions, and only one of the elements such as the aperture value is changed. Alternatively, only a plurality of elements such as the aperture value and the storage time may be changed. Furthermore, the setup section 5
Reference numeral 8 sets the image processing conditions such as the color balance adjustment and the gradation adjustment described above in accordance with the density histogram, the image feature amount, and an instruction or the like given by the operator as necessary.

The key correction unit 60 is an adjustment amount of density (brightness), color, contrast, sharpness, saturation, etc. set by a key (not shown) provided on the keyboard 18a or the operation system 18, and the mouse 18b. Adjustment amount of the image processing condition (for example, LU
A correction amount of T, etc.) 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 supplies the supplied image processing conditions to the image processing unit 50 of the prescan data processing unit 44 and the image processing unit 54 of the fine scan data processing unit 46. The image processing condition is set, and the image processing condition set for each portion 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 extracting the edge portion, which is a feature of the present invention, will be described in detail. FIG. 4 shows the image processing unit 5.
4 is a block diagram showing the outline of an example of Embodiment 4. As shown in FIG. 4, the image processing unit 54 includes a color density gradation converting means 64 for converting the density, color and gradation of the image data, a saturation converting means 66 for converting the saturation of the image data, and an image data Digital magnification conversion (electronic scaling) means 6 for converting the number of pixels
8. An edge portion extracting means 70 for extracting an edge portion and an image processing block 72 for performing various image processing such as sharpness enhancement, grain suppression, and conversion of the density dynamic range of image data as required.

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 the LUT or the like. Further, the saturation conversion means 66 is the color density gradation conversion means 6
The color saturation data of the image data obtained in step 4 is converted according to the MTX operation or the like. Further, 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. The number of pixel data of image data is increased or decreased by performing or thinning. The edge part extraction means 70 determines whether the target pixel is an edge part or a granular part and extracts the edge part. The image data subjected to the edge part extraction is input to the image processing block 72. To be done. In the image processing block 72, various other image processings such as sharpness enhancement for the edge portion extracted above and graininess suppression for the granular portion are performed.

FIG. 5 is a block diagram showing the outline of an embodiment of the edge portion extracting means 70. As shown in FIG. 5, the edge portion extraction means 70 includes a color tone conversion means 74, a luminance signal generation means 76, a template 78 used for calculating a gradient, and a means 8 for calculating a gradient.
0, a means 81 for storing the calculated gradient, a means 82 for calculating the connectivity of the target pixel and the like, a means 84 for calculating the directivity for each RGB, and a means 86 for determining and extracting the edge portion.

The color tone conversion means 74 is for converting the color tone signal level of the image data into an original image signal. The luminance signal generation means 76 converts the R, G, and B color signals of the original image signal whose color tone has been converted by the color tone conversion means 74 into luminance signals.
The color signals of R, G and B are weighted and converted into the luminance signal Y. As the conversion formula, for example, the following formula is exemplified. Y = 0.3R + 0.59G + 0.11B

The template 78 is for obtaining a gradient (corresponding to a gradient, so-called differentiation) representing the direction and intensity of the edge of the pixel of interest and its peripheral pixels. For example, in the case of a template consisting of a 3 × 3 matrix. The Sobel operator as shown in FIG. 10 may be used, and it is not particularly limited. Besides this, for example, the Prewitt operator, Kirsh (Kir)
sch) operator and the like, all of which are for calculating the magnitude and direction of the density gradient in the pixel of interest. The matrix forming the template used in the present invention, which serves as these operators, is not limited to 3 × 3 as shown in FIG. 10, and the size and shape thereof are not particularly limited. May be As the matrix of the template of the present invention, for example, a square matrix of 5 × 5, 7 × 7, 9 × 9, etc., is also used as 3 × 5 or 3
A non-square matrix such as × 7 or 5 × 9 can also be used.

The gradient calculating means 80 calculates the gradient of each target pixel and its peripheral pixels using the template 78 for the image data converted into the luminance signal by the luminance signal generating means 76, as described above. For example, in the case of image data of 3 × 3 pixels centered on the pixel of interest, the sum of products is calculated for these image data by using 8 types of 3 × 3 templates respectively indicating the 8 directions shown in FIG. Then, the gradient of the pixel of interest whose intensity and direction are the directions indicated by the obtained sum of products and the template in which the sum of products is maximum is calculated. Similarly, the gradient is calculated for the peripheral pixels. Next, the gradient storage means 81 stores the values of the gradient of each pixel of interest and its surrounding pixels calculated by the gradient calculation means 80. The connectivity calculator 82 calculates the connectivity of the target pixel from the stored gradients of the target pixel and the peripheral pixels. That is, the connectivity calculating unit 82 compares the gradient direction of the pixel of interest with the gradient direction of the neighboring pixels of the pixel of interest, determines the presence or absence of connectivity according to the connectivity determination condition, and determines the connectivity. It is calculated, and more specifically, connectivity is determined when the gradient directions of a predetermined number of these neighboring pixels match a predetermined condition. The connectivity determination condition will be described later. Also,
The directionality calculating means 84 for each RGB uses the template 78 for each R, G, B for each pixel of interest,
The gradient is calculated for each and the directionality is calculated.

The edge portion determining / extracting means 86 determines the edge portion of the pixel of interest based on the connectivity of the pixel of interest calculated by the connectivity calculating means 82 and the directivity calculated by the directionality calculating means 84 for each RGB. The edge portion is extracted by determining whether or not , that is, the granular portion. The image data for which the edge portion has been determined and extracted is sent to the image processing block 72, and image processing (frequency processing) such as sharpness enhancement or granularity suppression processing is performed.

The image processing apparatus and the digital photo printer using the same according to the present invention are basically constructed as described above. Hereinafter, the operation of the image processing apparatus and the digital photo printer of the present invention and the image processing method of the present invention will be described.

The operator operates the film F (frame to be read)
The carrier 28 corresponding to is loaded into the scanner 12, the film F is set at a predetermined position of the carrier 28, and after inputting necessary instructions such as finishing information and a print size to be produced, an instruction to start producing a print is given. Thereby, the aperture value of the variable aperture 24 of the scanner 12 and the image sensor 3
The accumulation time of 2 (line CCD sensors 32R, 32G, 32B) is set according to the prescan reading conditions.
After that, the carrier 28 conveys the film F in the sub-scanning direction at a speed according to the pre-scanning, the pre-scanning is started, the film F is slit-scanned, the projection light is imaged on the image sensor 32, and the film F is The image captured in R is separated into R, G, and B, and is photoelectrically read at a low resolution. Here, the prescan and the fine scan may be performed one frame at a time, or the prescan and the fine scan may be continuously performed on all the frames or a predetermined plurality of frames. In the following example, in order to simplify the description, the image reading of one frame will be described as an example.

The output signal of the image sensor 32 by the pre-scan is amplified by the amplifier 33, and the A / D converter 3
4, and after being converted into digital image data, is output to the image processing device 14 of the present invention. The digital image data input to the image processing device 14 is stored in the scanner correction unit 36.
After performing a predetermined correction of the dark current of the image sensor 32, the image sensor 32 is sent to the LOG converter 38, and the density range corresponding to the prescan, for example, the density range of 4 with the density D is 10b.
It is converted using the LUT so as to be allocated to the it data, and is converted into prescan image data, and the prescan image data is stored in the prescan memory 40.

When the prescan image data is stored in the prescan memory 40, the setup section 58 of the condition setting section 48 reads it out and creates a density histogram,
Calculate image features such as highlights and shadows,
Set the scanning conditions for fine scan, and then scan the scanner 12
In addition, various image processing conditions such as gradation adjustment and gray balance adjustment are set and supplied to the parameter integration unit 62. Parameter integration unit 6 that received the image processing conditions
2 sets this in a predetermined portion (hardware and software) of the prescan data processing unit 44 and the fine scan data processing unit 46.

When performing the verification, the prescan image data is read from the prescan memory 40 by the prescan data processing unit 44, image processed under the image processing conditions set in the image processing unit 50, and then the image is processed. The data is converted by the data conversion unit 52 and displayed on the monitor 20 as a simulation image. The operator confirms (verifies) the image, that is, the processing result, by looking at the display on the monitor 20, and adjusts the color, density, gradation and the like using the adjustment key or the like set on the keyboard 18a as necessary. The input of this adjustment is sent to the key correction unit 60, the key correction unit 60 calculates the correction amount of the image processing condition according to the adjustment input, and sends it to the parameter integration unit 62. The parameter integration unit 62 uses the image processing unit 50 according to the sent correction amount.
And LUT and MTX of 54 are corrected. Therefore, the image displayed on the monitor 20 also changes according to this correction, that is, the adjustment input by the operator.

When the operator determines that the image of this frame is proper (verification is OK), the operator gives an instruction to start printing by using the keyboard 18a or the like. As a result, the image processing conditions are determined, the aperture value of the variable aperture 24 in the scanner 12 is set in accordance with the fine scanning reading conditions, and the carrier 28 moves the film F at a speed corresponding to the fine scanning. The paper is conveyed and the fine scan is started. When the verification is not performed, the fine scan data processing unit 4 by the parameter integration unit 62 is used.
When the setting of the image processing conditions to the image processing unit 54 of No. 6 is completed, the image processing conditions are determined and the fine scan is started. The fine scan is performed in the same manner as the pre-scan except that the reading conditions such as the aperture value of the variable aperture 24 are different. The output signal from the image sensor 32 is amplified by the amplifier 33, and the A / D converter of the processing device 14 is obtained. The data is converted into digital density data in 34, subjected to predetermined processing in the scanner correction section 36, and sent to the LOG converter 38. In the LOG converter 38, the fine scan digital image data is processed with a density resolution higher than that in the prescan, and is converted by the LUT so as to allocate the density range of 2 with the density D to 10 bit data, and the fine scan image data is obtained. Then, it is sent to the fine scan memory 42.

In the image processing section 54, the color density gradation converting means 64 converts the density data, color data and gradation data of the fine scan image data in accordance with the look-up table, and the saturation converting means 66.
The saturation data of the image signal is converted according to the matrix calculation. Then, according to the size of the color image to be output to the color paper, the electronic scaling unit 68 increases or decreases the pixel data number of the image data signal, and then the image signal is
It is input to the edge part extraction means 70.

The original image signal whose color tone has been converted by the color tone converting means 74 is converted into the luminance signal Y by the luminance signal generating means 76 and input to the gradient calculating means 80. In the gradient calculating means 80, the template 7
8 is used to calculate a gradient, which is a vector amount representing the magnitude and direction of the density gradient of the target pixel and its peripheral pixels.

For example, for 3 × 3 image data composed of a target pixel and peripheral pixels as shown in FIG.
The 3 × 3 templates a1 to a8 shown in FIG. 0 are used to perform the product-sum operation as described above, and the gradient of the pixel of interest having the intensity and direction from the template corresponding to the largest product-sum and maximum product-sum is calculated. To calculate. Next, from these peripheral pixels, two adjacent pixels on both sides in the direction of 90 ° (direction orthogonal to) the gradient direction of the pixel of interest are selected as neighboring pixels used for determining the presence or absence of connectivity, For these two adjacent pixels,
A 3 × 3 image centered on the adjacent pixel is taken, and the gradient of the adjacent pixel is calculated in the same manner. At this time,
When the gradient direction of the pixel of interest is as indicated by an arrow in FIG. 6, the one indicated by a circle is the adjacent pixel. For example,
For 3 × 3 image data, if the direction is the direction indicated by the arrow in FIG. 11B, the pixel value 1 at the upper left corner in the figure is 1
And two pixels having a pixel value of 5 in the lower right corner in the figure are two adjacent pixels.

The gradient calculating means 80 calculates the gradient of each of these adjacent pixels and obtains its direction. Then, the gradients of the target pixel and the peripheral pixels thus obtained are stored in the gradient storage unit 81. The connectivity calculator 82 determines the connectivity of the target pixel from the stored gradient directions of the target pixel and the peripheral pixels. When the gradient directions of the two adjacent pixels are both within 45 ° with the gradient direction of the pixel of interest, the pixel of interest is determined to have connectivity.

On the other hand, the directionality calculating means for each RGB (hereinafter,
The directionality calculating means) 84 similarly calculates the gradient for the three image data of R, G, B relating to the same target pixel using the template 78, and as shown in FIG. 7, for each R, G, B. Calculate the directionality of.

The edge portion determination / extraction means 86 determines and extracts the edge portion from the connectivity of the pixel of interest and the directionality of each RGB calculated by the connectivity calculation means 82 and the directionality calculation means 84, respectively. When the pixel of interest has connectivity and the directionality of each RGB has a directionality of 45 ° or less, the pixel of interest is determined to be an edge portion and is left as an edge portion, and is not so. In some cases, it will be discarded. Here, the directionality of each RGB is 45
Having directionality within ° means that, when attention is paid to a channel of interest, for example, G, both the R direction and the B direction are within 45 ° with respect to the G direction as shown in FIG. 7.

The direction of the gradient calculated by the gradient calculating means 80 for the pixel of interest determined to be the edge portion in this way is called the edge direction,
The magnitude of the gradient is called the edge strength. The strength of this edge represents the inclination of the edge, and it can be said that an edge having a large strength is a sharp edge having a large inclination. Therefore, by using this strength, the degree of sharpness enhancement or graininess suppression of the image, that is, the gain that determines the strength can be controlled. The intensity of the gradient is set to 0 for the target pixel that is not determined to be the edge portion. For example, in the edge part, the gain of the high frequency component of the image data is increased according to the intensity of the gradient to emphasize the sharpness of the image, and in the flat part (granular part) not including the edge part, the gain of the middle frequency component of the image data is increased. The grain size can be reduced in accordance with the intensity of the gradient to suppress graininess of the image.

More specifically, up to a predetermined gradient intensity, the value increases from a value smaller than 1.0 to a value larger than 1.0 in accordance with the gradient intensity, and within a range larger than the predetermined gradient intensity. A look for medium- and high-frequency gain control in which a function that becomes constant is the gain of the medium-frequency component, and a function that is similar to the gain of the medium-frequency component and has a value larger than the gain of the medium-frequency component is the gain of the high-frequency component. An up table (LUT) is prepared, and for the sharpness enhancement of the edge portion, the intensity of the gradient is considered to be the intensity of the edge, and the gain intensity is calculated by the gain control LUT for the medium / high frequency components according to the gradient intensity. In the non-edge portion, the gradient strength is considered to be 0, and the gain strength is calculated similarly. In this way, the gain control according to the gradient intensity of the pixel of interest is performed. At the edge part, the sharpness is emphasized by emphasizing the middle and high frequency components. Pixels with higher edge strength will have stronger sharpness. At this time, the gain of the medium frequency component is set to be smaller than the gain of the high frequency component in order to suppress the granular roughness caused by the sharpness enhancement. Especially in the non-edge part, the gain of this medium frequency component is 1.0
By making it smaller, graininess can be effectively suppressed even in a film having poor graininess. At the same time, the gain of the high frequency component is 1.0 in order to maintain the sharpness.
Make it bigger. At this time, a sharpness image with an edge feeling can be obtained by applying a gain slightly weaker than the gain of the edge portion. Further, the negative density of the pixel of interest may be calculated, and in the case of underexposure, grain suppression may be more strongly applied.

The image data for which the edge portion has been determined and extracted is sent to the image processing block 72. The image processing block 72 performs image processing such as sharpness enhancement and grain suppression. After that, the image-processed image data 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 is a printer (printing device) for exposing a photosensitive material (photographic paper) to record a latent image according to input image data, and a predetermined process for printing the exposed photosensitive material for printing. And a processor (developing device) for outputting as. In a printer, for example, after cutting a photosensitive material into a predetermined length according to a finished print, a back print is recorded, and then three kinds of light of R exposure, G exposure, and B exposure according to the spectral sensitivity characteristics of the photosensitive material are recorded. The beam is modulated in accordance with the image data output from the processing device 14 to be deflected in the main scanning direction, and the photosensitive material is conveyed in the sub-scanning direction orthogonal to the main scanning direction. Two-dimensional scanning exposure is performed to record a latent image and the latent image is supplied to the processor. The processor receiving the light-sensitive material on which the latent image is formed is subjected to predetermined wet development processing such as color development, bleach-fixing, washing with water, and dried to obtain a finished print.
The film is sorted into a predetermined unit such as one film and collected.

The operation of the image processing apparatus and the digital photo printer of the present invention has been basically described above including the image processing method of the present invention. In particular, referring to FIG. 8 for the image processing method of the present invention, reference will be made below. And explain. FIG. 8 is a flowchart showing each processing of the image processing method of the present invention executed in the above-mentioned edge portion extracting means 70. In FIG. 8, in step 1, the gradient direction and intensity of the pixel of interest are calculated. In step 2, the gradients of the two adjacent pixels in the direction of the gradient of the pixel of interest and the direction of 90 ° are calculated and the directionality thereof is checked. In step 3, the directions of the two adjacent pixels and the target pixel are compared with each other, and if both have a directional property within 45 °, it is assumed that they have connectivity. In step 4, the gradient of the pixel of interest is calculated for each of the RGB channels and the directionality thereof is checked. Finally, in step 5, it is determined whether or not the pixel of interest is an edge portion based on the connectivity previously obtained and the directivity for each RGB.

In the above embodiment, the pixel of interest is centered,
To determine the presence / absence of connectivity by using 8 types of 3 × 3 templates each showing 8 directions shown in FIG. 10 for 3 × 3 pixel image data having 8 surrounding pixels as peripheral pixels. As the method of taking the neighboring pixels used for the above, two adjacent pixels on both sides in the direction of 90 ° in the gradient direction of the pixel of interest are selected from among the surrounding pixels, and as a determination condition of connectivity, that is, as a determination condition of connectivity, , The angles of the gradient directions of the adjacent pixels on both sides of the gradient direction of the pixel of interest are both within 45 °, and there is connectivity as a condition for determining an edge portion, that is, a condition for being an edge portion, The case where the directivity for each RGB is selected to have a directivity within 45 ° has been described as a representative example, but the present invention is not limited to this, and the target pixel and peripheral pixels and the connectivity are not limited. Any method may be used for the neighboring pixels for determining the presence / absence, and any template may be used as long as it corresponds to the method of taking the target pixel and peripheral pixels As long as the part can be determined, the connectivity determination condition and the edge part determination condition may be set in any manner.

For example, the size and shape of the target pixel and its peripheral pixels used in the present invention are not particularly limited, and in addition to 3 × 3 pixels, 5 × 5, 7 × 7, 9 × 9, etc. It may be a square pixel, a non-square rectangular pixel such as 3 × 5, 3 × 7 or 5 × 9, or a pixel of any shape. Therefore, in addition to the 8 pixels around the pixel of interest,
You may make it look over a wider pixel range, such as a pixel, 20 pixels, and 24 pixels. The template used in the present invention is also not particularly limited in size, shape, or number, and in addition to a 3 × 3 square matrix, 5 × 5 or 7 × 7 depending on the target pixel used and its peripheral pixels. And 9x
Even with a square matrix such as 9, 3x5, 3x7, or 5x9
A non-square rectangular matrix such as, or a template having another shape may be used. The number of templates is not limited to eight types indicating eight directions, and may be more or less.

There are no particular restrictions on the size or shape of the neighboring pixels for determining the presence or absence of connectivity, and two neighboring pixels on both sides orthogonal to the gradient direction of the pixel of interest can be used. , Some peripheral pixels may be viewed at the same time, and for example, the above-described square pixel, non-square rectangular pixel, or pixel of any shape excluding the pixel of interest centered on the pixel of interest may be used. The 1 × 3 pixels, the 1 × 5 pixels, the 3 × 5 pixels, the 3 × 7 pixels, which are more frequently present in the direction orthogonal to the (gradient) direction of this pixel of interest, as shown in FIG. It is preferable to use rectangular pixels such as × 9 pixels excluding the central pixel. The reason for this is that the edges of the image have a certain length, and in order to see the connectivity, it is good to take a wide width in the edge length direction, that is, in the direction orthogonal to the direction of the pixel of interest. It should be noted that when the edge direction of the target pixel is oblique, a plurality of pixels are taken in the oblique direction orthogonal to this, but when it is in a plurality of columns, for example, 3 × 5.
When pixels are taken, there is an array of 4 pixels between an array of 5 diagonal pixels, but it is preferable to take all 23 pixels including all of these as neighboring pixels.

Further, in the present invention, as the condition for determining connectivity with connectivity, the gradient direction of the pixel of interest is compared with the gradient direction of neighboring pixels of the pixel of interest, and a predetermined number of neighboring pixels are selected. The direction of the pixel matches the predetermined condition, but it is preferable that 50% or more of the direction of the neighboring pixel is within 45 ° with the direction of the pixel of interest. That is, the proportion of the predetermined number of pixels in which the directionality of the gradient in the neighboring pixels for determining the connectivity matches the target pixel under the predetermined condition may be at least 50%, more preferably 70% or more, and further preferably Is 80
% Or higher, most preferably 90% or higher, of course 1
Although it may be 00%, it can be changed according to various conditions as described later. Further, the predetermined condition of the directionality of the neighboring pixels is preferably within 45 °, more preferably 3
It is better to be within 0 °, and of course, it may be within 0 ° (perfect match) or within any angle within the range of 0 ° to 45 °, but in order to eliminate the omission of connectivity and improve the determination accuracy. Preferably has a certain width. Also in this respect, 4
It is preferably within 5 ° or within 30 °. This predetermined condition can also be changed according to various conditions described later. Of course, one of the extremely preferable connectivity determination conditions is that all the gradient directions of neighboring pixels for determining connectivity of two adjacent pixels on both sides of the target pixel are within 45 ° as described above. .

The directionality condition for each RGB, which is one of the edge condition determination conditions for determining an edge part, is exactly the same as the above-described predetermined condition for the directionality of neighboring pixels for connectivity determination. The angle may be within any angle within the range of 0 ° to 45 °, but the directionality within 45 ° of the above embodiment is preferable, and the directionality within 30 ° is more preferable. This directional condition can also be changed according to various conditions described later. Furthermore, a predetermined condition for the directionality of neighboring pixels for determining connectivity and R for determining edge portions are used.
The directionality condition for each GB is the same as within 45 ° in the above embodiment, but may be different.

Here, as described above, the size (shape) and number of the template, the way of taking the neighboring pixels, the connectivity determination condition, that is, the predetermined condition of the neighboring pixels and the predetermined directionality of the neighboring pixels. The ratio of pixels satisfying the condition and the condition of the directivity for each RGB can be changed variously.
For example, the original type (high-sensitivity negative film, low-sensitivity negative film, reversal film, reflective original, images taken by a digital camera, etc.), original size (240 (A
PS), 110, 135, 120 and 220 (Brownie, etc.), print magnification, print size, camera type and exposure conditions (under, over) at the time of shooting, etc. At least 1
It is preferable to determine it according to one. It is needless to say that the method of determining the above various conditions according to at least one of these items is not limited. Here, among these items, for example, the print magnification and the document type are
Although it has a great influence on conditions such as how to take neighboring pixels and the conditions for determining connectivity and the directionality of each RGB, when the print magnification changes, the way to take neighboring pixels is mainly changed to meet these conditions. It is preferable not to change, and when the original type, for example, the film sensitivity is changed, these conditions are mainly changed, that is, the conditions for high-sensitivity film are stricter than those for low-sensitivity film, and the way of taking neighboring pixels is not changed. Is preferred. Furthermore, it is preferable that the exposure conditions at the time of photographing are mainly made weaker in the case of underexposure and the way of taking neighboring pixels is not changed.

FIG. 9 shows the effect of this embodiment in comparison with the conventional one. First, FIG. 9A shows the case of the related art, in which the directionality of each RGB is not determined, and one of the adjacent pixels is determined to be within the allowable range (within 45 °). In this case, in addition to the white line that is the original edge portion, a large number of white particles that represent granular portions remain. In contrast,
In (b), the directivity for each RGB is not seen, but both adjacent pixels are within the allowable range (within 45 °). According to this, the determination of the edge portion becomes more accurate, and the number of particles is considerably reduced. Further, (c) is the same as the conventional one with respect to the adjacent pixel, and either one of the adjacent pixels is within the allowable range, but in addition to this, the directionality for each RGB is determined. . That is, this is the case where both channels other than the channel of interest have the allowable directionality. In this case too, the particles are largely removed.

Further, FIG. 9D shows a combination of (b) and (c) in the case of the present embodiment described above.
That is, for adjacent pixels, both are within the allowable range,
In addition, the directionality of each RGB (both channels other than the channel of interest are within tolerance) is also viewed. In this case, the edge determination is more accurate, and almost no particles remain. Further, in (e), both adjacent pixels have the same direction, and also with respect to RGB, both except the attention channel have the same direction. This also has the same effect as (d).

As described above, according to the present embodiment, since both adjacent pixels are within the allowable range and the directionality of each RGB is also viewed, the edge portion can be extracted more accurately than before. became.

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

[0068]

As described above, according to the present invention, it is possible to extract an edge portion more accurately than before, and it is possible to obtain a high quality output image.

[Brief description of drawings]

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

2A is a schematic perspective view for explaining an embodiment of a carrier mounted on the digital photo printer shown in FIG. 1, and FIG. 2B is a digital photo printer shown in FIG. 2 is a conceptual diagram of an example of the image sensor of FIG.

FIG. 3 is a block diagram of an embodiment of an image processing apparatus for carrying out the image processing method of the present invention for the digital photo printer shown in FIG.

4 is a block diagram of an embodiment of an image processing unit of a fine scan image data processing unit of the image processing apparatus shown in FIG.

FIG. 5 is a block diagram showing an outline of the edge part extraction means shown in FIG.

FIGS. 6A to 6D are explanatory diagrams showing the target pixel and its adjacent pixels.

7A to 7C are RGs in the present embodiment.
It is explanatory drawing which shows the directionality determination for every B.

FIG. 8 is a flowchart showing an outline of an edge extraction method according to this embodiment.

FIG. 9 is a drawing-substituting photograph showing the effect of the present embodiment in comparison with the related art, where (a) is the related art and (b) to (e) are the present embodiment.

10 (a1) to (a8) are explanatory diagrams showing an example of a template used for edge portion extraction.

FIG. 11A is an explanatory diagram showing an example of a 3 × 3 image composed of a target pixel and its peripheral pixels, and FIG.
It is explanatory drawing which shows the gradient direction of the attention pixel of (a).

FIG. 12 is an explanatory diagram showing an example of neighboring pixels selected for connectivity determination with respect to a pixel of interest in the present invention.

[Explanation of symbols]

10 Digital Photo Printer 12 scanner 14 (Image) processing device 16 Image recording device 18 Operation system 18a keyboard 18b mouse 20 monitors 22 Light source 24 variable aperture 26 diffusion box 28 careers 30 Imaging lens unit 32 image sensor 32R, 32G, 32B line CCD 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 section 50, 54 Image data conversion unit 58 Setup Department 60 key correction section 62 Parameter integration unit 64 color density gradation conversion means 66 Saturation conversion means 68 Electronic scaling (digital magnification conversion) means 70 Edge Part Extraction Means 72 Image processing block 74 Color tone conversion means 76 Luminance signal generating means 78 templates 80 Gradient calculation means 81 Gradient storage means 82 Connectivity calculation means 84 Directional calculation means (for each RGB) 86 Edge determination / extraction means

─────────────────────────────────────────────────── ─── Continuation of front page (58) Fields surveyed (Int.Cl. ⁷ , DB name) H04N 1/40-1/409 H04N 1/46 G06T 9/20 G06T 7/60

Claims (12)

(57) [Claims] 1. An image processing method for performing a predetermined image processing on a color image signal, comprising: from a pixel value of a target pixel of an image formed by the color image signal which is an image processing target and pixel values of its peripheral pixels, Gradients representing the edge direction and intensity of the target pixel and its peripheral pixels are calculated and stored, and the connectivity between the target pixel and its peripheral pixels is calculated from the stored gradient direction, and each R , G, and B, the gradient of the pixel of interest is calculated to calculate the directionality of each RGB of the pixel of interest. From the connectivity and the directionality of each RGB, the pixel of interest is By determining whether it is an edge part,
An image processing method characterized by performing edge extraction. 2. When calculating the connectivity between the pixel of interest and its peripheral pixels, a gradient direction of the pixel of interest is compared with a gradient direction of a pixel adjacent to the pixel of interest to determine a predetermined value of the neighboring pixels. The image processing method according to claim 1, wherein connectivity is established when the directions of several pixels match a predetermined condition. 3. A case where the directions of a predetermined number of pixels among the neighboring pixels match a predetermined condition means that 50% or more of the directions of the neighboring pixels are within 45 ° with respect to the direction of the target pixel. The image processing method according to claim 2, wherein: 4. The neighboring pixels are 1 × 3 pixels, 1 × 5 pixels, 3 × 5 pixels, 3 × 7 which are present mainly in the target pixel and are present in a direction orthogonal to the gradient direction of the target pixel. The image processing method according to claim 2, wherein the image processing method is a pixel obtained by removing the central pixel from any one of the pixel and the 5 × 9 pixel. 5. A condition for determining connectivity of pixels including a method of taking the neighboring pixels, a predetermined number of the pixels whose directions match the predetermined condition, and a pixel including the predetermined condition in which the directions of the predetermined number of pixels match. The image processing method according to any one of claims 2 to 4, wherein the image processing method is determined according to at least one of a document type, a document size, a print magnification, a camera type, and an exposure condition. 6. When calculating the connectivity between the target pixel and its peripheral pixels, the gradient direction of the target pixel is the direction of the gradient of the target pixel and the gradient direction of adjacent pixels on both sides forming a 90 ° direction. 2. The image processing method according to claim 1, wherein connectivity is established when both the angle formed with the direction and the angle formed with the direction are within 45 °. 7. An image processing apparatus for performing predetermined image processing on a color image signal, comprising: a pixel of interest of an image formed by the color image signal which is an image processing target and pixel values of its peripheral pixels, Means for calculating a gradient representing the edge direction and intensity of the target pixel and its peripheral pixels, means for storing the calculated gradient, and the target pixel and its peripheral pixels from the stored gradient direction And a means for calculating the directionality of each RGB of the pixel of interest by calculating the gradient of the pixel of interest for each R, G, B channel, and the connectivity and And a means for determining whether or not the pixel of interest is an edge portion based on the directionality of each RGB, thereby performing edge portion extraction. Processing apparatus. 8. The means for calculating the connectivity between the target pixel and its peripheral pixels includes a gradient direction of the target pixel,
The gradient directions of neighboring pixels of the pixel of interest are compared, and connectivity is established when the directions of a predetermined number of pixels of the neighboring pixels match a predetermined condition. Image processing device. 9. The case where the directions of a predetermined number of the neighboring pixels match a predetermined condition means that 50% or more of the directions of the neighboring pixels are within 45 ° with the direction of the target pixel. The image processing apparatus according to claim 8, which is provided. 10. The neighboring pixels are 1 × 3 pixels, 1 × 5 pixels, 3 × 5 pixels, which are centered on the target pixel and extend in a direction orthogonal to a gradient direction of the target pixel,
The image processing apparatus according to claim 8 or 9, wherein the pixel is a pixel obtained by removing a central pixel from any one of 3 × 7 pixels and 5 × 9 pixels. 11. A condition for determining connectivity of pixels including a method of taking the neighboring pixels and a predetermined number of the pixels whose direction matches the predetermined condition and the predetermined condition in which the directions of the predetermined number of pixels match. The image processing apparatus according to claim 8, which is determined according to at least one of a document type, a document size, a print magnification, a camera type, and an exposure condition. 12. The means for calculating the connectivity between the target pixel and its peripheral pixels has a gradient direction of the target pixel and a gradient direction of adjacent pixels on both sides forming a 90 ° direction as the target pixel. The image processing apparatus according to claim 7, wherein the image forming apparatus is connected when the angle formed with the gradient direction is within 45 °.