JP2001218015A - Picture processing method and picture processor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a picture processing method and a picture processor, which most suitably conduct granular suppression/sharpness emphasis processing in accordance with the photographing scene of an original picture or the photographing object of the photographing scene and can obtain the reproduced picture of high definition. SOLUTION: The picture processing method for discriminating the photographing scene of the whole original picture or the local area of the original picture, deciding the processing strength of the granular suppression/ sharpness emphasis processing conducted on picture data based on a discrimination result and conducting the granular suppression/sharpness emphasis processing on picture data of the photographing scene of the whole original picture or the local area of the original picture by using processing strength and the picture processor using the method are supplied.

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 for performing image processing on image data of an original image and an image processing apparatus using the same. The present invention relates to an image processing method and an image processing apparatus that can determine the processing intensity of the graininess suppression / sharpness enhancement processing according to the result of subject determination.

[0002]

2. Description of the Related Art At present, an image photographed on a photographic film (hereinafter referred to as a film) such as a negative film or a reversal film is printed on a photosensitive material (photographic paper) by projecting an image of the film onto the photosensitive material. This is performed by so-called direct exposure (analog exposure) that exposes a material surface.

On the other hand, in recent years, printing apparatuses utilizing digital exposure, that is, optically reading an image photographed on a film, converting the read image into a digital signal, and performing various image processings thereon to perform recording. 2. Description of the Related Art Digital photo printers have been put to practical use in which a photosensitive material is scanned and exposed by recording light modulated according to the output image data to record an image (latent image) and print (finished). This digital photo printer basically includes a scanner (image reading device) for photoelectrically reading an image recorded on a film, and image processing for processing the read image to output image data (exposure conditions). Input device having a device, a printer (image recording device) that scans and exposes a photosensitive material according to image data output from the image input device to record a latent image, and performs development processing on the exposed photosensitive material. And an image output device having a processor (developing device) for printing.

In a scanner, reading light emitted from a light source is incident on a film to obtain projection light carrying an image photographed on the film, and the projection light is transmitted to an image sensor such as a CCD sensor by an imaging lens. An image is read by forming an image and performing photoelectric conversion, and after performing various image processing as necessary, image data (image signal) of the film
To the image processing apparatus. The image processing apparatus sets image processing conditions from image data read by a scanner, performs image processing according to the set conditions on the image data, and outputs the image data to a printer as output image data (exposure conditions) for image recording. send. In a printer, for example, if the apparatus uses light beam scanning exposure, the light beam is modulated in accordance with image data sent from the image processing apparatus, and the light beam is deflected in the main scanning direction and the main scanning direction. The photosensitive material is conveyed in a sub-scanning direction perpendicular to the direction, so that the photosensitive material is exposed (burned) by a light beam carrying an image to form a latent image, and then processed in a processor in accordance with the photosensitive material. To obtain a print (photograph) in which the image photographed on the film is reproduced.

In such a digital photo printer,
Since the exposure conditions at the time of printing can be determined by image data processing using the image as digital image data,
In addition to correcting image skipping and blurring due to backlighting, strobe photography, etc., graininess suppression processing and sharpness enhancement (sharpening) for suppressing noticeable roughness (graininess) in areas with low image density due to photosensitive materials By suitably performing processing and the like, a high-quality print that cannot be obtained by conventional direct exposure can be obtained.

[0006]

However, the above-described graininess suppression processing and sharpness enhancement processing are performed according to the type of the original on which the original image was captured, for example, the type of film having different sensitivities, or the amount of exposure at the time of photography. The processing intensity, which is the processing condition, is changed. As described above, the processing conditions of the graininess suppression processing and the sharpness enhancement processing are determined irrespective of the content of the photographic scene, and thus the processing may not be optimally performed in accordance with the content of the photographic scene. For example, when a portrait scene image of a person is subjected to graininess suppression processing or sharpness enhancement processing using the same processing intensity as a landscape scene, sharpness enhancement becomes strong, and a portrait scene becomes a sharp image. For this reason, an intensity coefficient that satisfies a certain degree is set for both the portrait scene and the landscape scene, and the graininess suppression processing and the sharpness enhancement processing are performed. Therefore, there has been a problem that optimal graininess suppression processing and sharpness enhancement processing cannot be performed on each of the portrait scene and the landscape scene. Although the processing intensity can be corrected manually by the operator, it is not preferable in terms of work efficiency to always correct the processing intensity.

In order to solve such a problem, a graininess suppression / sharpness enhancement processing method for sharpening an edge area of a subject in a photographed image or a fine texture of a background image and obtaining an image in which roughness based on film graininess is suppressed is particularly known. Kaihei 9-2
2460. According to the publication, an image signal is divided into a low-frequency component, an intermediate-frequency component, and a high-frequency component, a high-frequency component signal is emphasized using a high-frequency gain coefficient, and the intermediate-frequency component is calculated using an intermediate-frequency gain coefficient. It is described that by suppressing the image and then combining the processed high frequency component, intermediate frequency component and low frequency component, a sharp reproduced image without roughness can be obtained.

In this method, the high frequency gain coefficient and the intermediate frequency gain coefficient are selected from preset ones, or the characteristics of image data, for example, R (red), G (green) and B (color image) of a color image. It is determined based on an evaluation value such as a correlation value in the middle / high frequency components of the image data of each pixel of (blue). However, since the high frequency gain coefficient and the intermediate frequency gain coefficient are automatically determined independently of the content of the shooting scene of the original image, the optimal grain suppression and sharpness enhancement processing for each of the landscape scene and the portrait scene is still performed. It cannot be applied. Further, the high frequency gain coefficient and the intermediate frequency gain coefficient can also be designated by manual designation by an operator. However, it is not preferable in terms of work efficiency that the operator always monitors the digital photo printer for manual designation.

Therefore, in order to solve the above-mentioned problems, the present invention optimally performs graininess suppression and sharpness enhancement processing according to the shooting scene of the original image or the shooting subject of the shooting scene to obtain a high-quality reproduced image. It is an object of the present invention to provide an image processing method and an image processing apparatus capable of performing the above.

[0010]

According to one aspect of the present invention, there is provided an image processing method for performing image processing on image data of an original image to obtain output image data. Determine the shooting scene of the local region of the original image, based on the determination result, determine the processing intensity of the granular suppression and sharpness enhancement processing to be applied to the image data, using the processing intensity the entire original image, or the It is an object of the present invention to provide an image processing method characterized by subjecting image data of a local area to graininess suppression / sharpness enhancement processing.

[0011] The photographing scene of the original image is determined to be a portrait scene or another scene according to the ratio of the face area of the person in the original image to the original image. In this case, it is preferable that the graininess suppression process is performed more strongly and the sharpness enhancement process is performed weaker than when the scene is determined to be a scene other than a portrait scene.

In addition, the spatial frequency characteristics of the image data of the entire original image are analyzed, and a photographing scene of the entire original image is determined.
It is preferable to determine that the scene is a grain-priority scene in which the graininess suppression process is strongly performed or a sharpness-priority scene in which the sharpness enhancement process is strongly performed. Alternatively, the spatial frequency characteristics of the image data of the local area are analyzed to determine that the shooting scene of the local area of the original image is a grain priority area where the grain suppression processing is strongly applied or a sharpness priority area where the sharpness enhancement processing is strongly applied. Is preferred. In addition, the spatial frequency characteristic is analyzed, and when the spectral value of the intermediate frequency component or the intermediate / high frequency component of the image data of the original image is larger than a predetermined value, a sharpness priority scene or a sharpness priority area where strong sharpness enhancement processing is performed. If the spectrum value is equal to or less than the predetermined value, it is preferable to determine that the scene is a grain-priority scene or a grain-priority region to which the graininess suppression process is to be strongly applied. Further, it is preferable that the contrast of the edge area of the subject in the original image is determined, and the sharpness enhancement processing is weakened according to the contrast.

Further, the present invention is an image processing apparatus for performing image processing on image data of an original image to obtain output image data, wherein the image processing apparatus discriminates a shooting scene of the entire original image or a local region of the original image, A control unit that controls the granular suppression / sharpness enhancement process by determining the processing intensity of the granular suppression / sharpness enhancement process to be performed on the image data based on the determination result, using the processing intensity determined by the control unit. An image processing unit that performs grain suppression and sharpness enhancement processing on the entire original image or the image data of the local area.

[0014]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, an image processing method and an image processing 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 showing an example of a digital photo printer using an image processing method and an image processing apparatus according to the present invention. The digital photo printer (hereinafter, referred to as a photo printer 10) shown in FIG. 1 basically includes a scanner (image reading device) 12 that photoelectrically reads an image captured on a film F, and read image data ( An image processing device 14 that performs image processing of image information and the entire operation and control of the photo printer 10, and images a photosensitive material (photographic paper) with a light beam modulated according to image data output from the image processing device 14. A printer 16 that exposes, develops, and outputs (finished) prints. The image processing apparatus 14 also includes a keyboard 18a and a mouse 1 for inputting (setting) various conditions, selecting and instructing processing, and inputting instructions such as color / density correction.
An operation system 18 having an 8b and a display 20 for displaying an image read by the scanner 12, various operation instructions, a condition setting / registration screen, and the like are connected.

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 28 for making the reading light incident on the film F uniform in the surface direction of the film F, an imaging lens unit 32, R (red), G (green), and B
An image sensor 34 having a line CCD sensor corresponding to each image reading of (blue), an amplifier 36,
An A / D (analog / digital) converter 38.

In the photo printer 10, the type and size of a film such as a new photo system (Advanced Photo System) or a 135-size negative (or reversal) film, the form of a film such as strips and slides, and the like are determined. A dedicated carrier 30 that can be mounted on the main body of the scanner 12 is prepared. By replacing the carrier 30, various types of films and processes can be handled. An image (frame) photographed on the film F and provided for printing is conveyed to a predetermined reading position by this carrier. In such a scanner 12,
When reading an image captured on the film F, the light source 2
The projection light carrying the image photographed on the film F by being incident on the film F positioned at a predetermined reading position by the carrier and transmitting therethrough, the reading light emitted from the lens 2 and adjusted in light amount by the variable aperture 24. Get light.

The carrier 30 has a line CCD of the image sensor 34 while the film F is positioned at a predetermined reading position.
A transport roller pair (not shown) that transports the film F in a sub-scanning direction orthogonal to the sensor extending direction (main scanning direction) while aligning the reading position in the sub-scanning direction with the film F conveyed; A mask (not shown) having a slit extending in the main scanning direction and located in correspondence with the reading position, for regulating the projection light of the film F into a predetermined slit shape. The reading light is incident on the film F while being transported in the sub-scanning direction by being positioned at the reading position by the carrier 30. As a result, the film F is two-dimensionally slit-scanned by the slit extending in the main scanning direction, and the image of each frame captured on the film F is read.

As described above, the reading light is transmitted through the film F held by the carrier 30 to become projection light for carrying an image, and this projection light is formed on the light receiving surface of the image sensor 34 by the imaging lens unit 32. Imaged. The image sensor 34 includes a line CCD sensor 34R for reading an R image, a line CCD sensor 34G for reading a G image, and a line CCD sensor 34B for reading a B image.
In the sensor, 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 34 and read photoelectrically. Image sensor 34
Is amplified by the amplifier 36, and the A / D converter 3
The digital signal is sent to the image processing device 14 at step 8.

The scanner 12 reads an image photographed on the film F by two image readings: a pre-scan for reading at a low resolution and a main scan for obtaining image data of an output image. The pre-scan is performed under pre-scan reading conditions set in advance so that the image of all the films targeted by the scanner 12 can be read without saturation of the image sensor 34. On the other hand, the main scan is performed under the main scan reading conditions set for each frame from the pre-scan data so that the image sensor 34 saturates at a density slightly lower than the minimum density of the image (frame). The output signals of the pre-scan and the main scan are basically the same data except that the resolution and the output level are different.

In the digital photo printer using the image processing method and the image processing apparatus according to the present invention, the scanner 12 is not limited to the one using the slit scanning reading, and the entire surface of one frame of image is irradiated with the reading light once. The surface reading may be used. In this case, for example, using an area CCD sensor, providing means for inserting R, G, and B color filters between the light source and the film F, inserting a color filter, and reading an image with the area CCD sensor. Is sequentially performed by each of R, G, and B color filters, and the image photographed on the film is separated into three primary colors, and sequentially performed. As described above, the digital signal output from the scanner 12 is output to the image processing device 14 (hereinafter, referred to as the processing device 14). The object of the image processing performed in the present embodiment is a digital signal obtained by reading the film F by the scanner 12 and A / D converting the digital signal. It may be an image digital signal obtained by the above.

FIG. 2 shows a block diagram of the processing device 14. The processing device 14 includes a data processing unit 40, a Log converter 42, a prescan (frame) memory 44, a main scan (frame) memory 46, a prescan processing unit 48,
It has a main scan processing section 50 and a condition setting section 60. FIG. 2 mainly shows parts related to the image processing.
C that controls and manages the entire photo printer 10 including the printer 4
A PU, a memory for storing information necessary for the operation of the photo printer 10, and the like are arranged, and the operation system 18 and the display 20 are connected to each part via the CPU or the like (CPU bus).

The R, G, and B digital signals output from the scanner 12 are subjected to predetermined data processing such as darkness correction, defective pixel correction, and shading correction in a data processing unit 40, and then are Log-converted. Is converted into digital image data (density data) by the
The pre-scan data is stored (stored) in the pre-scan memory 44, and the main scan data is stored (stored) in the main scan memory 46. The pre-scan data stored in the pre-scan memory 44 is sent to a pre-scan processing unit 48 having an image data processing unit 52 and an image data conversion unit 54,
On the other hand, the main scan data stored in the main scan memory 46 is transmitted to an image data processing unit 56 and an image data conversion unit 58.
Are read and processed by the main scan processing unit 50 having

The image data processing section 52 of the pre-scan processing section 48 and the image data processing section 5 of the main scan processing section 50
Reference numeral 6 denotes a portion for performing predetermined image processing on an image (image data) read by the scanner 12 in accordance with processing conditions set by a condition setting section 60 described later. The same process is performed.

In the image processing by both processing units, the roughness (granularity) caused by the photosensitive material which is conspicuous in a region where the image density is low.
At least, a graininess suppression process for suppressing and removing the like and a sharpness enhancement process for sharpening an original image are included. Other processes are not particularly limited, and various known image processes are exemplified. For example, gray balance adjustment, gradation correction, and density (brightness) adjustment using an LUT (look-up table) are exemplified. , Matrix (MTX)
In addition, electronic scaling processing, dodging processing (compression / expansion of density dynamic range), and the like using interpolation calculation and the like, and the like, are exemplified. Note that the graininess suppression processing can also suppress noise such as shot noise included in an original image captured by a digital still camera or the like, noise included in obtaining an original image via a network, and the like. The graininess suppression processing and the sharpness enhancement processing are performed based on a certain processing intensity. The processing intensity is determined by the condition setting unit 60 that sets processing conditions using prescan data.

Here, the image data processing units 52 and 56
FIG. 3 shows an example of the processing of the main scan data in the graininess suppression processing and the sharpness emphasis processing performed in (1). However, the graininess suppression / sharpness forming a part of the image data processing unit 56 shown in the lower part of the figure is shown. As shown in the emphasis processing unit 56A, image processing is performed on image data R, G, and B, which are main scan data, to obtain processed image data R ', G', and B '. Of course,
Similarly to the main scan data, the image data processing unit 52 performs the same processing as the granularity suppression / sharpness enhancement processing unit 56A on the pre-scan data. here,
The processing content of the graininess suppression / sharpness enhancement processing section 56A will be described. First, the following 5 × 5 low-pass filters are cascaded in two stages to image data R, G, and B, which are main scan data. Filtering is performed by a × 9 low-pass filter 56B to obtain low-frequency components R _L , G _L , and B _L of the main scan image data.

(Equation 1)

Next, the low frequency components R _L , G _L , and B _L are subtracted from the image data R, G, and B by an adder / subtractor 56C, and the intermediate / high frequency components R _MH , G _MH, and B _MH are obtained. obtain. Here, the low frequency components R _L , G _L and B _L do not include the edges or texture of the subject in the original image or the roughness due to the graininess of the film F, and the intermediate frequency components R _M , G _M
And B _M include the roughness due to the graininess of the film F, and the high frequency components R _H , G _H and B _H include the edges and texture of the subject in the original image.

Low frequency component R_L, G_L, B_LFigure 4
A distribution H having a peak at a spatial frequency 0 as shown in FIG.
_LA filter processed by a filter having the filter characteristics of
A wave number component and an intermediate frequency component R_M, G_MAnd B_M
Is the Nyquist sky determined by the pixel interval of the playback image data
Inter-frequency f_SPeak near the spatial frequency of 1/3 of / 2
Distribution H with_MFilter with filter characteristics of
The processed frequency component, the high frequency component R_H, G_H
And B_HIs the Nyquist spatial frequency f_SPeak at / 2
Distribution H with_MFilter with filter characteristics of
This is the processed frequency component. Here, FIG.
Number component R_H, G_HAnd B_HAnd the intermediate frequency component R_M, G
_MAnd B_MSets the gain coefficients M and H described later to 1.
This shows the filter characteristics when the value is set to 0. Where gay
The coefficients H and M are coefficients greater than or equal to 0,
Indicates a non-processed state in which no processing is performed. Gain factor
As H becomes larger than 1.0, the sharpness enhancement process
When the gain coefficient M becomes smaller than 1.0,
Suppression processing becomes stronger, and granular suppression and sharpness described later
It is determined automatically by the emphasis processing control means 62A.
The distribution H in FIG. _L, H_MAnd H_HOf the frequency component of
The sum is 1.0.

Next, a luminance component is calculated from the decomposed intermediate / high frequency components R _MH , G _MH and B _MH . This luminance component is calculated by converting the intermediate / high frequency components R _MH , G _MH, and B _MH of the main scan image data into the MTX converter 56.
In D, the component Y is converted to a YIQ basis.
_MH is calculated. Here, conversion to the YIQ basis is performed by the following equation.

(Equation 2)

The component I, which is a color component converted to YIQ conversion
_MHAnd component Q_MHIs grainy color due to film graininess
Image, and generally contains images
Empirically knows that it has almost no components
Therefore, component I_MHAnd component Q _MHCan be 0,
This suppresses color roughness caused by film graininess
can do.

[0031] the component Y _MH obtained by MTX conversion section 56D, a low-pass filter 56E with a low-pass filter of 5 × 5 described above, to give the intermediate frequency components Y _M of the components Y _MH from component Y _MH, which by subtracting from the component Y _MH in adder-subtractor 56F, and high frequency components Y _H of the components Y _MH
Get.

Next, the granularity suppression and sharpness strength described later will be described.
Gay automatically determined by the tone control means 62A.
Using the calculation coefficients M and H, as shown in the following equation,
In multipliers 56G and 56I, respectively, the component Y_M
And Y_HAnd the processed component Y_M’, Y_H’
And processed component Y_M’, Y_H’Are synthesized into components
Y _MH'. Y_MH’= M × Y_M + H × Y_H

Thereafter, the component Y _MH ′ is added to the low frequency components R _L , G _L, and B _L obtained by the low-pass filter 56B in the adder 56K to obtain processed image data R ′, G ′, and B ′. . The component Y _MH ′ is added to the low frequency components R _L , G _L, and B _{L because the} components I _MH and Q _MH are set to 0 by the MTX operation unit 56D, and the processed component Y _MH ′ is inversely transformed to R , G and B, all have the same value as the processed component Y _MH ′, so that the value of the direct component Y _MH ′ can be directly added to the low frequency components _RL , _GL and _BL. Because. As described above, since the gain coefficient M is a coefficient for controlling an intermediate frequency component including color roughness caused by film graininess, the gain coefficient M is a coefficient that determines the processing strength of the graininess suppression processing. Further, since the gain coefficient H is a coefficient for controlling a high frequency component including image information such as an edge and a texture of a subject in the original image, the gain coefficient H determines the processing strength of the sharpness enhancement processing of the original image. It is a coefficient to be determined.
Therefore, in the processing described above, the graininess suppression processing and the sharpness enhancement processing are performed simultaneously by determining the gain coefficients M and H. Hereinafter, this processing is referred to as graininess suppression / sharpness enhancement processing.

The image data converter 58 converts the image data processed by the image data processor 56 into, for example, a 3D image data.
(3D)-converted using a LUT or the like, and
Printer 1 as image data corresponding to image recording by
6 The image data conversion unit 54 thins out the image data processed by the image data processing unit 52 as necessary, similarly converts the image data using a 3D-LUT or the like, and converts the image data corresponding to the display on the display 20. Is supplied to the display 20.

The condition setting section 60 includes a pre-scan processing section 4
8 and a section for setting various processing conditions in the main scan processing section 50 and reading conditions for the main scan, and includes a setup section 62, a key correction section 64, and a parameter integration section 66.

The setup section 62 includes a grain suppression / sharpness enhancement control means 62A for automatically determining the gain coefficients M and H for determining the processing strength of the graininess suppression / sharpness enhancement processing, and an image other than the graininess suppression / sharpness enhancement processing. It includes a parameter setting unit 62B that automatically sets processing condition parameters for image processing performed by the pre-scan processing unit 48 for processing, for example, the above-described gray balance adjustment and gradation correction, and the main scan processing unit 50. The graininess suppression / sharpness enhancement processing control means 62A is a part that automatically determines the gain coefficients M and H used in the above-described graininess suppression / sharpness enhancement processing unit 56A in accordance with the determination result of the shooting scene. 62C, a scene determination unit 62D and a gain coefficient determination unit 62E.

The face extracting section 62C is a part for extracting the face of the photographed person from the original image. Further, the face extraction method executed in the present invention is not particularly limited.
Face extraction by circular shape extraction, face extraction by face contour / circle shape extraction, face extraction by torso / circle shape extraction, face extraction by eye (face internal structure) / circle shape extraction, face extraction by hair part extraction / circle shape extraction Extraction and the like. These extraction methods are described in detail in Japanese Patent Application Laid-Open No. 8-184925 and the like.

For example, in the skin color / circular shape extraction, a face region is extracted by performing skin color extraction and circular shape extraction.
That is, the hue and saturation of each pixel are found from pre-scan data (thinning can be performed if necessary), and a pixel area (skin color area) that can be estimated as a skin color of human skin is extracted. Is generally an elliptical shape, an (elliptical) circular shape presumed to be a human face is extracted from the extracted skin color region, and this is used as a face region candidate.

In the face contour / circle shape extraction, a face region is extracted by performing face contour extraction and circular shape extraction by edge extraction. Similarly, torso / circular shape extraction is torso contour extraction and circular shape extraction by edge extraction, eye / circle shape extraction is human eye extraction and circular shape extraction, and hair / circle shape extraction is edge extraction The extraction of the human hair and the extraction of the circular shape are performed to extract the face region.

Further, in the present invention, for example,
-346332, 4-346333, 4-34
No. 6334, No. 5-100328, No. 5-15816
No. 4, 5-165119, 5-165120,
Nos. 6-67320, 6-160992, 6-1
No. 60993, No. 6-160994, No. 6-1609
No. 95, No. 8-122944, No. 9-80652,
9-101579, 9-138470, 9-
Various known main part extraction methods disclosed in respective publications such as 138471 can also be used.

The information on the face area thus extracted is sent to the scene discriminating section 62D. Scene determination unit 6
2D determines whether the ratio of the face portion area to the original image is equal to or greater than a certain threshold from the obtained face area information, and if the ratio is equal to or greater than the certain threshold, the original image is determined to be a portrait scene. I do. If the value is equal to or smaller than a certain threshold, the original image is determined to be a scene other than the portrait scene. Thereafter, the determination result is sent to the gain coefficient determination unit 62E. At the same time, an image feature amount or the like when performing density correction or the like in the parameter setting unit 62B is sent to the gain coefficient determination unit 62E, and the gain coefficients M and H are automatically and uniquely determined together with the determination result of the scene determination. .

The gain coefficient determining section 62E is a section that determines gain coefficients M and H that determine the processing strength of the graininess suppression / sharpness enhancement processing in accordance with the result of the determination made by the scene determining section 62D. The gain coefficients M and H are automatically adjusted based on the determination result of a portrait scene or other scene, and an image density histogram and an image feature amount automatically calculated from pre-scan image data in a parameter setting unit 62B described later. However, when the scene is determined to be a portrait scene, the gain coefficients M and H are smaller than when the scene is determined to be a scene other than a portrait scene. In this way, when the scene is determined to be a portrait scene, the processing strength of the graininess suppression processing is increased and the processing strength of the sharpness enhancement processing is reduced as compared with the case where the scene is determined to be a scene other than the portrait scene. When the portrait scene is determined, the processing strength of the graininess suppression process is increased because the intermediate frequency component has color roughness due to film graininess, and the face portion of a person who is a photographing subject in the portrait scene This is for suppressing the roughness of the skin. Also, the reason why the processing strength of the sharpness enhancement processing is reduced is to prevent the facial expression of a person image, which is a photographic subject in a portrait scene, from becoming sharp due to sharpening of the edge region.

The gain coefficients M and H obtained are sent to the parameter integrating section 66. The granularity suppression / sharpness enhancement processing control means 62A can configure all of the components by software, can configure all of the components by hardware, and can configure a part of the components by software. Or by hardware.

Parameter setting section 6 of setup section 62
2B reads out pre-scan data from the pre-scan memory 52, creates a density histogram from the pre-scan data, and calculates image feature amounts such as average density, highlight (lowest density), and shadow (highest density). Determine the reading conditions for the main scan, create an LUT that performs gray balance adjustment, tone correction, and density adjustment in accordance with instructions from the operator as needed, in addition to density histograms and image feature values, Prescan processing unit 48 and main scan processing unit 5 such as creation of MTX operation formula
Various image processing conditions at 0 are set.

The key correction unit 58 controls the density (brightness), color,
The amount of adjustment of image processing conditions is calculated in accordance with keys for adjusting contrast, sharpness, saturation, etc., and various instructions input with the mouse 18b, and supplied to the parameter integration unit 66. The parameter integration unit 66 receives the image processing conditions set by the parameter setting unit 62B and the gain coefficients M and H determined by the gain coefficient determination unit 62E, and sets them in the pre-scan processing unit 48 and the main scan processing unit 50. In accordance with the adjustment amount calculated by the key correction unit 64, the image processing condition set for each part is corrected (adjusted) or the image processing condition is reset.

The operation of the scanner 12 and the processing device 14 will be described below. The operator who is requested to make a print of the film F operates on the carrier 3 corresponding to the film F.
0 is loaded into the scanner 12, the film F (cartridge) is set at a predetermined position of the carrier 30, and necessary instructions such as a print size to be created are input, and then a print creation start is instructed. Thereby, the aperture value of the variable aperture 24 of the scanner 12 and the accumulation time of the image sensor (line CCD sensor) 34 are set according to the pre-scanning reading conditions. Thereafter, the carrier 30 pulls out the film F from the cartridge and presses the film F. The film F is conveyed in the sub-scanning direction at a speed corresponding to the can, and the pre-scan is started. At a predetermined reading position, the film F is slit-scanned, and the projection light is focused on the image sensor 34 as described above. An image captured at F is separated into R, G, and B and photoelectrically read.

The pre-scan and the main scan are
The prescan and the main scan may be performed one frame at a time, or continuously for all frames or for a predetermined plurality of frames. In the following example, for simplicity, 1
The description will be given by taking the image reading of a frame as an example.

The output signal of the image sensor 34 by the pre-scan is amplified by the amplifier 36 and
8 and converted into a digital signal. The digital signal is
The data is sent to the processing device 14, subjected to predetermined data processing by the data processing unit 40, converted into digital image data by the Log converter 42, and stored in the prescan memory 44.

When the prescan data is stored in the prescan memory 44, the setup section 62 of the condition setting section 60 reads it out and supplies it to the granularity suppression / sharpness enhancement processing control means 62A and the parameter setting section 62B. The parameter setting unit 62B creates a density histogram of the image from the pre-scan data, calculates an image feature amount such as highlight or shadow, sets reading conditions for the main scan, and supplies the main scanning conditions to the scanner 12. The density histogram, the calculated image feature amount, and the like are supplied to the gain coefficient determination unit 62E and the parameter integration unit 66.

In the graininess suppression / sharpness enhancement processing control means 62A, as described above, a face portion of a person in the original image is extracted by the face extracting section 62C, and the entire original image of the extracted face portion region is extracted. If the ratio to the area is equal to or greater than a predetermined threshold, the scene discriminating unit 62D discriminates the original image as a portrait scene, and the discrimination result is sent to the gain coefficient determining unit 62E. In the gain coefficient determination unit 62E, the gain coefficients M and H are uniquely and automatically determined based on the determination result sent from the scene determination unit 62D, the density histogram sent from the parameter setting unit 62B, the calculated image feature amount, and the like. Is determined. The determined gain coefficients M and H are sent to the parameter integrating unit 66.

The parameter integration section 66 corrects and adjusts the received gain coefficients M and H and the image processing conditions by the key correction section 58 as necessary, and sets predetermined parameters (hardware) of the prescan processing section 56 and the main scan processing section 58. Ware).

When performing the test, the pre-scan data is stored in the pre-scan memory 4 by the image data processing unit 52.
4 and processed by the image data processing unit 52,
The image data is converted by the image data conversion unit 54 and displayed on the display 20 as a simulation image. The operator looks at the display 20 to check (verify) the image, that is, the processing result, and adjusts the color, density, gradation, and the like using the adjustment keys and the like set on the keyboard 18a as necessary. . The input of this adjustment is sent to the key correction unit 64, which calculates the correction amount of the image processing condition according to the adjustment input, and sends it to the parameter integration unit 66. The parameter integration unit 66 corrects the LUT, MTX, and the like of the image data processing units 52 and 56 according to the correction amount sent as described above. Therefore, according to this correction, that is, the adjustment input by the operator, the display 2
The image displayed at 0 also changes.

When the operator determines that the image of this frame is proper (test OK), the operator instructs the start of printing using the keyboard 18a or the like. As a result, the image processing conditions are fixed, the aperture value of the variable aperture 24 is set in the scanner 12 in accordance with the reading conditions of the main scan, and the carrier 30 moves the film F at a speed corresponding to the main scan. Then, the main scan is started. When the verification is not performed, the image processing conditions are determined at the time when the setting of the image processing conditions in the main scan processing unit 50 by the parameter integration unit 66 is completed, and the main scan is started.

The main scan is performed in the same manner as the pre-scan except that the read conditions such as the aperture value of the variable aperture 24 are set, and the output signal from the image sensor 34 is amplified by the amplifier 36. The digital signal is converted into a digital signal by the A / D converter 38, processed by the data processing unit 40 of the processing device 14, converted into the main scan data by the Log converter 42, and sent to the main scan memory 46. When the main scan data is sent to the main scan memory 46, the main scan data is read out by the main scan processing unit 50, and image processing is performed under the image processing conditions determined by the image data processing unit 56.
Next, the image data is converted by the image data conversion unit 58 to output image data, and output to the printer 16.

The printer 16 exposes a photosensitive material (printing paper) in accordance with the supplied image data to record a latent image, and prints the exposed photosensitive material by performing predetermined processing. Processor (developing device) that outputs as
And In a printer, for example, after cutting a photosensitive material into a predetermined length corresponding to a print, a back print is recorded, and then three types of light beams of R exposure, G exposure, and B exposure according to the spectral sensitivity characteristics of the photosensitive material. Processing unit 1
The light beam is conveyed in the sub-scanning direction orthogonal to the main scanning direction by modulating the light-sensitive material in the main scanning direction and modulated in accordance with the image data output from the photodetector 4, thereby two-dimensionally transforming the photosensitive material by the light beam. The latent image is recorded by scanning exposure and supplied to the processor. The processor that has received the photosensitive material performs a predetermined wet development process such as color development, bleach-fixing, and washing with water, and forms a print by drying, and sorts and accumulates it into a predetermined unit such as one film.

In the embodiment based on FIG. 2 and FIG. 3, the gain coefficients M and H of the graininess suppression / sharpness enhancement processing to be applied to the entire image data are automatically determined based on the determination result of the determined shooting scene of the entire original image. As shown in FIG. 5, the main part extracting unit 62G, the frequency analyzing unit 62H, and the gain coefficient determining unit 62I are used to control the granularity suppression / sharpness enhancement processing control unit 62A of the set-up unit 62 shown in FIG. The granularity suppression / sharpness enhancement processing control means 62F may be replaced with the frequency analysis and configured to perform the graininess suppression / sharpness enhancement processing.

Here, the main part extracting section 62G uses the various methods described in the above-described face extracting section 62C for, for example, pets, animals such as horses, automobiles, mountains, lakes, and the like in addition to the face of the person as the main part. May be used for extraction. In this case, an extraction algorithm using colors and shapes suitable for the selected main part may be selected.

The frequency analysis section 62 determines the main region in the extracted photographic scene, that is, the local region in the original image.
Perform frequency analysis with H. That is, the frequency analysis is performed on the extracted image data of the local region of the main part with the Nyquist spatial frequency f _S / 2 determined from the pixel interval of the reproduced image data as the maximum frequency. For example, FFT (Fast F
Ourier Transformation) and discrete Fourier transform are used to perform frequency analysis to obtain a spectral distribution, and multiply by a filter characteristic as shown in FIG. 4 to obtain an overall spectrum value of the intermediate frequency component frequency band.
Obtain the spectral value of the intermediate frequency component. Alternatively, the intermediate frequency component may be extracted by performing filter processing used in the above-described low-pass filters 56B and 56E, and the spectral value of the intermediate frequency component may be obtained by FFT or discrete Fourier transform. The spectrum value of the obtained intermediate frequency component is used as a spatial frequency characteristic, and the spectrum value is used as a predetermined value, for example, an image feature quantity representing a filming condition such as the film sensitivity of the film F or an underexposure calculated by the parameter setting unit 62B. If it exceeds a threshold value determined accordingly, it is determined to be a sharpness priority area. If the spectrum value is other than that, that is, equal to or less than the predetermined value, it is determined to be a granular priority area.

Here, the spectral values used for discrimination are obtained by integrating the spectral values separately obtained for each of the R, G and B image data, and are used as discrimination as spatial frequency characteristics. Alternatively, the R, G, and B image data may be combined into one spectrum value by a predetermined method such as an average value or a total value, and the determination may be performed. Also, a predetermined value is determined for each of the spectral values of the R, G, and B image data, and when at least one of the three spectral values or all three spectral values exceed the predetermined value, the sharpness It may be determined as a priority area. Further, instead of the spectrum value of the intermediate frequency component, the spectrum value of the intermediate / high frequency component including the intermediate frequency component and the high frequency component may be used as the spatial frequency characteristic.

The reason why the sharpness priority area or the granular priority area can be determined based on the magnitude of the spectrum value of the intermediate frequency component or the intermediate / high frequency component is as follows. That is, in addition to the granular component caused by the film, the intermediate frequency component is a component of the edge region of the photographing subject, which is included in the high frequency component and desirably subjected to the sharpness processing, that is, the texture of the edge component, a fine pattern, or the like. The edge component and the texture component have a larger amplitude than the granular component caused by the film, and have a great influence on the spectrum value. In a so-called flat region where the spatial fluctuation is small, the spectrum value of the intermediate frequency component or the intermediate / high frequency component is small, and conversely, a region including an edge component or a texture component for which it is desirable to perform sharpness processing is the intermediate frequency component or This is because the spectrum value of the intermediate / high frequency component increases. For example, since the landscape area contains many edge components and texture components of the photographing subject, the spectrum value of the intermediate frequency component or the intermediate / high frequency component exceeds the above-mentioned predetermined value, and is determined as the sharpness priority area.

The obtained discrimination result is obtained by the gain coefficient determination unit 6
Sent to 2I. The gain coefficient determination unit 62I determines the gain coefficients M and H according to the obtained determination result. That is, the gain coefficients M and H are automatically adjusted based on the determination result of the sharpness priority area or the granularity priority area and the density histogram and image feature amount automatically calculated from the prescan image data in the parameter setting unit 62B. Although uniquely determined, the gain coefficient H when determined as the sharpness priority area is a value larger than the gain coefficient H when determined as the granular priority area, and the gain coefficient M when determined as the granularity priority area is: The value becomes smaller than the gain coefficient M when the sharpness priority area is determined. The grain priority region suppresses the roughness due to the film, so that the grain suppression is enhanced and the color roughness can be suppressed. On the other hand, the sharpness priority area is determined to have a large spatial variation in image density, many high frequency components, and many subject edge components and texture components. Therefore, sharpness enhancement processing is strongly performed to obtain a sharp image.

The determined gain coefficients M and H are sent to the parameter integrating section 66 together with the position information of the local area of the main part extracted by the main part extracting section 62G. After the obtained gain coefficients M and H and the position information of the local area where the graininess suppression / sharpness enhancement processing is performed using the coefficients are sent to the image data processing units 52 and 56 via the parameter integration unit 66. The graininess suppression / sharpness enhancement processing is performed on the local region based on the gain coefficients M and H described above. Such a local region is not limited to one region in the original image, and a plurality of local regions may be extracted. For the plurality of local regions, based on gain coefficients M and H determined for each local region. A graininess suppression / sharpness enhancement process may be performed. Further, for regions other than the local region, the gain coefficients M and H according to the region may be determined. Furthermore, the local area according to the present embodiment is the main part extracted by the main part extracting unit 62G, but is not limited to the main part extracted as a main part, and may be a predetermined area in a predetermined original image, for example, an original area. It may be a local area obtained by dividing an image into rectangles or the like.

The granularity suppression / sharpness enhancement processing control means 62F based on frequency analysis includes a main extraction section 62G.
Is to set the conditions for performing grain suppression and sharpness enhancement processing on the image data of the local area in which the main part is extracted from the original image. However, the frequency analysis of the local area is not necessarily performed, and the The image data is not limited to one that performs grain suppression and sharpness enhancement processing.
When the entire original image is subjected to frequency analysis by the frequency analysis unit 62H, and the spectral value of the intermediate frequency component or the intermediate / high frequency component is larger than a predetermined value, for example, a threshold value determined according to an image feature amount representing film sensitivity or underexposure or the like. ,
When the intermediate frequency component or the intermediate / high frequency component is equal to or less than the predetermined value, the scene is determined to be a sharpness priority scene to which sharpness enhancement processing is strongly applied, and is determined to be a granular priority scene to which strong grain suppression processing is strongly applied. The graininess suppression / sharpness enhancement processing may be performed using the two gain coefficients M and H. For example, in the case of a landscape scene, since a large number of edge components and texture components of the photographing subject are included, the spectrum value of the intermediate frequency component or the intermediate and high frequency components exceeds the above-described predetermined value, and is determined to be a sharpness priority scene.

Further, the gain coefficient determination units 62E and 62I in the graininess suppression / sharpness enhancement processing control means 62A and 62F determine the contrast between the edge area of the extracted human face and the edge area of the extracted main part. However, for example, when the contrast of the edge area is strong and the image data changes rapidly, the gain coefficient H may be finely adjusted according to the degree of the change to weaken the processing strength of the sharpness enhancement processing. This is because, when the sharpness enhancement processing is performed when the contrast of the edge region is high, an edge is formed on the extracted face or the outline of the main part, resulting in an unnatural processed image. The present invention is not limited to the case where the sharpness enhancement is weakened by finely adjusting the gain coefficient H, and the sharpness enhancement may be weakened by a separate sharpness enhancement process.

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

[0066]

As described above in detail, according to the present invention, in a photo printer such as a digital photo printer or the like, image data is determined based on the determination result of the entire original image or a local scene of the original image. Granulation control applied to
Since the processing intensity of the sharpness enhancement processing is determined, the granularity suppression and sharpness enhancement processing can be optimally performed according to the shooting scene of the entire original image or the local region, and a high-quality reproduced image can be obtained.

[Brief description of the drawings]

FIG. 1 is a block diagram of a digital photo printer that uses an example of an image processing method and an image processing apparatus according to the present invention.

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

FIG. 3 is a block diagram illustrating a main part of the image processing apparatus illustrated in FIG. 2;

FIG. 4 is a characteristic diagram showing low frequency components, intermediate frequency components, and high frequency components used in the image processing method of the present invention.

FIG. 5 is a block diagram showing a main part of another example of the image processing apparatus of the present invention.

[Explanation of symbols]

 10 (Digital) Photo Printer 12 Scanner 14 (Image) Processing Device 16 Printer 18 Operation System 20 Display 22 Light Source 24 Variable Aperture 28 Diffusion Box 30 Carrier 32 Imaging Lens Unit 34 Image Sensor 34R, 34G, 34B Line CCD Sensor 36 Amplifier 38 A / D converter 40 Data processing unit 42 Log converter 44 Prescan (frame) memory 46 Main scan (frame) memory 48 Prescan processing unit 50 Main scan processing unit 52, 56 Image data processing unit 54, 58 Image data conversion Section 60 condition setting section 62 setup section 64 key correction section 66 parameter integration section

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Claims (7)

[Claims] 1. An image processing method for performing image processing on image data of an original image to obtain output image data, comprising: determining a shooting scene of the entire original image or a local region of the original image; Determining the processing strength of the graininess suppression / sharpness enhancement processing to be performed on the image data based on the image data, and performing the graininess suppression / sharpness enhancement processing on the entire original image or the image data of the local region using the processing strength. Characteristic image processing method. 2. A photographing scene of an original image is determined to be a portrait scene or another scene according to a ratio of a face area of a person in the original image to an original image, and the original image is defined as a portrait scene. The image processing method according to claim 1, wherein when the determination is made, the graininess suppression processing is performed more strongly and the sharpness enhancement processing is performed weaker than when the scene is determined to be a scene other than a portrait scene. 3. A scene in which a photographing scene of the entire original image is a grain priority scene or a sharpness priority scene in which sharpness suppression processing or strong sharpness enhancement processing is performed by analyzing spatial frequency characteristics of image data of the entire original image. The image processing method according to claim 1, wherein: 4. A spatial frequency characteristic of the image data of the local area is analyzed, and a photographed scene of the local area of the original image is converted into a grain priority area where grain suppression processing is strongly applied or a sharpness priority area where sharpness enhancement processing is strongly applied. The image processing method according to claim 1, wherein the image processing method determines that there is an image. 5. The image processing apparatus according to claim 1, wherein said spatial frequency characteristic is analyzed, and when a spectrum value of an intermediate frequency component or an intermediate / high frequency component of the image data of said original image is larger than a predetermined value, a sharpness priority scene to which sharpness enhancement processing is strongly applied; 5. The image processing method according to claim 3, wherein the image is determined to be a sharpness priority area, and when the spectrum value is equal to or less than the predetermined value, the area is determined to be a granular priority scene or a granular priority area to which granular suppression processing is strongly applied. 6. The image processing method according to claim 1, wherein the contrast of the edge area of the subject in the original image is determined, and the sharpness enhancement processing is reduced according to the contrast. 7. An image processing apparatus for performing image processing on image data of an original image to obtain output image data, comprising: determining a shooting scene of the entire original image or a local region of the original image; Control means for controlling the graininess suppression / sharpness enhancement processing to be applied to the image data to control the graininess suppression / sharpness enhancement processing; and using the processing strength determined by the control means, An image processing apparatus, comprising: image processing means for performing graininess suppression / sharpness enhancement processing on the entire image or image data of the local region.