JP2006024097A - Apparatus and method for measuring sharpness, apparatus and method for processing image, sharpness measuring program, image processing program, and storage medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an apparatus and method for processing an image that provides a digital image having preferable sharpness, and an apparatus and method for measuring sharpness that can obtain the optimum measurement value as sharpness strength used for the processing. <P>SOLUTION: A lightness luminance signal converting section 11 converts an inputted image signal into a lightness luminance signal indicating perceptually equivalent lightness or luminance, then a band processing section 12 applies differentiation processing to the lightness luminance signal to provide a differential image signal. A sharpness strength measuring section 14 calculates a histogram indicating a correspondence relation between a value of the differential image signal and the number of pixels, calculates a frequency value taking some percentage between the maximum in the histogram and 3-10 % of all number of pixels, and sets the value of the differential image signal corresponding to the frequency value as the sharpness strength. At this time, the sharpness strength may be corrected according to the attribute information acquired by an attribute information acquisition section 13. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to an image processing technique that can realize an optimum degree of sharpness for a digital image, and a technique for measuring the sharpness intensity of a digital image when such an optimum degree of sharpness is realized.

  The quality of the final printed matter is determined by the characteristics of the digital image signal and the characteristics of the color image recording apparatus and the image recording material. Similarly, a color image processing apparatus includes a processing apparatus for correcting or optimizing an input digital image signal (input image signal) according to the characteristics of the color image recording apparatus or image recording material, and photographing. It can be classified into processing devices intended for adjustment of input image signals whose conditions and color space are unknown.

In either image processing apparatus, input image signals to the image processing apparatus are red (R) green (G) blue (B) color signals, CIEL ^* a ^* b ^* (CIELAB) color signals, and cyan (C). Magenta (M) yellow (Y) black (K) color signals are used, and the intensity of the input image signal is multi-valued, such as 8 bits or 12 bits for a single color. The image processing apparatus includes a color correction processing unit, a sharpness (including spatial correction) processing unit, and the like, which are common by performing a series of image signal processing.

  The color processing in the above-described image processing apparatus for the purpose of adjusting the input image signal includes techniques such as contrast adjustment, color balance adjustment, white balance adjustment, fog correction, and sharpness processing includes sharpness enhancement including edge enhancement. , Resolution conversion, noise removal, etc.

  In addition, spatial correction processing for the purpose of correcting devices such as input devices and output devices including display devices is an unnecessary periodicity and image noise characteristics of image signals, and degradation of spatial frequency characteristics caused by image recording devices. Suppression processing and further enhancement processing such as a specific spatial frequency band are provided.

  The spatial correction processing described above has a mechanism for performing image processing using a sharpness correction filter described with limited information that can be obtained in advance on the characteristics of the device. However, since the device correction information is information independent of the information of the digital image itself, an optimal output condition for the digital image is not taken into consideration, and an unbalanced digital image may be output. In order to solve this, a processing device for adjusting the digital image signal is required.

  The best measure for adjusting the digital image signal is a method of performing processing according to preference while checking the degree of the output image on the output device used by the user. However, this method has a problem that the user is required to have experience in image processing and working time. For this reason, the image processing apparatus is expected to include a method (automatic image quality adjustment technique) for performing image measurement and image quality adjustment that automatically obtains information from the image itself with minimum effort.

  The sharpness processing in the above-described automatic image quality adjustment technique requires a function of measuring the degree of sharpness (representing the degree of combination of edge degree and image noise) from a digital image and performing the sharpness processing according to the measurement result.

  One problem with sharpness processing is the degree to which it can be processed. If blurring is simply applied, high-definition reproduction (texture) is lost and the sharpness level is reduced. Also, if the sharpness is too strong in the sharpness enhancement processing, the skin becomes rough (skin rough), the noise in the achromatic color part, and the failure of the boundary of the edge part (ringing) is noticeable and uncomfortable. With normal sharpness processing technology, as sharpness (sharpness degree) increases, defects due to sharpness processing become significant, and each cannot be controlled independently. Therefore, the fundamental solution is difficult only with the information of the digital image signal.

  To deal with this problem, the degree of sharpness and the degree of preference for sharpness (sharpness preference) that reflects the amount of deterioration (sharpness inhibition amount) that inhibits the goodness of sharpness are required as the measurement amount. It is.

  Several techniques have been proposed for measuring the characteristics of an image from the image signal itself, in particular, for sharpness measurement. For example, as a sharpness evaluation method, a sharpness evaluation method (for example, refer to Non-Patent Document 1 or the like) has been proposed in which the sum of signal intensities of differential images (edge images) is used as an evaluation value of sharpness. Further, for example, Patent Literature 1, Patent Literature 2, Patent Literature 3 and the like describe a digital image sharpness evaluation device or an image processing device that converts sharpness using the same principle as the above-described method. Among these, Patent Document 1 and Patent Document 2 describe a method of normalizing by the number of edge pixels (pixels whose edge intensity is not 0) as an amount corresponding to the sum. Further, Patent Document 3 describes an image processing method including a step of obtaining a pixel having edge strength equal to or higher than a threshold in a pixel number calculation step of normalizing the sum.

  In the sharpness measuring apparatus described in Patent Document 2, after obtaining the sum of the signal strengths of the edge image and normalizing in the edge region as in the above-described sharpness evaluation method, The average strength or the average strength of the square value of the edge strength is obtained, and the strength value (degree of strength) of the edge degree is defined as sharpness. In this patent document 2, the processing process is simplified by using luminance information instead of color image information. It is known that the information used for sharpening and the measurement of sharpness can be expected to improve accuracy according to processing costs by using color information rather than brightness information. Usually, if accuracy is required, processing cost is applied. When moderate accuracy is desired, luminance or brightness information may be used.

  On the other hand, the sharpening device described in Patent Document 1 is a sharpening device using the above-described sharpness evaluation method and the principle of the sharpness evaluation device. Further, the image processing apparatus described in Patent Document 3 includes a sharpness determination means characterized by a threshold processing method in addition to the above-described sharpness evaluation method and the principle of the sharpness evaluation apparatus. These apparatuses are means for digitizing the intensity of sharpness, and use an average value in a frequency distribution.

  Patent Document 4 also describes a technique for calculating a sharpness degree that is subjectively desirable by measuring an amount that inhibits the sharpness intensity together with the sharpness intensity.

  Generally, when measuring sharpness or sharpness intensity, an image to be evaluated is differentiated and the frequency distribution of the differentiated value is evaluated. There is a maximum value in the frequency distribution (statistic) of the differential value, and this maximum value is used as an index indicating the sharpness or sharpness intensity. However, when the maximum value is simply used, although a good result may be shown, there is a problem that a stable evaluation cannot be performed for a sudden phenomenon such as an image defect.

Japanese Patent No. 2692531 Japanese Patent No. 2611723 Japanese Patent Laid-Open No. 10-200756 JP 2004-096291 A Yoichi Miyake, “2-3 Hard Copy Image Quality Evaluation”, Television Society Journal, 1989, Vol. 43, no. 11, p. 1212-1217

  The present invention has been made in view of the above-described circumstances. In view of human visual characteristics, the present invention provides an image processing apparatus and an image processing method capable of obtaining a digital image having favorable sharpness, and such an image. An object of the present invention is to provide a sharpness measuring apparatus and a sharpness measuring method capable of obtaining an optimum measurement value as a sharpness intensity used for processing in a processing apparatus and an image processing method. Further, it is an object to provide a sharpness measurement program and an image processing program for executing such a sharpness measurement method and an image processing method by a computer, and a storage medium storing such a sharpness measurement program and an image processing program. To do.

  The present invention relates to a sharpness measuring apparatus and a sharpness measuring method for measuring the sharpness intensity of an input digital image signal, wherein the digital image signal is converted into a brightness luminance signal indicating at least perceptually equivalent lightness or brightness, The brightness luminance signal is differentiated to obtain a differentiated image signal, a histogram indicating the correspondence between the value of the differentiated image signal and the number of pixels is calculated, and 3-10% of the total number of pixels is calculated from the maximum value in the histogram. A frequency value occupying any ratio between them is calculated, and the value of the differential image signal corresponding to the frequency value is set as the sharpness intensity. Further, after calculating the histogram, frequency values occupying a plurality of ratios between 3 to 10% of the total number of pixels are calculated from the maximum value in the histogram, and the differential image corresponding to each of the plurality of frequency values The signal value is weighted to obtain a sharpness intensity.

  It is also possible to select a measurement target area for sharpness intensity, calculate a histogram for the measurement target area, and measure the sharpness intensity. Further, the attribute information such as the number of effective gradations, the number of pixels, the output resolution or the number of printed lines of the measurement target area of the sharpness intensity in the digital image signal is acquired, and the sharpness intensity is corrected in consideration of the attribute information. You may comprise as follows.

  The present invention also provides an image processing apparatus and an image processing method for performing sharpness processing on an input digital image signal, and obtaining sharpness intensity by the sharpness measuring method of the present invention as described above, and sharpness processing is performed from the sharpness intensity. In this case, a coefficient for performing the processing is determined, and a sharpness process is performed on the digital image signal in accordance with the determined coefficient.

  Furthermore, the present invention is characterized in that a sharpness measurement program for measuring the sharpness intensity of an input digital image signal causes a computer to execute the sharpness measurement method of the present invention. An image processing program that performs sharpness processing on an input digital image signal causes a computer to execute the image processing method of the present invention.

  Furthermore, the present invention stores a sharpness measurement program for causing a computer to execute the sharpness measurement method of the present invention in a computer-readable storage medium storing a sharpness measurement program for measuring the sharpness intensity of an input digital image signal. It is characterized by this. A computer-readable storage medium storing an image processing program for performing sharpness processing on an input digital image signal stores the image processing program for causing the computer to execute the image processing method of the present invention. It is what.

  According to the present invention, it is possible to measure the sharpness intensity required to satisfactorily automatically adjust the image quality of a digital image, and by applying a sharpness process to the digital image according to a coefficient obtained from the sharpness intensity, There is an effect that a preferable digital image can be obtained.

  FIG. 1 is a block diagram showing an embodiment of an image processing apparatus and an image processing method according to the present invention. In the figure, 1 is a sharpness measuring unit, 2 is a sharpness processing coefficient determination unit, and 3 is a sharpness processing unit. Any image signal may be input, but in the present invention, a digital image signal including a natural image or the like is particularly preferable. Here, as an example, the input image signal is an RGB color signal. Of course, other color signals may be used.

  The sharpness measuring unit 1 measures the sharpness intensity of the input image signal, and is the sharpness measuring apparatus of the present invention. The sharpness processing coefficient determination unit 2 determines a processing coefficient used when the sharpness processing unit 3 performs sharpness processing from the sharpness intensity obtained by the sharpness measurement unit 1. The sharpness processing unit 3 performs sharpness processing on the input image signal according to the processing coefficient determined by the sharpness processing coefficient determination unit 2.

  FIG. 2 is a block diagram illustrating a first example of the sharpness measuring unit 1. In the figure, 11 is a brightness / luminance signal conversion unit, 12 is a band processing unit, 13 is an attribute information acquisition unit, and 14 is a sharpness intensity measurement unit. The block diagram shown in FIG. 2 shows an embodiment of the sharpness measuring apparatus and sharpness measuring method of the present invention.

The lightness / luminance signal conversion unit 11 converts the image signal into a lightness / luminance signal that indicates at least perceptually equivalent lightness or luminance. Here, when the image signal is an RGB color signal and the brightness luminance signal is a luminance signal Y in the YCrCb color space, the luminance signal Y is Y = 0.30R + 0.59G + 0.11B.
Can be converted. Of course, the brightness luminance signal is not limited to this example. For example, only the tristimulus value CIEXYZ or R, G, or B signals that are components of RGB color signals may be used. If high-precision processing is desired, L ^{* of} the CIELAB signal, principal component analysis, , K-L converted signal may be used. In other words, the brightness luminance signal can be appropriately changed as long as it is a signal representing brightness, and can be appropriately selected according to the uniformity of the perceptual amount and the processing speed.

The band processing unit 12 performs a differentiation process on the brightness luminance signal converted by the brightness luminance signal conversion unit 11 to obtain a differential image signal. In this differential processing, first order differentiation is generally used to emphasize processing speed, but diffusion process and visual characteristics, which are one of the basic phenomena of image blurring, are related to second order differential images. Since it is known that it is deep, the secondary differential image is a differential image signal here. The second-order differential image is an absolute value obtained by removing the luminance image signal fb blurred by applying an unsharp mask (USM) filter from the luminance image signal f, and is a signal of only the middle and high frequency band components with little scene information. . That is, if the differential image signal is Fx,
Fx = | f−fb | (1)
Can be obtained at

  FIG. 3 is an explanatory diagram of an example of an unsharp mask filter. FIG. 3 shows a 5 × 5 pixel size filter. The 5 × 5 pixel image signal is multiplied by the numerical values shown at the corresponding positions, added, and then divided by the sum of the values shown in FIG. 3 to obtain the center of the 5 × 5 pixel region. A luminance image signal fb corresponding to the pixel is obtained. Using this luminance image signal fb, the differential image signal Fx may be calculated by the above-described equation (1).

  The filter shown in FIG. 3 is an example, and an arbitrary unsharp mask filter can be used. Preferably, the differential image is a second-order differential image (scalar amount) with a Gaussian function, but there is no problem with any differential image. For example, it may be a method of taking an absolute value of a first order differential (vector amount) of a general image or a difference between differential images having different filter shapes, and is not particularly limited. For example, the filter shape may use a contrast response function (transfer function) that is a visual spatial frequency characteristic. In particular, to extract a high-frequency component, an edge extraction filter such as a differential filter or a differential filter, an unsharp mask filter As well as wavelet filters can be used. The differential image may be an energy amount corresponding to the square of the intensity value.

  Returning to FIG. 2, the attribute information acquisition unit 13 acquires attribute information such as the number of effective gradations, the number of pixels, the output resolution, or the number of print lines from the input image signal and passes it to the sharpness intensity measurement unit 14. If the sharpness intensity measurement unit 14 does not perform correction processing using attribute information, the attribute information acquisition unit 13 may be omitted.

  The sharpness intensity measuring unit 14 measures the sharpness intensity from the differential image signal obtained by the band processing unit 12. As a method therefor, here, a histogram indicating the correspondence between the value of the differential image signal and the number of pixels is calculated, and the maximum value in the histogram is 3 to 10%, preferably 5 to 8% of the total number of pixels. A frequency value occupying any ratio is calculated, and the value of the differential image signal corresponding to the frequency value is defined as the sharpness intensity. Alternatively, frequency values occupying a plurality of ratios between 3 to 10%, preferably 5 to 8% of the total number of pixels are calculated from the maximum value in the histogram, and the sharpness intensity is weighted to the plurality of frequency values. It can be. The sharpness intensity may be corrected in consideration of the attribute information obtained by the attribute information acquisition unit 14.

  FIG. 4 is an explanatory diagram of an example of a histogram calculated by the sharpness intensity measurement unit 14. When the relationship between the value (edge intensity) of the differentiated image signal obtained by differentiating the image signal such as a natural image and the number of pixels (frequency) is obtained, for example, a histogram as shown in FIG. 4 is obtained. The portion where the value of the differential image signal is small is a portion where the image is almost uniform or the image changes slowly. The sharper the change in the image, the larger the value of the differential image signal.

  Then, the value of the differential image signal becomes maximum at the portion (edge) where the change in the image is the largest, and this value is shown as the maximum intensity value Fmax in FIG. This maximum intensity value Fmax indicates the largest part of the change in the image as described above, but in reality, an undesirable edge occurs in the image due to noise or the like, and the maximum intensity value Fmax is caused by the edge. It is often obtained. Therefore, there is a problem in setting the maximum intensity value Fmax to reflect the sharpness intensity of the input image signal.

  In the present invention, a frequency value that occupies any proportion between 3 to 10% of the total number of pixels, desirably 5 to 8%, is calculated from the maximum intensity value Fmax, and corresponds to the frequency value. The value of the differential image signal is obtained as the sharpness intensity. FIG. 4 shows that the value shown as the maximum neighborhood value P is obtained as the sharpness intensity.

Further, the sharpness intensity can be obtained by appropriately correcting the maximum neighborhood value Sd. For example, assuming that the sharpness intensity corresponding to 5% of the total number of pixels from the maximum intensity value Fmax is Sd5, the maximum neighborhood value P5 at that time is used, for example, Sd5 = K × P5 / N (2)
It can ask for. Here, N is a normalization coefficient, and K is an arbitrary coefficient. The coefficient K at this time is a parameter determined by attribute information such as the number of pixels to be evaluated, the number of gradations, the output resolution of the image processing apparatus, or the number of output lines. These pieces of attribute information are acquired from the attribute information acquisition unit 14. Of course, such correction may not be performed.

  FIG. 5 is a graph showing an example of the relationship between measured sharpness intensity and subjective sharpness intensity. FIG. 5 shows a graph in which the sharpness intensity measured as described above and the subjective sharpness intensity felt by the observer are correlated. FIG. 5 shows respective graphs with respect to the 3% ratio, the 5% ratio, and the 10% ratio of the total number of pixels counted from the maximum intensity value Fmax. As can be seen from FIG. 5, the measured sharpness intensity and the subjective sharpness intensity of the observer have a predetermined relationship. Therefore, the measured sharpness intensity reflects the subjective sharpness intensity of the observer, and good sharpness processing can be performed using the measured sharpness intensity.

  However, if the ratio is less than 3% or exceeds 10%, a graph as shown in FIG. 5 cannot be obtained. If it is less than 3%, it is likely to be affected by noise in the image, and it is often a differential value at the edge of the noise. For this reason, even if the measurement values are the same, the subjective sharpness strength felt by the observer varies greatly depending on the image, and the relationship shown in FIG. 5 cannot be obtained. Therefore, even if the measured sharpness intensity is used, good sharpness correction cannot be performed.

  Further, if the distance exceeds the maximum intensity value Fmax by more than 10%, this time, it is easily affected by the contents of the image. That is, when a line is drawn on a flat image, it is visually judged as a sharp image by the line. However, if the number of pixels in the edge portion of the line is small, the measured sharpness intensity is low, and the subjective sharpness intensity of the observer is not reflected. The same applies to the reverse case, and the relationship shown in FIG. 5 cannot be obtained.

  FIG. 6 is an explanatory diagram of an experimental result of correspondence between measured sharpness intensity and subjective sharpness intensity at each ratio from the maximum intensity value Fmax. By actually changing the ratio from the maximum intensity value Fmax and examining the correspondence between the measured sharpness intensity and the subjective sharpness intensity, between 3% and 10%, the measured sharpness intensity and the subjective sharpness intensity For example, a good relationship as shown in FIG. 5 could be found, and a good relationship was obtained particularly at 5% to 8%. However, in other ratios, the variation due to the image was large, and the relationship as shown in FIG. 5 could not be obtained. Therefore, the ratio for acquiring the value of the differential image may be set within the range of 3% to 10%, preferably 5% to 8% from the maximum intensity value Fmax.

  Note that a plurality of ratios may be selected in the above-described range, and the value of the differential image signal corresponding to the frequency value including the pixels having the respective ratios may be weighted to obtain the sharpness intensity.

  In the above description, the sharpness intensity is measured using the input image signal as it is. However, for example, the sharpness intensity may be measured for an image signal obtained by thinning out pixels.

  Using the sharpness intensity measured by the sharpness measuring unit 1 configured as described above, the sharpness processing coefficient determination unit 2 determines a processing coefficient, and the sharpness processing unit 3 performs sharpness processing on the input image signal according to the processing coefficient. Will be given. As a result, sharpness processing can be performed in accordance with the observer's subjectivity, and a good image signal can be obtained.

  FIG. 7 is a block diagram illustrating a second example of the sharpness measuring unit 1. In the figure, parts similar to those in FIG. Reference numeral 15 denotes an image area selection unit. In the second example, the sharpness intensity measurement is limited to a part of the image.

  The image area selection unit 15 selects an area in the image to be measured for sharpness intensity. The selected measurement target region is subjected to the same processing as in the first example, and the sharpness intensity is measured. Therefore, the sharpness intensity measurement unit 14 creates a histogram from the differential image signal in the selected area, and the maximum intensity value Fmax is 3 to 10%, preferably 5 to 8% of the total number of pixels in the measurement target area. The sharpness intensity may be calculated by obtaining the value of the differential image signal corresponding to any one or a plurality of ratio frequency values. The attribute information acquisition unit 13 may also acquire the attribute information of the measurement target area.

  In this way, the sharpness intensity in a specific area in the image can be measured. For example, it is possible to measure the sharpness intensity for the region of interest, or to divide the entire region and measure the sharpness intensity for each divided region.

  When the sharpness processing unit 3 performs the sharpness processing, the sharpness processing is performed only on the region selected by the image region selection unit 15, and the entire image is processed by the processing coefficient obtained according to the sharpness intensity measured from a part of the region. On the other hand, sharpness processing may be performed. For example, the sharpness processing can be performed on the entire image using the sharpness intensity measured for the attention area. When the entire image is divided and the sharpness intensity is measured for each divided region, the sharpness process may be performed for each corresponding divided region.

  FIG. 8 illustrates an example of the functions of the image processing apparatus and the sharpness measuring apparatus according to the present invention, or a computer program when the image processing method and the sharpness measuring method according to the present invention are implemented by a computer program, and a storage medium storing the computer program. FIG. In the figure, 21 is a program, 22 is a computer, 31 is a magneto-optical disk, 32 is an optical disk, 33 is a magnetic disk, 34 is a memory, 41 is a magneto-optical disk apparatus, 42 is an optical disk apparatus, and 43 is a magnetic disk apparatus.

  Part or all of the processing of each unit described above can be realized by a program 21 that can be executed by a computer. In this case, the program 21 and data used by the program can be stored in a computer-readable storage medium. A storage medium is a signal format that causes a state of change in energy such as magnetism, light, electricity, etc. according to the description of a program to a reader provided in hardware resources of a computer. Thus, the description content of the program can be transmitted to the reading device. For example, there are a magneto-optical disk 31, an optical disk 32 (including a CD and a DVD), a magnetic disk 33, a memory 34 (including an IC card, a memory card, and the like). Of course, these storage media are not limited to portable types.

  By storing the program 21 in these storage media and mounting these storage media in, for example, the magneto-optical disk device 41, the optical disk device 42, the magnetic disk device 43, or a memory slot (not shown) of the computer 22, The program 21 can be read to execute the functions of the image processing apparatus and the sharpness measuring apparatus of the present invention or the image processing method and the sharpness measuring method of the present invention. Alternatively, a storage medium may be attached to the computer 22 in advance, and the program 21 may be transferred to the computer 22 via a network, for example, and the program 21 may be stored and executed on the storage medium.

  Of course, some functions may be configured by hardware, or all may be configured by hardware. Alternatively, it can be incorporated as part of other software. Further, it can be incorporated as a part of another apparatus such as an output device.

It is a block diagram which shows one Embodiment of the image processing apparatus and image processing method of this invention. 2 is a block diagram illustrating a first example of a sharpness measuring unit 1. FIG. It is explanatory drawing of an example of an unsharp mask filter. It is explanatory drawing of an example of the histogram calculated by the sharpness intensity | strength measurement part. It is a graph which shows an example of the relationship between the measured sharpness intensity | strength and subjective sharpness intensity | strength. It is explanatory drawing of the experimental result of a response | compatibility with the measured sharpness intensity | strength and subjective sharpness intensity | strength in each ratio from the maximum intensity value Fmax. 6 is a block diagram illustrating a second example of the sharpness measuring unit 1. FIG. It is explanatory drawing of an example of the storage medium which stored the computer program in the case of implement | achieving the function of the image processing apparatus and sharpness measuring apparatus of this invention, or the image processing method and sharpness measuring method of this invention with a computer program.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Sharpness measurement part, 2 ... Sharpness processing coefficient determination part, 3 ... Sharpness processing part, 11 ... Lightness brightness signal conversion part, 12 ... Band processing part, 13 ... Attribute information acquisition part, 14 ... Sharpness intensity measurement part, 15 ... Image region selection unit, 21 ... program, 22 ... computer, 31 ... magneto-optical disk, 32 ... optical disk, 33 ... magnetic disk, 34 ... memory, 41 ... magneto-optical disk device, 42 ... optical disk device, 43 ... magnetic disk device.

Claims (14)

  In a sharpness measuring apparatus for measuring the sharpness intensity of an input digital image signal, a lightness / luminance conversion means for converting the digital image signal into a lightness / luminance signal indicating at least perceptually equal lightness or luminance, and the lightness / luminance Band processing means for performing differential processing on the signal to obtain a differential image signal, and sharpness intensity measuring means for measuring sharpness intensity from the differential image signal, wherein the sharpness intensity measuring means is a value of the differential image signal And calculating a frequency value that occupies any proportion between 3 to 10% of the total number of pixels from the maximum value in the histogram and calculating the histogram corresponding to the frequency value. A sharpness measuring apparatus characterized in that the value of the differential image signal is defined as sharpness intensity.   In a sharpness measuring apparatus for measuring the sharpness intensity of an input digital image signal, a lightness / luminance conversion means for converting the digital image signal into a lightness / luminance signal indicating at least perceptually equal lightness or luminance, and the lightness / luminance Band processing means for performing differential processing on the signal to obtain a differential image signal, and sharpness intensity measuring means for measuring sharpness intensity from the differential image signal, wherein the sharpness intensity measuring means is a value of the differential image signal And a histogram indicating the correspondence relationship between the number of pixels and a frequency value occupying a plurality of ratios between 3 to 10% of the total number of pixels from the maximum value in the histogram, respectively, and a plurality of frequency values Sharpening intensity by weighting the value of the differential image signal corresponding to Scan measuring device.   2. The image processing apparatus according to claim 1, further comprising an image area selecting unit that selects a measurement target area of sharpness intensity, wherein the sharpness intensity measurement unit calculates the histogram of the measurement target area and measures the sharpness intensity. Alternatively, the sharpness measuring apparatus according to claim 2.   Further, the digital image signal has information acquisition means for acquiring attribute information such as the number of effective gradations, the number of pixels, and the output resolution or the number of printed lines of the measurement target area of the sharpness intensity, the sharpness intensity measurement means, 4. The sharpness measuring apparatus according to claim 1, wherein the sharpness intensity is corrected in consideration of the attribute information acquired by the information acquisition unit.   In the sharpness measurement method for measuring the sharpness intensity of an input digital image signal, the digital image signal is converted into a brightness luminance signal indicating brightness or luminance that is at least perceptually equivalent by a brightness / luminance conversion means, and the brightness / luminance is converted. The signal is subjected to differential processing by band processing means to obtain a differential image signal, and a sharpness intensity measuring means calculates a histogram indicating a correspondence relationship between the value of the differential image signal and the number of pixels, and calculates the total from the maximum value in the histogram. A sharpness measurement method, wherein a frequency value occupying any ratio between 3% and 10% of the number of pixels is calculated, and a value of the differential image signal corresponding to the frequency value is defined as a sharpness intensity.   In the sharpness measurement method for measuring the sharpness intensity of an input digital image signal, the digital image signal is converted into a brightness luminance signal indicating brightness or luminance that is at least perceptually equivalent by a brightness / luminance conversion means, and the brightness / luminance is converted. The signal is subjected to differential processing by band processing means to obtain a differential image signal, and a sharpness intensity measuring means calculates a histogram indicating a correspondence relationship between the value of the differential image signal and the number of pixels, and calculates the total from the maximum value in the histogram. Calculating a frequency value occupying a plurality of proportions between 3 to 10% of the number of pixels, and weighting the value of the differential image signal corresponding to each of the plurality of frequency values to obtain a sharpness intensity. Characteristic sharpness measurement method.   The sharpness measurement method according to claim 5 or 6, further comprising: selecting a measurement target area of sharpness intensity, calculating the histogram for the measurement target area, and measuring the sharpness intensity.   Further, the attribute information such as the effective gradation number, the number of pixels, the output resolution or the number of printed lines of the measurement target area of the sharpness intensity in the digital image signal is acquired, and the sharpness intensity is corrected in consideration of the attribute information. The sharpness measuring method according to claim 5, wherein the sharpness measuring method is performed.   5. An image processing apparatus for performing sharpness processing on an input digital image signal, wherein the sharpness measurement apparatus according to any one of claims 1 to 4 and the sharpness intensity obtained by the sharpness measurement apparatus are subjected to sharpness. An image comprising sharpness processing coefficient determining means for determining a coefficient for performing processing, and sharpness processing means for performing sharpness processing on the digital image signal in accordance with the coefficient determined by the sharpness processing coefficient determining means Processing equipment.   An image processing method for performing sharpness processing on an input digital image signal, wherein a sharpness intensity is obtained by the sharpness measuring method according to any one of claims 5 to 8, and the sharpness processing is performed from the sharpness intensity. An image processing method characterized in that a coefficient when performing the determination is determined by a sharpness processing coefficient determination means, and sharpness processing is performed by the sharpness processing means on the digital image signal in accordance with the determined coefficient.   A sharpness measurement program for measuring the sharpness intensity of an input digital image signal, wherein the sharpness measurement program according to any one of claims 5 to 8 is executed by a computer.   An image processing program for performing sharpness processing on an input digital image signal, causing the computer to execute the image processing method according to claim 10.   9. A computer-readable storage medium storing a sharpness measurement program for measuring the sharpness intensity of an input digital image signal, causing the computer to execute the sharpness measurement method according to any one of claims 5 to 8. A computer-readable storage medium storing a sharpness measurement program.   A computer-readable storage medium storing an image processing program for performing sharpness processing on an input digital image signal stores the image processing program for causing the computer to execute the image processing method according to claim 10. A computer-readable storage medium.

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