JPH10150570A - Method, device for specifying defective pixel in digital image and recording medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To specify a defective pixel while minimizing the labor of operator by determining a threshold value, based on the average value of pixel values inside a rectangular frame further limiting an evaluation area, and defining only the group of pixels in the limited rectangular frame as an object. SOLUTION: The operator displays the desired image from an image storage part 1 onto a monitor 5 and instructs pixels near the defective pixel through a mouse or the like. While referring to the size of area in an area-setting part 17, an evaluation area-setting part 19 sets an area near the group of these instructed pixels as the evaluation area and transfers it to a memory 21 for processing. A defective pixel candidate setting part 23 sets pixels having darkest pixel value in that area as defective pixel candidates. An average line value calculating part 25 calculates average values on the upper, lower, left and right sides of defective pixel candidates. An area-limiting part 27 further limits the evaluation area from the average values. A defective pixel discriminating part 31 compares the defective pixel candidates with the threshold value calculated by a threshold value calculating part 29 and discriminates dark defective pixels. At a defective pixel correction processing part 33, the defective pixels are corrected and replaced with data in the memory 21 for processing.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a pixel (hereinafter referred to as a pixel) which is not normally converted due to dust or dust when an original image such as a reversal film or print is converted into a digital image by a reading means such as a scanner. The present invention relates to a method and an apparatus for specifying a defective pixel of a digital image for specifying a defective pixel, and a recording medium, and more particularly to a technique for specifying a defective pixel in a digital image with little effort.

[0002]

2. Description of the Related Art When an original image such as a reversal film or a color print is converted into a digital image by an image reading means such as a scanner, if dust or dust adheres to the original image or the reading means, the portion of the original image or the reading means is removed. The original image or the original image corresponding to the position is not normally converted into a digital image and becomes an unnecessary defective pixel. That is, the digital image converted in the above state includes unnecessary defective pixels and normal pixels in which the original image has been normally converted. Since a digital image including unnecessary defective pixels as described above has poor quality as it is, defective pixels are usually removed to improve the quality.

[0003] Ideally, such a defective pixel removing operation should completely remove the defective pixel automatically without human intervention, but at present, such a technical level has not been reached. Is reality. Therefore, the operator's labor is small, and the digital image after removing the defective pixels is visually uncomfortable.
This is a technical issue.

The operation of removing a defective pixel includes a plurality of steps including identification of a defective pixel, correction of the identified defective pixel, and the like. This is a step of specifying a defective pixel existing in the image. Various methods have been put into practical use as a method for specifying the defective pixel. The following operation is performed by an operator using a mouse, for example, while watching a digital image displayed on a display.

(1) Specify defective pixels one by one. (2) The outer periphery is designated by a free curve so as to surround the defective pixel. (3) Two points are specified so as to include a defective pixel inside, and a rectangular or circular area is specified. Although not put to practical use, there has been proposed a method of reducing the burden on the operator by (4) designating only one defective pixel or its vicinity.

[0006]

SUMMARY OF THE INVENTION In each of the above methods,
It is clear that the method (4), which requires only one instruction, has the least burden on the operator, but the realization of the proposed method has the following problems.

That is, as shown in FIG. 10, a fixed area centered on a designated one defective pixel DP1 is set as an evaluation area ER, and the pixels in this evaluation area ER are uniformly specified as defective pixels. The defective pixel DP2 [not indicated] in that area can be automatically specified as a defective pixel, but the normal pixel NP in the evaluation area ER is also specified as a defective pixel. Therefore, the specified defective pixels (the normal pixel NP and the defective pixel D)
P1 and DP2) are corrected by interpolation or the like using the pixel values of the normal pixels located around the evaluation area ER, so that even the normal pixels NP that do not need to be corrected are corrected. The texture (also called texture) of the original image is easily lost from the digital image. Therefore, it is conceivable to specify a defective pixel in the evaluation area ER based on a certain threshold instead of uniformly specifying all the pixels existing in the evaluation area ER as defective pixels as described above. However, when a threshold value is simply set and a defective pixel is determined based on the threshold value, a normal pixel NP ′ having a dark pixel value such as a shadow or a black wall in the evaluation area ER as shown in FIG.
Exists, even the normal pixels NP ′ are specified as defective pixels. Therefore, the texture of the original image is also likely to be lost. Because of these problems, it is difficult to put the proposed method (4) into practical use.

The present invention has been made in view of such circumstances, and determines the threshold value based on the pixel value of a rectangular frame further limiting the evaluation area, thereby minimizing the operator's labor. It is an object of the present invention to provide a method, a device, and a recording medium for specifying a defective pixel of a digital image capable of specifying a defective pixel.

[0009]

The present invention has the following configuration in order to achieve the above object. That is, the method for identifying defective pixels in a digital image according to claim 1 is characterized in that when an original image is converted into a digital image by a reading means, normal pixels normally converted from the original image and dust and dust are generated. A method for identifying a defective pixel in a digital image including a pixel group including a defective pixel that has occurred, comprising: (a) designating a vicinity of a defective pixel in the digital image; Setting a pixel group included in an area of a predetermined size with the center as an evaluation area; and (c) determining a pixel having the darkest pixel value among pixels near the center of the evaluation area as a defect. Setting a pixel candidate as a pixel candidate; and (d) in a horizontal direction of a pixel above the defective pixel candidate with respect to a pixel group around the defective pixel candidate among the pixel groups in the evaluation area. The upper line formed by each pixel along, the lower line formed by each pixel along the horizontal direction of the pixel below the defective pixel candidate, and the vertical direction of the pixel on the left side of the defective pixel candidate The average value of the pixel values is calculated for each line consisting of a left line composed of pixels along the line and a right line composed of pixels along the vertical direction of the pixel on the right side of the defective pixel candidate. (E) calculating the average value of each of the upper, lower, left, and right lines and selecting the brightest one for each of the upper, lower, left, and right lines to further limit the evaluation area; (G) calculating a threshold value of a pixel value for determining a defective pixel based on an average value of pixel values of a rectangular frame formed by each of the selected upper, lower, left, and right lines; Said Compared pixel values of all pixels in the form frame and with said threshold value and is characterized in that it comprises the steps of determining a defective pixel darker than the threshold value.

According to a second aspect of the present invention, in the method for identifying defective pixels of a digital image according to the first aspect, the size of the area is determined before the step (a). It is characterized by including a setting process.

According to a third aspect of the present invention, there is provided an apparatus for identifying defective pixels in a digital image, wherein when an original image is converted into a digital image by a reading means, normal pixels normally converted from the original image and dust and dirt are removed. In a device for identifying the defective pixel in a digital image including a pixel group including a defective pixel caused by the cause, a storage unit for storing the digital image, a display unit for displaying the digital image, and the display Means for instructing the vicinity of a defective pixel of the digital image displayed on the means, and an evaluation for setting a group of pixels included in a region of a predetermined size around the designated pixel as an evaluation region Area setting means; defective pixel candidate setting means for setting a pixel having the darkest pixel value among defective pixels near the center of the evaluation area as a defective pixel candidate; Among the pixel groups in the area, the upper line constituted by the pixels along the left and right direction of the pixel above the defective pixel candidate with respect to the pixel group around the defective pixel candidate, A lower line composed of pixels along the left and right direction of the pixel below the pixel candidate, and a left line composed of pixels along the vertical direction of the pixel on the left side of the defective pixel candidate,
An average value calculating unit that calculates an average value of pixel values as a line average value for each line including a right line formed by pixels along a vertical direction of a pixel on the right side of the defective pixel candidate; An area limiter for further selecting the brightest one for each of the upper, lower, left and right lines from the average values of the left and right lines, to further limit the evaluation area; and a line for each of the selected upper, lower, left, and right lines Threshold calculating means for calculating a threshold of a pixel value for determining a defective pixel based on an average value of pixel values of a rectangular frame formed by: And a defective pixel determining unit that determines a pixel darker than the threshold value as a defective pixel.

According to a fourth aspect of the present invention, there is provided the digital image defective pixel specifying device, wherein the size of the area is set in addition to the means. It is characterized by having an area setting means.

Further, in the recording medium according to the present invention, when the original image is converted into a digital image by the reading means, a normal pixel normally converted from the original image and a normal image are generated due to dust and the like. A program for specifying the defective pixel in a digital image composed of a pixel group including a defective pixel including: (a) a process for specifying a vicinity of a defective pixel in the digital image; A process of setting, as an evaluation region, a group of pixels included in a region of a predetermined size centering on the pixel; and (c) a pixel having a darkest pixel value among pixels near the center of the evaluation region. And (d) selecting a pixel group around the defective pixel candidate from among the pixel groups in the evaluation area, and setting the left and right of the pixel above the defective pixel candidate. In the direction An upper line formed by each pixel, a lower line formed by each pixel along the left and right direction of a pixel below the defective pixel candidate, and a vertical direction of a pixel on the left side of the defective pixel candidate. The average value of the pixel values is calculated for each line consisting of a left line composed of pixels along the line and a right line composed of pixels along the vertical direction of the pixel on the right side of the defective pixel candidate. (E) a process of calculating as an average value, (e) a process of selecting the brightest one for each of the upper, lower, left, and right lines from among the average values of the upper, lower, left, and right lines one by one to further limit the evaluation area; (G) calculating a threshold value of a pixel value for determining a defective pixel based on an average value of pixel values of a rectangular frame formed by each of the selected upper, lower, left, and right lines; The rectangle A process for comparing the pixel values of all the pixels in the frame with the threshold value, and determining a pixel darker than the threshold value as a defective pixel, and a program for controlling a computer to perform the process. is there.

[0014]

The operation of the method according to the present invention is as follows. The operator recognizes a defective pixel existing in the digital image and gives an instruction on the defective pixel or the vicinity of the defective pixel (step (a)). A pixel group included in a region of a predetermined size centering on the designated pixel is set as an evaluation region (step (b)). Since the operator points to a pixel in the digital image by focusing on the defective pixel, the defective pixel always exists near the center of the set evaluation area. Therefore, the pixel having the darkest pixel value is determined from the pixels in the vicinity of the center of the evaluation area, and is set as a defective pixel candidate (step (c)).

Next, an upper line composed of pixels along the left-right direction of each pixel above the defective pixel candidate is determined for the pixel group within the set evaluation area, and each of these upper lines is determined. The average value of the pixel values for each line is calculated as the line average value. That is, an average value is calculated for the pixel values of each pixel row in the evaluation area located above the defective pixel candidate, and these are set as a line average value. Similarly, the average value of the pixel values for each lower line located below the defective pixel candidate is calculated as the line average value. further,
A left line composed of each pixel value along the vertical direction of each pixel value on the left side of the defective pixel candidate is obtained, and an average value of the pixel values of each of these left lines is calculated as a line average value. That is, an average value is calculated for the pixel values of each pixel row in the evaluation area located on the left side of the defective pixel candidate, and these are set as a line average value. Similarly,
The average value of the pixel values for each right line located on the right side of the defective pixel candidate is calculated as a line average value (step (d)).

Next, the brightest one is obtained for each direction from among the average values of the lines in the upper, lower, left and right directions, and the evaluation area is further limited (step (e)). In other words, in the evaluation area, the brightest pixel is selected from each pixel row located above and below the defective pixel candidate and each pixel column located left and right of the defective pixel candidate, and the predetermined size is evaluated. Further narrow the area. By further limiting the evaluation area based on the pixel value in this way, normal pixels that are far from the defective pixel candidates but are present in the evaluation area can be excluded from the subsequent processing targets.

On the basis of the average value of the pixel values of the rectangular frame formed by each of the upper, lower, left and right lines defining the evaluation area, a threshold value as a reference for determining a defective pixel is calculated (process). (F)). The reason for adopting a rectangular frame-shaped pixel group excluding the area surrounded by each line for calculating the threshold value, instead of the area surrounded by each line, is as follows. In other words, since the defective pixel including the defective pixel candidate and the normal pixel are mixed in the area defined by each line, the threshold value is calculated based on the pixel value of the pixel group existing in the limited area. However, a defective pixel and a normal pixel cannot be accurately distinguished. Therefore, a threshold value is calculated based on the average value of the pixel values of a rectangular frame (consisting of the brightest pixel row and pixel column) including only normal pixels having a pixel value brighter than the defective pixel.

The threshold value calculated as described above is compared with the pixel values of all the pixels in the rectangular frame, and a pixel having a pixel value darker than the threshold value is determined as a defective pixel (step (g)). As described above, the threshold value is calculated based on the average value of the pixel values of the rectangular frame including only the normal pixels, and the defective pixel is specified only for the pixel group in the rectangular frame further limiting the evaluation area, so that the pixel is accurately determined. Only defective pixels can be specified. Further, since the operator only has to first designate the vicinity of the defective pixel, the labor can be minimized.

According to the second aspect of the present invention, since the size of the area that determines the evaluation area is set, the case where the defective pixel group exceeds the evaluation area or the defective pixel group is distributed to a plurality of locations is determined. The size of the evaluation area can be changed in accordance with the mode of the defective pixel, such as the case where the error occurs. Therefore, defective pixels of various sizes and defective pixels of various modes can be appropriately specified.

The operation of the device according to the third aspect of the present invention is as follows. In a state where the digital image stored in the storage means is displayed on the display means, the operator indicates the defective pixel or the vicinity thereof by the instruction means. The evaluation area setting means sets, as an evaluation area, a group of pixels included in an area of a preset size, centering on a pixel designated by the operator. Since the vicinity of the center of the evaluation area is a place where the operator pays attention to and designates the defective pixel, the defective pixel always exists near the center.
Therefore, the defective pixel candidate setting means sets a pixel having the darkest pixel value from the vicinity of the center as a defective pixel candidate.

The average value calculating means obtains an upper line composed of pixels along the left-right direction of each pixel located above the defective pixel candidate with respect to the pixel group within the set evaluation area. The average value of the pixel values for each of these upper lines is calculated as a line average value. That is, an average value is calculated for the pixel values of each pixel row in the evaluation area located above the defective pixel candidate, and these are set as a line average value. Similarly, the average value of the pixel values for each lower line located below the defective pixel candidate is calculated as the line average value. Further, a left line constituted by each pixel value along the vertical direction of each pixel value on the left side of the defective pixel candidate is obtained, and an average value of the pixel values of each of these left lines is calculated as a line average value. I do. That is, an average value is calculated for the pixel values of each pixel row in the evaluation area located on the left side of the defective pixel candidate, and these are set as a line average value. Similarly, the average value of the pixel values for each right line located on the right side of the defective pixel candidate is calculated as the line average value.

The area limiter further limits the evaluation area by finding the brightest one for each direction from among the line averages in the up, down, left, and right directions calculated by the average value calculator. This further narrows down the evaluation area of a preset size. By further limiting the evaluation area based on the pixel value in this way, normal pixels that are far from the defective pixel candidates but are present in the evaluation area can be excluded from the subsequent processing targets.

The threshold value calculating means calculates a threshold value, which is a reference for determining a defective pixel, based on the average value of the pixel values of the rectangular frame. The defective pixel determining means compares the pixel values of all the pixels in the rectangular frame with the calculated threshold value, and determines a pixel having a pixel value darker than the threshold value as a defective pixel. As described above, the threshold value is calculated based on the average value of the pixel values of the rectangular frame including only the normal pixels, and the defective pixel is specified only for the pixel group in the rectangular frame further limiting the evaluation area, so that the pixel is accurately determined. Only defective pixels can be specified.
Further, since the operator only has to first instruct the vicinity of the defective pixel by the instructing means, the labor can be minimized.

According to the fourth aspect of the present invention, the size of the area for determining the evaluation area is set by the area setting means. The size of the evaluation area can be changed according to the mode of the defective pixel, such as when the evaluation area is dispersed at a plurality of locations. Therefore, defective pixels of various sizes and defective pixels of various modes can be appropriately specified.

Further, by causing a computer to execute the program stored in the recording medium according to the present invention, a process for designating a defective pixel existing in the digital image recognized by the operator or the vicinity of the defective pixel is performed. Let Then, a pixel group included in a region of a predetermined size centering on the designated pixel is set as an evaluation region. Since the operator points to a pixel in the digital image by focusing on the defective pixel, the defective pixel always exists near the center of the set evaluation area. Therefore, the pixel having the darkest pixel value is determined from the pixels near the center of the evaluation area, and this is set as a defective pixel candidate.

Next, an upper line composed of pixels along the left-right direction of the pixels above the defective pixel candidate is determined for the pixel group in the set evaluation area, and each of these upper lines is determined. The average value of the pixel values for each line is calculated as a line average value. Similarly, an average value of pixel values for each lower line located below the defective pixel candidate is calculated as a line average value. Further, a left line constituted by each pixel value along the vertical direction of each pixel value on the left side of the defective pixel candidate is obtained, and an average value of the pixel values of each of these left lines is calculated as a line average value. Let it. Similarly, an average value of pixel values for each right line located on the right side of the defective pixel candidate is calculated as a line average value.

Next, from the average values of the lines in the upper, lower, left, and right directions, the brightest one in each direction is obtained to further limit the evaluation area. By further limiting the evaluation area based on the pixel value in this way, normal pixels that are far from the defective pixel candidate but exist in the evaluation area can be excluded from the subsequent processing targets. On the basis of the average value of the pixel values of the rectangular frame formed by each of the upper, lower, left, and right lines defining the evaluation area, a threshold that is a reference for determining a defective pixel is calculated.

The threshold value calculated as described above is compared with the pixel values of all the pixels in the rectangular frame, and a pixel having a pixel value darker than the threshold value is determined as a defective pixel. As described above, the threshold value is calculated based on the average value of the pixel values of the rectangular frame including only the normal pixels, and the defective pixel is specified only for the pixel group within the rectangular frame further limiting the evaluation area. Only defective pixels can be specified. Further, since the operator only needs to instruct the computer near the defective pixel, labor can be minimized.

[0029]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram illustrating a schematic configuration of an image processing apparatus that performs image processing including a method for identifying defective pixels in a digital image according to the present invention.

In FIG. 1, reference numeral 1 denotes an image storage unit for storing a plurality of digital images, which is constituted by a hard disk device or a magneto-optical disk device having a large storage capacity. This image storage unit 1 corresponds to a storage unit in the present invention. A digital image is obtained by converting an original image such as a color reversal film or a color print into digital data using a scanner (reading means) (not shown). At the time of reading, dust and dirt adhere to the original image and the reading unit of the scanner. If so, that part is not converted normally and becomes a defective pixel. Here, a description will be given assuming that the digital image stored in the image storage unit 1 includes the defective pixel and a normal pixel normally converted from the original image without being affected by dust or the like. In addition,
In general, when the original image is in color, the digital image includes information of each of the three colors of R, G, and B. In the following, for ease of understanding, a digital image expressed in grayscale in black and white will be described. This will be described using an image as an example. In addition,
For example, when gradation is expressed by performing quantization with 8 bits,
Although the pixel value of each pixel will have a value of 0 to 255,
In the following description, a pixel value near “0” is expressed as dark, and a pixel value near “255” is expressed as bright.

When an operator selects a desired one of a plurality of digital images stored in the image storage unit 1, the image is displayed on a monitor 5 corresponding to a display unit via the control unit 3. The selection of a desired digital image is performed using the keyboard 7 or the mouse 9 as the instruction means. The control unit 3 includes a CPU, a RAM, and a RO.
M and the like. This image processing apparatus stores a program for causing the control unit 3 to perform processing described later in the storage device 11 or stores the program in a recording medium M such as a floppy disk, a magneto-optical disk, or an IC card. The program that has been
There is a form of reading from. In this example, the control unit 3 reads a program from the recording medium M via the driving device 15, and the control unit 3 executes processing described later in detail based on the program. The operation of reading the program need only be executed once when the apparatus is started. In addition,
In the following description, each process according to the above program is also shown in a functional block diagram for easy understanding.

The area storage section 17 stores a preset area size. The size of this area can be changed by directly inputting a numerical value (for example, the number of dots) from the keyboard 7 or indirectly selecting and inputting a numerical value using the mouse 9 according to the judgment of the operator. In the following description, this size is 15
It is assumed that × 15 dots are set in advance. The evaluation area setting unit 19 refers to the size of the area stored in the area storage unit 17, sets a pixel group included in the area around the point designated by the operator as an evaluation area, The pixel group included in the evaluation area is transferred to the processing memory 21. The area storage unit 17
Corresponds to the area setting means of the present invention, and the above-described evaluation area setting section 19 corresponds to the evaluation area setting means of the present invention.

The defective pixel candidate setting unit 23 targets the pixel group in the evaluation area transferred to the processing memory 21 and selects the pixel group having the darkest pixel value from the pixel group near the center of the pixel group. Pixel candidate ". The line average value calculation unit 25 outputs
An upper line composed of pixels along the left-right direction of pixels above the defective pixel candidate, that is, an average value of pixel values of each pixel row is calculated for each upper line. Similarly, for the lower line below the defective pixel candidate, the average value of the pixel values is calculated for each lower line. Also,
The left line composed of pixels along the vertical direction of the pixel on the left side of the defective pixel candidate, that is, the average value of the pixel values of each pixel column is calculated for each left line, and similarly, the defective pixel candidate is calculated. As for the right line on the right side, the average value of the pixel values is calculated for each right line. The defective pixel candidate setting unit 23 and the line average value calculation unit 25
Respectively correspond to a defective pixel candidate setting unit and an average value calculating unit in the present invention.

An area limiting section 27 corresponding to area limiting means
Is to select the brightest line for each direction one by one from the average value of the pixel values of each line calculated by the line average value calculation unit 25, and further narrow down the evaluation area to limit. The threshold calculator 29 calculates the average value of the pixel values of the rectangular frame formed by the upper, lower, left, and right lines selected by the region limiting unit 27, and calculates the variance thereof. Further, although details will be described later, a threshold value for determining a defective pixel is calculated based on the details. The threshold value calculated in this way is referred to by the defective pixel determination unit 31, and is compared with the pixel value of each pixel in the area defined by the rectangular frame in the pixel group stored in the processing memory 21. . As a result of the comparison, a pixel having a pixel value darker than the threshold value is determined as a defective pixel. The threshold calculator 29 corresponds to a threshold calculator in the present invention, and the defective pixel determiner 31 corresponds to a defective pixel determiner in the present invention.

After the defective pixel identification processing is completed by determining the defective pixel as described above, the coordinate value and the position data together with the pixel values of those pixels are stored in the defective pixel correction processing unit 3.
3 and is processed by interpolation or the like based on the pixel value of a normal pixel located around the defective pixel.
Are corrected. After the correction, for example, the pixel group of the processing memory 21 is replaced with the corresponding digital image data in the image storage unit 1.

Next, the operation of the apparatus will be described in detail with reference to the flowchart of FIG. 2 and the schematic diagrams of digital images of FIGS.

Step S1 (Display of Digital Image) The operator selects a desired digital image from a large number of digital images stored in the image storage unit 1 by using the keyboard 7 or the mouse 9. The selected digital image is output to the monitor 5 via the control unit 3 and displayed. In this example, for simplicity of explanation,
A description will be given assuming that a digital image F represented by 19 dots × 19 dots as shown in FIG. In addition, in FIG. 3, the code | symbol L1 attached along the up-down direction
L19 indicates a pixel row constituted by a pixel group existing along the left-right direction, and reference numerals C1 to C19 attached along the left-right direction are constituted by pixel groups existing along the vertical direction. 3 shows a pixel column. Also, in the digital image F, there is a normal pixel group NP ′ which is a group of normal pixels having relatively dark pixel values on the left side,
Near the center, there is a defective pixel group DP, which is a group of defective pixels having dark pixel values. The other pixels are a normal pixel group NP which is a group of pixels having bright pixel values. In the following description, when it is not clear whether a pixel is a defective pixel or a normal pixel in the process, it is simply referred to as a pixel P, and when it is necessary to clarify the position, the above pixel row is referred to as a pixel P. L1 to L19, and C1 to C19, each representing a pixel row, are shown in parentheses. That is, the pixel located at the upper left corner of the normal pixel group NP in FIG. 3 is represented as P (L19, C1).

Step S2 (instruction of defective pixel) The operator recognizes the defective pixel group DP based on the relationship with the pixel values of the surrounding pixels while watching the digital image F displayed on the monitor 5, and the pixel P ( L9, C11), pixel P (L10, C9), pixel P (L10, C10), pixel P (L10, C11), pixel P (L10, C12), pixel P (L11, C10), pixel P (L11, C11),
One of the pixels P (L11, C12) is designated by the mouse 9. Here, it is assumed that the pixel P (L10, C10) existing at the center of the image is designated, and this pixel is appropriately referred to as PI. As will be easily understood from the following description, it is not always necessary to designate a defective pixel, and a normal pixel near the defective pixel may be designated. Also,
This step S2 corresponds to the process (a) and the process (a) in the present invention.

Step S3 (Display Evaluation Area) The evaluation area setting section 19 refers to the area size (15 × 15 dots) stored in the area storage section 17 and outputs this information to the control section 3. . As shown in FIG.
Displays a frame having the size of the designated pixel PI as a center on the digital image F of the monitor 5 as an evaluation area ER. Further, the evaluation area setting unit 19 outputs a pixel group (pixel P (L3, C3) and pixel P (L17, C1) included in the digital image F in the pixel group.
7) is set as an evaluation area ER, and the pixels included in the evaluation area ER are transferred to the processing memory 21. In this case, the right part of the normal pixel group NP ′ having a relatively dark pixel value, the defective pixel group DP, and a part of the normal pixel group NP are transferred. Step S3 corresponds to the process (b) and the process (b) of the present invention.

Step S4 (Defective Pixel Candidate Setting) As shown in FIG. 5, the defective pixel candidate setting section 23 sets the pixel group in the processing memory 21, that is, the pixel group in the evaluation area ER from the vicinity of the center. The pixel having the darkest pixel value is set as a defective pixel candidate PA. The vicinity of the center is, for example, a rectangular area of 2 dots × 2 dots around the designated pixel PI. In this example, it is assumed that the pixel values of a plurality of [defective] pixels near the center are substantially the same, and in such a case, any of the pixels may be a defective pixel candidate. Is set as the defective pixel candidate PA with priority given to the pixel PI designated by the user. Normally, the operator recognizes a defective pixel and gives an instruction for it, so that no inconvenience can occur even with this setting.
This step S4 corresponds to the process (c) and the process (c) of the present invention.

Step S5 (Calculate Line Average Value) The line average value calculation unit 25 targets each pixel along the left and right direction of the pixel above the defective pixel candidate PA for the pixel group existing in the evaluation area ER. , Ie, seven upper lines UL1 located between the defective pixel candidate PA and the upper side of the evaluation area ER as shown in FIG.
The average of the pixel values of UL7 to UL7 is calculated as a line average value. In this case, since the upper line UL1 has three dark pixel value defective pixels near the middle thereof and the normal pixel of the normal pixel group NP ′ having a relatively dark pixel value at the left end, the average is the highest. Value is small. Also, the upper line UL7 has two normal pixels in the normal pixel group NP 'having a relatively dark pixel value at the left end thereof, so that the upper line UL1
The average value is the second smallest. Also, the upper lines UL2 to UL
No. 6 has the largest average value because there is only one normal pixel of the normal pixel group NP 'having a relatively dark pixel value at the left end. Next, as shown in FIG. 6, the average value of the pixel values of the lower lines DL1 to DL7 formed by the pixels along the left-right direction of the pixels below the defective pixel candidate PA is calculated as the line average value. I do.
In this case, the lower line DL1 has the smallest average value, and the lower lines DL2 to DL7 have larger average values than the lower line DL1. Similarly, the average value of the pixel values of the left line LL1 to LL7 and the right line RL1 to RL7 formed by the pixels along the vertical direction of the pixels located on the left and right of the defective pixel candidate PA is defined as the line average value. calculate. In this case, the left line LL7 has the smallest average value, the left line LL1 has the next smallest average value, the left line LL6 has the smallest average value after the left line LL1, and the left lines LL2 to LL5 have the largest average value. Further, for each right line, the average value increases in the order of the right line RL1, the right line RL2, and the right lines RL3 to RL7.

Step S5 corresponds to the process (d) and the process (d) in the present invention.

Step S6 (Limiting Evaluation Area) The area limiting section 27 refers to the line average values in the up, down, left, and right directions of the line average value calculating section 25, and has the brightest line average value in each direction. Select a line. The brightest is the one with the largest line average value from the relationship between the brightness and the pixel value described above. That is, in this example, five upper lines UL2 to UL6, six lower lines DL2 to DL7, four left lines LL2 to LL5,
The line average value of the five right lines RL3 to RL7 is the largest in each direction. In such a case,
The line farthest from the defective pixel candidate PA is selected for each direction for the reason described later. That is, the upper line UL6 is selected from above, and the lower line DL is selected from below.
7, the left line LL5 is selected from the left direction, and the right line RL7 is selected from the right direction. By this processing, the area is further narrowed from the initially set evaluation area ER to the defective pixel candidate PA (see FIG. 7). By limiting the evaluation area ER in this way, a part of the normal pixel group NP ′ existing on the left side of the evaluation area ER can be excluded from the following processing. Step S6 corresponds to the process (e) and the process (e) in the present invention.

Step S7 (Calculate Threshold) As shown in FIG.
, Lower line DL7, left line LL5, and right line R
A threshold value is calculated from each pixel of the rectangular frame R composed of L7. This threshold value is obtained by calculating the average value of the pixel values of the rectangular frame R by M
When the variance of the pixel values of the rectangular frame R is S and the constant is C, the threshold T is determined by T = MS × C. The reason why the variance S is subtracted from the average value M of the pixel values of the rectangular frame R in this way is to prevent the recognition of a normal pixel as a defective pixel by considering the variation of the normal pixel existing in the rectangular frame R. To do that. The variance S is a constant C
Is empirical, and the constant C is preferably a value of 2 to 3. Step S7 corresponds to the process (f) and the process (f) of the present invention. To calculate the threshold T as described above, each line UL6, DL7,
The reason for adopting the pixel group of the rectangular frame R excluding the region surrounded by LL5 and RL7 instead of the region is as follows. In other words, the defective pixel DP including the defective pixel candidate PA is located within the area defined by the lines.
And the normal pixel NP are mixed, so that even if the threshold value T is calculated based on the pixel value of the pixel group existing in the rectangular frame R, the defective pixel DP and the normal pixel NP cannot be accurately determined. . Therefore, the threshold value T is set based on the average value M of the pixel values of the rectangular frame R (consisting of the brightest pixel rows and pixel columns) including only the normal pixels NP having the pixel values brighter than the defective pixel DP. It is calculated.

Step S8 (Determine Defective Pixel) The defective pixel determination unit 31 compares the threshold value T with the pixel values of all the pixels present in the rectangular frame R, and determines a pixel value darker (smaller) than the threshold value T. All the pixels having the pixel are determined as defective pixels. That is, in FIG. 7, the pixel values of all the pixels forming the rectangle having the vertexes at the diagonal of the pixels P (L4, C6) and the pixels P (L15, C16) inside the rectangular frame R are Compare with threshold value T. Step S8 corresponds to the process (g) and the process (g) in the present invention.

As described above, the threshold value T is determined on the basis of the average value M of the pixel values of the rectangular frame R including only normal pixels, and the defect T is determined only for the pixel group within the rectangular frame R in which the evaluation area ER is further limited. Since the pixel is specified, even if the evaluation area ER includes a normal pixel NP ′ having a dark pixel value, if the pixel is apart from the pixel PI specified by the operator, the pixel is correctly identified without being erroneously recognized as a defective pixel. Only the defective pixel can be specified. In addition, the operator only needs to first specify the vicinity of the defective pixel in one place, so that the labor can be minimized. Thus, a defective pixel can be specified while minimizing the operator's labor.

Step S9 (Correct defective pixels) The defective pixel correction processing section 33 corrects each of the defective pixels specified by the defective pixel determining section 31. For example, the pixel value of the defective pixel DP (L10, C9) is changed to the normal pixel NP (L11, C9) and the normal pixel NP (L9, C9).
, And is replaced with this pixel value.
Similarly, the correction is performed for all the defective pixels DP, and the data in the processing memory 21 is rewritten. Then, the original digital image stored in the image storage unit 1 is corrected based on the data in the processing memory 21. Since the defective pixel is accurately specified as described above, the correction can be performed with high quality without deteriorating the texture of the digital image.

Here, a supplementary explanation of step S6 will be given. As described above, in step S6, the process of limiting the evaluation area ER from FIG. 5 to FIG. 7 is performed. At this time, when there are a plurality of brightest lines in each direction, which line is selected becomes a problem. . That is, in order to further limit the evaluation area ER, it seems preferable to select the line closest to the defective pixel candidate PA because the area can be further limited. Here, as shown in FIG.
It is assumed that defective pixels are dispersed in the evaluation area ER like the defective pixel groups DP1 and DP2. In such a case, when the line closest to the defective pixel candidate PA is selected from the brightest lines one by one in each direction, the upper line UL2, the lower line DL2, the left line LL2, The right line RL3 will be selected. However, as is clear from FIG. 8, it can be seen that the defective pixel group DP2 is leaking from the limited area. In order to prevent such an inconvenience from occurring, a line farthest from the defective pixel candidate PA is selected.

Although the size of the area for determining the size of the evaluation area ER is stored in the area storage section 17 in advance, an example in which it is preferable to change the size will be described with reference to FIG. In the digital image F, a defective pixel group DP1 exists near the center of the digital image F, and a defective pixel group DP2 exists at a position distant in the right direction. In such a case,
If the operator instructs the same pixel PI as described above, the defective pixel group DP2 will be out of the evaluation area ER. In such a case, the above-described processing can be performed once again, that is, by instructing the vicinity of the defective pixel group DP2. However, changing the value of the area storage unit 17 using the keyboard 7 or the mouse 9 is one time. With this instruction, the two defective pixel groups DP1 and DP2 can be specified, which is efficient. In this example, the size of 15 × 15 dots of the area previously stored in the area storage unit 17 is changed to 16 × 16 dots.
What is necessary is just to change it to a value larger than a dot. Further, even when an extremely large defective pixel group exists, for example, when the size of the region exceeds the size of the region, it is preferable to change the size of the region. Conversely, if there is a small defective pixel group, and if this indicates a large number of surrounding normal pixel groups are included in the evaluation range, the size of the area may be set small. Note that the operator generally knows whether or not the defective pixel fits within the evaluation area ER according to the size of the defective pixel. Therefore, before the above-described step S2 (instruction of the defective pixel), that is, step S1 (the digital image It is preferable to change the size of the area according to the form of the defective pixel when the digital image is displayed on the monitor 5 and the size of the defective pixel is recognized. As a result, various types of defective pixels can be specified, and correction can be accurately performed. Further, changing the size of the region is not limited to the time of step S1, but may be changed at the time of specifying a defective pixel in step S2. Further, when the evaluation area is superimposed and displayed on the digital image at the time of step S3 (displaying the evaluation area), the position may be changed after confirming the positional relationship between the evaluation area and the defective pixel.

In the above-described example, a digital image expressed in black-and-white gradation has been described for the purpose of easy understanding. However, in general, a color digital image is often processed. . When a color image is to be processed as described above, for example, grayscale information = (R +
(G + B) / 3, and the process may be executed as described above after converting to gray scale. In fact, since defective pixels are extremely rare due to dust and dust, they do not cause any inconvenience.

Steps S2 to S8 shown in the flowchart of FIG. 2 correspond to the program of the defective pixel specifying method according to the present invention, and are stored in the recording medium M. Therefore, even if the computer does not have the configuration as shown in the block diagram shown in FIG. 1, the same operation and effect as those of the device having the above configuration can be obtained by reading and executing the recording medium M storing the above program. Obtainable.

[0052]

As is apparent from the above description, according to the method of the present invention, the threshold value is determined based on the average value of the pixel values of the rectangular frame including only normal pixels, and the evaluation area is determined. Further, since the defective pixel is specified only for the pixel group within the limited rectangular frame, even if the evaluation area includes a normal pixel having a dark pixel value, the defective pixel is separated from the pixel specified by the operator. Then, only the defective pixel can be specified accurately without erroneous recognition as a defective pixel. Further, since the operator only needs to first specify the vicinity of the defective pixel in one place, the labor can be minimized. Therefore, a method capable of specifying a defective pixel while minimizing the labor of the operator can be put to practical use. As described above, by performing processing of correcting a pixel value by a method such as interpolation after specifying a defective pixel included in a digital image, quality can be improved without lowering the texture.

According to the second aspect of the present invention, there are various defective pixel groups such as a case where the defective pixel group has a size exceeding the evaluation area and a case where the defective pixel group is dispersed at a plurality of locations. By appropriately setting the size of the evaluation area according to the mode, the defective pixel can be specified flexibly.

According to the third aspect of the present invention, the method of the first aspect can be suitably implemented.

Further, according to the invention apparatus described in claim 4, the invention method described in claim 2 can be suitably implemented.

According to the fifth aspect of the present invention, by causing a computer to execute a program stored in a recording medium, the method according to the first aspect of the present invention can be executed.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a schematic configuration of an image processing apparatus according to an embodiment.

FIG. 2 is a flowchart illustrating an operation of the image processing apparatus.

FIG. 3 is a schematic diagram showing a digital image.

FIG. 4 is a schematic diagram showing an evaluation area together with a digital image.

FIG. 5 is a schematic diagram for explaining a process of limiting an evaluation area.

FIG. 6 is a schematic diagram for explaining a process of limiting an evaluation area.

FIG. 7 is a schematic diagram showing a state in which an evaluation area is further limited.

FIG. 8 is a schematic diagram illustrating a problem that may occur when the evaluation area is limited.

FIG. 9 is a schematic diagram for explaining an example in which it is preferable to change the size of the evaluation area.

FIG. 10 is an explanatory diagram of a conventional example.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Image storage part (storage means) 3 ... Control part 5 ... Monitor (display means) 7 ... Keyboard (instruction means) 9 ... Mouse (instruction means) 11 ... Storage device 15 ... Driving device M ... Recording medium 17 ... Area storage Section (area setting means) 19 ... evaluation area setting section (evaluation area setting means) 23 ... defective pixel candidate setting section (defective pixel candidate setting means) 25 ... line average value calculation section (average value calculation means) 27 ... area limiting section (Area Limiting Means) 29 Threshold Value Calculation Unit (Threshold Calculation Means) 31 Defective Pixel Determination Unit (Defective Pixel Determination Means) 33 Defective Pixel Correction Processing Unit F Digital Image PA Defective Pixel Candidate ER Evaluation Area NP Normal Pixel group NP ': dark normal pixel group DP: defective pixel group R: rectangular frame

Claims (5)

[Claims] 1. A pixel group comprising a normal pixel normally converted from an original image and a defective pixel caused by dust or the like when the original image is converted to a digital image by a reading unit. A method for identifying the defective pixel in the digital image, comprising: (a) indicating the vicinity of the defective pixel in the digital image; and (b) setting an area of a predetermined size around the specified pixel. (C) setting a pixel group having a darkest pixel value among pixels near the center of the evaluation area as a defective pixel candidate; Of the pixel groups in the evaluation area, for the pixel group around the defective pixel candidate, an upper line composed of pixels along the left and right direction of the pixel above the defective pixel candidate, A lower line composed of pixels along the left and right direction of the pixel below the defective pixel candidate, and a left line composed of pixels along the vertical direction of the pixel on the left side of the defective pixel candidate Calculating an average value of pixel values as a line average value for each line consisting of a right line constituted by pixels along a vertical direction of a pixel on the right side of the defective pixel candidate; and (e) Selecting the brightest one for each of the upper, lower, left, and right lines from among the average values of the upper, lower, left, and right lines to further limit the evaluation area; and (f) selecting each of the selected upper, lower, left, and right lines Calculating a threshold value of a pixel value for determining a defective pixel based on an average value of pixel values of the rectangular frame formed by the lines; and (g) calculating pixel values of all pixels within the rectangular frame. Ratio with the threshold And determining a pixel darker than the threshold value as a defective pixel. 2. The method according to claim 1, further comprising the step of setting a size of the area before the step (a). Identification method. 3. A pixel group including a normal pixel normally converted from an original image when the original image is converted into a digital image by a reading unit, and a defective pixel generated due to dust or dust. In the device for identifying the defective pixel in the digital image, a storage unit for storing the digital image, a display unit for displaying the digital image, and an instruction for indicating the vicinity of the defective pixel of the digital image displayed on the display unit Means, an evaluation area setting means for setting a pixel group included in an area of a predetermined size as an evaluation area, with the designated pixel as a center, and a pixel located near the center of the evaluation area. A defective pixel candidate setting means for setting a pixel having the darkest pixel value as a defective pixel candidate; and a defective pixel candidate around a defective pixel among a group of pixels in the evaluation area. Target pixel group, an upper line composed of pixels along the left and right direction of the pixel above the defective pixel candidate, and each pixel along the left and right direction of the pixel below the defective pixel candidate And a left line composed of pixels along the vertical direction of a pixel on the left side of the defective pixel candidate, and a pixel along the vertical direction of a pixel on the right side of the defective pixel candidate Average value calculation means for calculating an average value of pixel values as a line average value for each line composed of a right line and a line composed of: An area limiting means for further selecting the bright areas one by one to further limit the evaluation area; and an average value of the pixel values of the rectangular frame formed by each of the selected upper, lower, left and right lines. A threshold value calculating means for calculating a threshold value of a pixel value for determining a defective pixel; comparing the pixel values of all the pixels within the rectangular frame with the threshold value; A defective pixel specifying device for a digital image, comprising: a defective pixel determining unit that determines a pixel as a pixel. 4. The digital image defective pixel identifying apparatus according to claim 3, further comprising an area setting means for setting a size of the area in addition to each of the means. Defective pixel identification device. 5. A pixel group including a normal pixel normally converted from an original image when the original image is converted into a digital image by a reading unit, and a defective pixel generated due to dust or dust. A recording medium storing a program for identifying the defective pixel in the digital image, comprising: (a) a process of designating a vicinity of the defective pixel in the digital image; and (b) a process of focusing on the designated pixel. A process of setting a pixel group included in an area of a predetermined size as an evaluation area; and (c) among pixels near the center of the evaluation area, a pixel having the darkest pixel value as a defective pixel candidate. (D) among the pixel groups in the evaluation area, with respect to the pixel groups around the defective pixel candidate, each pixel along the left-right direction of the pixel above the defective pixel candidate To And a lower line formed by pixels along the left and right direction of a pixel below the defective pixel candidate, and a lower line formed by pixels along the left and right direction of the defective pixel candidate. The average value of pixel values for each line consisting of a left line composed of pixels and a right line composed of pixels along the vertical direction of pixels on the right side of the defective pixel candidate is defined as a line average value. (F) selecting one of the brightest lines for each of the upper, lower, left, and right lines from the average values of the upper, lower, left, and right lines to further limit the evaluation area; (G) calculating a threshold of a pixel value for determining a defective pixel based on an average value of pixel values of a rectangular frame formed by each of the upper, lower, left, and right lines; In A storage medium storing a program for controlling a computer to perform a process of comparing pixel values of all pixels with the threshold value and determining a pixel darker than the threshold value as a defective pixel.