JPH10150571A - Method, device for correcting defective pixel in digital image and recording medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To reflect correction with the pixel values of nearby existent normal pixels, to suppress the sense of discomfort accompanying correction and to decrease the texture deterioration of digital image by performing correcting processing successively from the deflective pixel closest to the normal pixels. SOLUTION: An operator reads the desired image out of an image storage part 1 and instructs the group of defective pixels, discovered visually on a monitor 5 through a mouse 9. A defective pixel specifying processing part 17 sets the evaluation area of 15×15 dots with the instructed defective pixel as a center, calculates a threshold value concerning its peripheral section except for its central section from the average and distribution of pixel values and discriminates the pixels darker than the threshold value as defective pixels among the respective pixels at the central section. A correct pixel value calculating part 29 selects arrangement, minimizing the number of continuous defective pixels for respective row and column directions and performs linear interpolation, while using the values of normal pixels on both the sides of that arrangement. It is sufficient for the operator to instruct the area near the discovered group of defective pixels only once.

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 apparatus for correcting a defective pixel of a digital image for correcting a defective pixel, and a recording medium, and more particularly, to a technique for preventing a deterioration in texture of an original image due to correction of a defective pixel.

[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 labor of the operator can be reduced, and in the digital image after the defective pixel is removed, there is no visually unnatural feeling without an unnatural step around the defective pixel, that is, the texture of the original image can be minimized. Two points of maintenance are called for as technical issues.

The operation of removing a defective pixel includes a plurality of steps including identification of a defective pixel and correction of the identified defective pixel. Various methods for specifying the defective pixel have been put to practical use, but the following is described in descending order of the burden on the operator. In addition,
The following operation is performed by an operator using a mouse or the like while watching a digital image displayed on a display, for example.

(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.

A typical method for correcting the specified defective pixel is as follows.

(A) Method by Pixel Copy For example, an operator visually identifies a defective pixel one by one, and copies a pixel value of a normal pixel located near the defective pixel as a pixel value of the defective pixel. This method is probably the most widely used method of electronic image processing from the first spread to today. However, this method uses the pixel value of a normal pixel adjacent to the identified defective pixel,
If the color tone of the copied normal pixel does not completely match, even if the defective pixel is corrected, a color tone step occurs in that portion, and the texture is reduced. Therefore, the correction of defective pixels by this method has a problem that the burden on the operator is large and a high level of skill is required, and the skill of the operator is clearly reflected in the image quality. Naturally, if the number of defective pixels is large,
It takes a lot of work time.

As compared with the above (a) method using pixel copying, the burden on the operator is small and is not influenced by the skill of the operator, and the working time is short even when the number of defective pixels is large. (B) There is a method of performing correction based on the pixel value of a normal pixel located around a defective pixel. In this method, a defective pixel is specified by any one of the above-described methods (1) to (4), a correction value is calculated based on a pixel value of a normal pixel located on the outer periphery of the defective pixel, and a defect is calculated based on the correction value. This is to replace the pixel value of the pixel. More specifically, with reference to FIG. 14, among the normal pixels NP that exist together with the defective pixel DP (indicated by a cross) in the digital image F, the specified defective pixel DP
Is calculated, and the average value of the pixel values of the normal pixels (indicated by circles) located around the pixel is calculated.
Are uniformly replaced.

[0009]

As described above, the method (b) has the advantage that it does not depend on the skill of the operator, but has the following problem. That is, when the defective pixel DP is composed of only one pixel, it is possible to completely correct the defective pixel DP without deteriorating the texture by this method. However, since the defective pixel DP is generally composed of two or more pixels as shown in FIG. 14, if the pixel values of all the defective pixels DP are replaced with the same pixel value, the texture is deteriorated. There is a problem.

In particular, when a defective pixel DP exists in a portion (called a vignette) where the pixel value (color tone) changes smoothly, replacing all the defective pixels DP with the same pixel value conversely. A large step occurs in the pixel value, and the texture is greatly reduced.

SUMMARY OF THE INVENTION The present invention has been made in view of the above circumstances, and a method of correcting a defective pixel of a digital image capable of minimizing the deterioration of the texture by devising the correction order of the defective pixel. It is an object to provide a method, an apparatus thereof, and a recording medium.

[0012]

The present invention has the following configuration in order to achieve the above object. That is, in the method for correcting defective pixels of a digital image according to the first aspect, when an original image is converted into a digital image by a reading unit, defective pixels occurring in the digital image due to dust and dirt are corrected. The method comprising: (a) identifying defective pixels present in a digital image; and (b)
(C) determining the number of consecutive defective pixels in the row direction for each defective pixel as the continuous number of rows, and determining the number of consecutive defective pixels in the column direction as the continuous number of columns;
(D) obtaining a minimum pixel as the minimum number of consecutive pixels from the number of consecutive rows and the number of consecutive columns, and determining a defective pixel corresponding to the minimum number of consecutive pixels as a minimum defective pixel; Determining a pixel value of the minimum defective pixel as a corrected pixel value based on a pixel value of a normal pixel sandwiching the minimum defective pixel in a direction of the minimum number of consecutive pixels; (F) replacing the defective pixel with the corrected pixel value with a normal pixel;
(G) repeating steps (b) to (f) until all the defective pixels become normal pixels.

The method of correcting defective pixels of a digital image according to claim 2 is the method of correcting defective pixels of digital image according to claim 1, wherein the corrected pixel value in the step (d) is the minimum defective pixel. Are calculated by linear interpolation from the pixel values of two normal pixels sandwiching.

According to a third aspect of the present invention, there is provided an apparatus for correcting defective pixels of a digital image, wherein a defective pixel generated in a digital image due to dust or the like when an original image is converted into a digital image by a reading means. A storage unit for storing the digital image, a display unit for displaying the digital image, and a defective pixel specifying unit for specifying a defective pixel present in the digital image displayed on the display unit. A number-of-consecutive-numbers calculating unit for obtaining the number of defective pixels continuous in the row direction for each defective pixel as the number of continuous rows, and calculating the number of defective pixels continuous in the column direction as the number of continuous columns; Number and the minimum number among the column-direction continuation numbers is determined as the minimum continuation number, and the defective pixel corresponding to the minimum continuation number is defined as the minimum defective pixel The minimum defective pixel calculation means for calculating Te, located in the direction of the minimum consecutive number of said minimum defective pixel,
Based on the pixel value of the normal pixel sandwiching the minimum defective pixel,
A correction pixel value calculation unit that calculates a pixel value of the minimum defective pixel as a correction pixel value, and corrects the digital image by replacing a pixel value of the minimum defect pixel with the correction pixel value; Pixel correction means to be normal pixels, until all the defective pixels become normal pixels, the consecutive number calculation means, the minimum defective pixel calculation means, the correction pixel value calculation means, the pixel correction means And control means for performing repetitive control.

According to a fourth aspect of the present invention, there is provided the digital image defective pixel correcting apparatus, wherein the corrected pixel value calculating means comprises:
The correction pixel value is calculated by linear interpolation from the pixel values of two normal pixels including the minimum defective pixel.

According to a fifth aspect of the present invention, there is provided a recording medium for correcting a defective pixel occurring in a digital image due to dust or the like when an original image is converted into a digital image by a reading unit. A storage medium storing a program, wherein (a) a process for specifying defective pixels present in a digital image, and (b) the number of defective pixels continuous in the row direction for each defective pixel is determined as the number of continuous rows. A process of calculating the number of continuous defective pixels in the column direction as the number of continuous columns; and (c) determining the smallest of the number of continuous rows and the number of continuous columns in the column direction as the minimum number of continuous pixels. (D) determining a defective pixel corresponding to the minimum number of continuous pixels as a minimum defective pixel; and (d) determining a normal pixel located in the direction of the minimum number of continuous minimum defective pixels and sandwiching the minimum defective pixel. A process of obtaining a pixel value of the minimum defective pixel as a corrected pixel value based on the prime value; (e) a process of replacing the pixel value of the minimum defective pixel with the corrected pixel value; And (g) repeating the processes (b) to (f) until all of the defective pixels become normal pixels. It stores a program for controlling a computer.

[0017]

The operation of the first aspect of the invention is as follows. First, among the defective pixels present in the digital image,
A defective pixel existing in the digital image is identified by a method of designating defective pixels one by one, or a method of designating an area to include a defective pixel and then determining based on a set threshold or the like ( Step (a)). For each of the defective pixels specified in this way, the number of defective pixels that are continuously present in the row direction of each pixel is calculated as the “continuation number in the row direction”. The row direction refers to a direction in which the number of rows increases or decreases in the matrix, and is a vertical direction of each pixel. That is, the number of consecutive defective pixels is calculated in the pixel row where the defective pixels exist. Further, for each defective pixel, the number of defective pixels existing continuously in the column direction of each pixel is calculated as the “continuation number in the column direction”.
The column direction is a direction in which the number of columns increases or decreases in the matrix, in other words, a left-right direction. That is, the number of consecutive defective pixels in the pixel row where the defective pixel exists is calculated (step (b)).

After calculating the number of continuations in the row direction and the number of continuations in the column direction for each defective pixel as described above, the smallest one of these is calculated as the "minimum continuation number". That is,
The minimum number of consecutive pixels is the number of consecutive consecutive defective pixels in the row or column direction. Then, a defective pixel corresponding to the minimum number of continuous pixels is obtained as a "minimum defective pixel" (step (c)). The minimum defective pixel has few defective pixels around it, particularly in a direction (row direction or column direction) corresponding to the minimum number of continuous pixels, and conversely, a normal pixel is closest to each other among the defective pixels. Things.

Next, paying attention to the direction corresponding to the minimum number of consecutive minimum defective pixels, this direction (row direction or column direction)
Then, a corrected pixel value is calculated based on the pixel values of the normal pixels sandwiching the minimum defective pixel (step (d)). Since the minimum defective pixel has a small number of defective pixels in the direction corresponding to the minimum number of consecutive pixels and has the shortest distance to the normal pixel, the correction pixel value is calculated by using the pixel value of the normal pixel sandwiching the defective pixel. In addition, the pixel values of surrounding normal pixels can be reflected as much as possible on the corrected pixel values. Then, the pixel value of the minimum defective pixel is replaced with the corrected pixel value (step (e)), and the corrected defective pixel is treated as a normal pixel (step (f)).

After correcting the pixel value of the minimum defective pixel as described above, the process of calculating the “continuation number in the row direction” and the “continuation number in the column direction” of each defective pixel until all pixels become normal pixels ( b) and subsequent steps are repeated (process (g)). Therefore, since the above-described correction processing is sequentially performed from the defective pixel closest to the normal pixel among the defective pixels, each defective pixel is not corrected to the same pixel value. Can be reflected as much as possible. Therefore, it is possible to suppress the occurrence of unnaturalness due to the correction.

According to the second aspect of the present invention, the correction pixel value is calculated by linear interpolation based on the pixel values of two normal pixels sandwiching the minimum defective pixel, so that the correction pixel value exists in the vicinity of the minimum defective pixel. The pixel value of the normal pixel to be reflected can be better reflected. Therefore, it is possible to further suppress a sense of incompatibility with surrounding normal pixels.

The operation of the third aspect of the present invention is as follows. With the digital image stored in the storage means displayed on the display means, defective pixels present in the digital image are specified by the defective pixel specifying means. As this defective pixel specifying means, for example, the operator identifies one defective pixel using a pointing device such as a mouse.
One in which the operator instructs only one place, and the defective pixels are automatically specified based on a threshold or the like for pixels included in a certain area around the one. is there.

The number-of-continuations calculating means calculates, for each defective pixel,
The number of defective pixels that continuously exist in the row direction of each pixel is calculated as “the number of continuous continuations in the row direction”. The row direction refers to a direction in which the number of rows increases or decreases in the matrix, and is a vertical direction of each pixel. Further, for each defective pixel,
The number of defective pixels that exist continuously in the column direction of each pixel is calculated as the “continuation number in the column direction”. The column direction refers to the direction in which the number of columns increases or decreases in the matrix, and is the horizontal direction of each pixel.

The minimum defective pixel calculating means calculates the number of continuous pixels in the row direction and the number of continuous pixels in the column direction for each defective pixel, and then calculates the smallest one as the “minimum number of continuous pixels”.
Then, a defective pixel corresponding to the minimum number of continuous pixels is obtained as a “minimum defective pixel”. The minimum defective pixel is located in a direction (row direction or column direction) corresponding to the periphery thereof, particularly, the minimum continuous number.
The number of defective pixels is small.

The correction pixel value calculation means pays attention to the direction corresponding to the minimum number of consecutive minimum defective pixels, and calculates a correction pixel value based on the pixel values of normal pixels positioned in this direction and sandwiching the minimum defective pixel. . Since the minimum defective pixel has a small number of defective pixels in the direction corresponding to the minimum number of consecutive pixels and has the shortest distance to the normal pixel, the correction pixel value is calculated by using the pixel value of the normal pixel sandwiching the defective pixel. In addition, the pixel values of surrounding normal pixels can be reflected as much as possible on the corrected pixel values. With the corrected pixel value calculated in this way,
The pixel correcting unit replaces the pixel value of the minimum defective pixel and performs correction, and sets the corrected defective pixel as a normal pixel.

After correcting the pixel value of the minimum defective pixel as described above, the control means continues to calculate the continuous number calculating means, the minimum defective pixel calculating means, The pixel value calculation means and the pixel correction means are repeatedly controlled. Therefore, since the above-described correction processing is sequentially performed from the defective pixel closest to the normal pixel among the defective pixels, each defective pixel is not corrected to the same pixel value, and the vicinity of each defective pixel is not corrected. Can be reflected. Therefore, it is possible to suppress the occurrence of unnaturalness due to the correction.

According to the fourth aspect of the present invention, the corrected pixel value calculating means calculates the corrected pixel value by linear interpolation based on the pixel values of two normal pixels sandwiching the minimum defective pixel, thereby minimizing the corrected pixel value. The pixel value of a normal pixel existing near the defective pixel can be better reflected. Therefore, it is possible to further suppress a sense of incompatibility with surrounding normal pixels.

Further, by causing a computer to execute the program stored in the recording medium according to claim 5, first, a defective pixel existing in a digital image is specified. For each defective pixel specified in this way, the number of defective pixels that are continuously present in the row direction of each pixel is calculated as the “continuous number in the row direction”, and the number of defective pixels that are continuously present in the column direction of each pixel is calculated. The number of defective pixels is calculated as the “continuation number in the column direction”.

After the number of continuations in the row direction and the number of continuations in the column direction are calculated for each defective pixel as described above, the smallest one is calculated as the “minimum continuation number”, and Is determined as the “minimum defective pixel”. Next, paying attention to the direction corresponding to the minimum continuous number of the minimum defective pixels, the correction pixel value is calculated based on the pixel values of the normal pixels located in the direction and sandwiching the minimum defective pixel. Then, the pixel value of the minimum defective pixel is replaced with the corrected pixel value, and the corrected defective pixel is treated as a normal pixel.

After correcting the pixel value of the minimum defective pixel as described above, the process of calculating the “continuous number in the row direction” and the “continuous number in the column direction” of each defective pixel until all the pixels become normal pixels is performed. Is repeated. Therefore, since the above-described correction processing is sequentially performed from the defective pixel closest to the normal pixel among the defective pixels, each defective pixel is not corrected to the same pixel value, and the vicinity of each defective pixel is not corrected. Can be reflected. Therefore, it is possible to suppress the occurrence of unnaturalness due to the correction.

[0031]

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 showing a schematic configuration of an image processing apparatus that performs image processing including a method of correcting defective pixels of 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, and 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 selected image is displayed on a monitor 5 corresponding to a display unit via the control unit 3. A desired digital image is selected using the keyboard 7 or the mouse 9. The control unit 3 includes a CPU, a RAM, a ROM, and the like, and performs overall control of each unit described below. The control unit 3 corresponds to a control unit in the present invention. 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. In some cases, the program is read from the drive device 13. In this example, the control unit 3 reads a program from the recording medium M via the driving device 13, and the control unit 3 executes processing described later in detail based on the program. The program reading operation is performed when the device is started up.
It only needs to be executed once. In the following description,
For easy understanding, each processing by the above program is also shown functionally in a block diagram.

The defective pixel specifying section 17 corresponding to the defective pixel specifying means has a function of performing processing for specifying a defective pixel existing in the image memory selected by the operator. Although the details of the defective pixel specifying process will be described later, an outline of the process will be briefly described here. First, the operator recognizes a defective pixel existing in the image memory, and designates, for example, any defective pixel or its vicinity using the mouse 9. An evaluation area is set around the designated pixel, and the evaluation area is further limited based on the pixel values of the normal pixels existing in the evaluation area. Then, a threshold value is set based on the pixel values of the rectangular frame constituting the limited area, the pixel values of all the pixels present in the limited area are compared with the threshold value, and the defective pixel is specified. I have. The position of the defective pixel specified in this manner (for example, a matrix indicating the pixel position) is stored in the defective pixel specifying processing unit 17 as defective pixel information.

To the processing memory 19, a group of pixels existing in the evaluation area set by the defective pixel specifying processing unit 17 is transferred by the control unit 3, and these pixel groups are stored and held. In the pixel group stored here, the pixel value is referred to or rewritten by each unit described later.

As will be described in detail later, when correcting defective pixels, the number of defective pixels continuous in the row direction (vertical direction) and the number of defective pixels continuous in the column direction (horizontal direction) are determined for each defective pixel. , And the correction process is performed first on the defective pixel having the minimum number of consecutive pixels among the defective pixels. When a plurality of defective pixels have the same continuous number, the processing rule storage unit 23 stores in advance rules for determining which defective pixel is to be preferentially processed. These rules can be appropriately set by the operator using the keyboard 7 and the mouse 9. In this embodiment, when there is a defective pixel having the same continuous number in the row direction, the upper defective pixel is prioritized, and when there is a defective pixel having the same continuous number in the column direction, the left side is determined. It is assumed that a rule that gives priority to the defective pixel is set. Further, when sequentially correcting the defective pixel having the minimum number of consecutive pixels, if both the row direction and the column direction are the minimum, it is problematic to interpolate based on the normal pixel in which direction. However, in such a case, a rule is set to alternately switch between the corrected direction of the defective pixel processed before that and the corrected direction. That is, after the correction is performed based on the normal pixels in the row direction, the correction is performed based on the normal pixels in the column direction.

The continuous number calculating section 25 corresponding to the continuous number calculating means of the present invention refers to the processing memory 19 and calculates the number of defective pixels continuous in the column direction (left-right direction) for each defective pixel. In addition to obtaining the number of continuations, the number of defective pixels that continue in the row direction (vertical direction) for each defective pixel is obtained as the number of continuations in the row direction. The minimum defective pixel calculation unit 27 calculates the smallest one of the continuous numbers in each column direction and each continuous direction in each row calculated by the continuous number calculation unit 25 as the minimum continuous number. Further, it has a function of obtaining a defective pixel corresponding to the minimum number of continuous pixels as a minimum defective pixel. At this time, if there are a plurality of minimum defective pixels, the minimum defective pixel is determined according to the rule with reference to the processing rule storage unit 23 described above. Note that the minimum defective pixel calculation section 27 corresponds to the minimum defective pixel calculation means in the present invention.

The correction pixel value calculation unit 29 calculates the pixel value of the minimum defective pixel based on the pixel value of the normal pixel located at the position sandwiching the minimum defective pixel, corresponding to the direction of the minimum number of consecutive minimum defective pixels. Calculate as a value. In this example, the correction pixel value is calculated by linear interpolation (interpolation interpolation) using the pixel values of two normal pixels located at the position sandwiching the minimum defective pixel. Various methods can be used as an interpolation method for calculating the correction pixel value.
Examples include spline interpolation and Lagrange interpolation.
In this embodiment, the correction pixel value is calculated by linear interpolation. However, for example, the correction pixel value may be calculated by the above-described interpolation method according to the position of a defective pixel existing on a digital image. Note that the correction pixel value calculation unit 29 corresponds to a correction pixel value calculation unit in the present invention.

Pixel correction unit 31 corresponding to pixel correction means
Replaces the pixel value of the smallest defective pixel with the calculated correction pixel value. Specifically, the pixel value of the defective pixel corresponding to the smallest defective pixel in the pixel group in the evaluation area stored in the processing memory 19 is replaced. Further, the defective pixel information corresponding to the corrected minimum defective pixel held in the defective pixel specifying processing unit 17 is deleted. The control unit 3 controls each of the above-described components, and until the defective pixel information stored in the defective pixel specifying processing unit 17 disappears, the above-described consecutive number calculation unit 25, the minimum defective pixel calculation unit 27, and the correction pixel. The value calculation unit 29 and the pixel correction unit 31 are repeatedly controlled.

Next, the operation of the above-described apparatus will be described with reference to the flowchart of FIG. 2 and the schematic diagrams of FIGS.

Step S1 (Display Digital Image) The operator selects a desired digital image from the image storage unit 1 using the keyboard 7 or the mouse 9. The selected digital image is displayed on the monitor 5 via the control unit 3. The displayed digital image is, for example, as shown in the schematic diagram of FIG. As shown in FIG. 3, the digital image F includes a normal pixel (group) NP normally converted from the original image and a defective pixel (group) DP (x mark) that was not normally converted due to the influence of dust or dust. Shown). The digital image F has a relatively dark pixel value near the left side thereof (for example, a dark wall or a shadow portion).
There is a normal pixel (group) NP ′ (indicated by /) having the following.

In this example, it is assumed that the digital image F is represented by 19 dots × 19 dots for simplification of description. In FIG. 3, reference numerals L1 to L19 attached along the up-down direction indicate pixel rows constituted by pixel groups existing along the column direction (left-right direction) in which the number of columns of the matrix increases / decreases. The symbols C1 to C19 attached along the left and right directions indicate pixel columns formed by pixel groups existing along the row direction (vertical direction) in which the number of rows of the matrix increases and decreases. In the following description, if it is not clear whether a pixel is a defective pixel or a normal pixel in the process, the pixel is simply referred to as a pixel P. L1 to L1 representing rows
9 and C1 to C19 representing a pixel column 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 (specify defective pixel: corresponding to process (a) and process (a)) The operator selects the digital image F displayed on the monitor 5.
, The defective pixel group DP is recognized based on the relationship with the pixel values of the surrounding pixels, and the pixels P (L9, C10) and the pixels P
(L9, C11), pixel P (L10, C9), pixel P
One of the pixels (L10, C10), the pixel P (L10, C11), the pixel P (L10, C12), the pixel P (L11, C11), and the pixel 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. At this time, it is not always necessary to indicate a defective pixel at this time, but a normal pixel near the defective pixel may be specified at this time.

As shown in FIG. 4, the defective pixel specification processing unit 17 sets a frame of a previously stored area (15 × 15 dots) as an evaluation area ER around the designated pixel PI. The image is superimposed and displayed on the digital image F on the monitor 5. Then, a pixel group included in the area of the pixel group of the digital image F (a pixel group in a rectangle having the pixels P (L3, C3) and the pixels P (L17, C17) as diagonal vertices) Is set as the evaluation area ER, and the evaluation area ER
Is transferred to the processing memory 19. In this case, what is transferred is the right part of the normal pixel group NP ′ having a relatively dark pixel value and the defective pixel group DP.
And a part of the normal pixel group NP.

Next, as shown in FIG.
The pixel having the darkest pixel value from the vicinity of the center among the pixel groups in the evaluation area ER stored in No. 9 is set as the 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. Pixel PI indicated by
Is prioritized and set as a defective pixel candidate PA. Usually, the operator recognizes the defective pixel and indicates it,
No inconvenience can occur with such a setting.

Then, for the pixel group existing in the evaluation area ER, an upper line composed of pixels along the column direction of the pixels above the defective pixel candidate PA, that is, as shown in FIG. From the defective pixel candidate PA to the evaluation area E
Seven upper lines UL1 to UL7 located between the upper sides of R
Is calculated as a line average value. In this case, the upper line UL1 has the smallest average value,
The upper line UL7 has the smallest average value next to the upper line UL1, and the upper lines UL2 to UL6 have the largest average value.

Similarly, a line average value is calculated for the lower lines DL1 to DL7 below the defective pixel candidate PA. 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. Furthermore, left lines LL1 to LL7 and right lines RL1 to RL located on the left and right of the defective pixel candidate PA.
The line average value of L7 is calculated. In this case, the left line L
L7 has the smallest average value, the left line LL1 has the next smallest average value, the left line LL6 has the second smallest value after the left line LL1, and the left lines LL2 to LL5.
Is the largest average value. Further, regarding each right line, a right line RL1, a right line RL2, a right line RL3
The average value increases in the order of to RL7.

The line having the brightest line average value for each direction is selected with reference to the line average values for each of the upper, lower, left, and right directions calculated as described above. 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, 5
One upper line UL2 to UL6 and six lower lines DL2
DL7, four left lines LL2 to LL5, and five right lines RL3 to RL7 have the largest line average values in each direction. In such a case, a defective pixel candidate P
Select the line furthest from A. That is, the upper line UL6 is selected from above, the lower line DL7 from below, the left line LL5 from left, and the right line RL7 from right. By this processing, the area is narrowed down from the evaluation area ER initially set toward the defective pixel candidate PA (see FIG. 6), and a part of the normal pixel group NP ′ existing on the left side of the evaluation area ER is described below. It can be excluded from processing.

Next, a threshold value is calculated from each pixel of the rectangular frame R in FIG. This threshold value is determined by the threshold value T = M−S × C, where M is the average of the pixel values of the rectangular frame R, S is the variance of the pixel values of the rectangular frame R, and C is a constant. 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. It is empirical to multiply the variance S by a constant C, and the constant C is preferably a value of 2 to 3. The reason for using the pixel group of the rectangular frame R excluding the area surrounded by the lines UL6, DL7, LL5, and RL7 to calculate the threshold T as described above, instead of the area surrounded by the lines UL6, DL7, LL5, and RL7, is as follows. by. That is, since the defective pixel DP including the defective pixel candidate PA and the normal pixel NP are mixed in the area defined by each line, the threshold value is determined based on the pixel value of the pixel group existing in the rectangular frame R. Even if T is calculated, the defective pixel DP and the normal pixel NP cannot be accurately determined. Therefore, the threshold value T is calculated based on the average value M of the pixel values of the rectangular frame R including only the normal pixels NP having a pixel value brighter than the defective pixel DP.

The calculated threshold value T is compared with the pixel values of all the pixels present in the rectangular frame R, and all pixels having pixel values darker (smaller) than the threshold value T are determined as defective pixels. That is, in FIG. 6, the pixel values of all the pixels forming the rectangle having the vertices 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.

As described above, the threshold value T is determined based on the average value M of the pixel values of the rectangular frame R including only the normal pixels, and the defect T is determined only for the pixel group within the rectangular frame R further defining the evaluation area ER. 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.

By the above processing, the defective pixel specifying processor 1
7, the following defective pixel information is stored. In addition,
FIG. 7 shows an enlarged digital image F in correspondence with the following symbols so that the specified defective pixel group becomes clear.

Defective pixels DP1 (L9, C10) DP2 (L9, C11) DP3 (L10, C9) DP4 (L10, C10) DP5 (L10, C11) DP6 (L10, C12) DP7 (L11, C11) DP8 (L11) , C12)

Step S3 (Calculate the number of continuations: Step (b)
And the process (b)). The continuation number calculating unit 25 refers to the processing memory 19 and calculates the eight defective pixels DP1 to DP identified by the above-described process.
For each of P8, the number of defective pixels continuous in the row direction including itself is calculated as the continuous number in the row direction, and the number of defective pixels continuous in the column direction including itself is calculated as the continuous number in the column direction. The continuous number in the row direction and the continuous number in the column direction of each defective pixel DP1 to DP8 are as follows.

Defective pixel Continuous number in row direction Continuous number in column direction DP1 (L9, C10) 22 DP2 (L9, C11) 32 DP3 (L10, C9) 14 DP4 (L10, C10) 24 DP5 (L10, C11) ) 34 DP6 (L10, C12) 24 DP7 (L11, C11) 32 DP8 (L11, C12) 22

Step S4 (Determine Minimum Defective Pixel: Corresponding to Process (c) and Process (c)) The minimum defective pixel calculation section 27 calculates the defective pixels DP1 to DP8.
Of the row-direction continuation numbers and the column-direction continuation numbers of. Here, the defective pixel DP3 (L10, C9) whose row direction continuation number is “1” is the minimum, and is defined as the minimum defective pixel DP3. This minimum defective pixel DP3
Represents two normal pixels N among the defective pixels DP1 to DP8.
The distance sandwiched by P is the closest.

Step S5 (Determine Corrected Pixel Value: Corresponding to Process (d) and Process (d)) The corrected pixel value calculator 29 determines whether the defective pixel DP3 (L10, C
The correction pixel value of 9) is calculated. Since the number of consecutive defective pixels DP3 in the row direction is the minimum, the defective pixel DP3 is located in the row direction and
Two normal pixels NP circled in FIG. 7 sandwiching P3
The pixel values of (L11, C9) and NP (L9, C9) are linearly interpolated to calculate corrected pixel values. Since the correction pixel value is calculated using the two normal pixels sandwiching the defective pixel DP3 to be corrected at the shortest distance, the pixel values of the surrounding normal pixels can be reflected as much as possible.

Step S6 (correct the minimum defective pixel:
The processes (e) and (f) and the processes (e) and (f) correspond to each other.
Is replaced with the corrected pixel value calculated by the corrected pixel value calculation unit 29. Specifically, the data of the pixel group in the evaluation area ER stored in the processing memory 19 is updated. Further, the pixel correction unit 31 deletes the defective pixel information corresponding to the defective pixel DP3, which is the minimum defective pixel, held in the defective pixel specifying processing unit 17. Thereafter, the defective pixel DP3 is treated as a normal pixel NP. Therefore, the defective pixel information stored in the defective pixel identification processing unit 17 is as follows, with the information of the defective pixel DP3 being deleted. FIG. 8 schematically shows the digital image F at this time.

Defective pixels DP1 (L9, C10) DP2 (L9, C11) DP4 (L10, C10) DP5 (L10, C11) DP6 (L10, C12) DP7 (L11, C11) DP8 (L11, C12)

When the above processing is completed, the control section 3 refers to the defective pixel information of the defective pixel specifying processing section 17 in step S7 (corresponding to the process (g) and the processing (g)), and this information is lost. The above process is repeated until the above. Since the current seven defective pixel information exists in the defective pixel identification processing unit 17 as described above, the control unit 3
Returns to step S3 (calculation of the number of continuations) and repeatedly executes the processing.

Step S3 (Calculate the number of continuations) The number-of-continuations calculation section 25 calculates the number of continuations in the row direction and the number of continuations in the column direction for each of the seven defective pixels DP1, DP2, DP4 to DP8 as described above. . The number of consecutive defective pixels is as follows.

Defective pixel Row continuous number Column continuous number DP1 (L9, C10) 22 DP2 (L9, C11) 32 DP4 (L10, C10) 23 DP5 (L10, C11) 33 DP6 (L10, C12) ) 23 DP7 (L11, C11) 32 DP8 (L11, C12) 22

Step S4 (Determine the Minimum Defective Pixel) The minimum defective pixel calculation unit 27 calculates the defective pixels DP1, D
The smallest one is determined from the number of continuations in the row direction and the number of continuations in the column direction of P2, DP4 to DP8. Here, the defective pixel D
Of the defective pixels P1, DP2, DP4 to DP8 except for the defective pixel DP5, either the row or column continuation number becomes the minimum continuation number “2”. In such a case, since the minimum defective pixel cannot be determined,
5 refers to the rules stored in the processing rule storage unit 23. As described above, this rule gives priority to the upper defective pixel when there is a defective pixel having the same continuous number in the row direction, and when there is a defective pixel having the same continuous number in the column direction. Defective pixels on the left are prioritized. Therefore, in this case, the defective pixels DP7, DP
Since 8 exists at the top, these are processed preferentially. That is, the minimum defective pixel is replaced with the defective pixels DP7 and DP7.
8 is assumed.

Step S5 (Determine Corrected Pixel Value) The corrected pixel values of the defective pixels DP7 and DP8, which are the minimum defective pixels, are calculated. Since the number of consecutive defective pixels DP7 is the minimum "2" in the column direction, Normal pixels N located in this direction
P (L11, C10) and the normal pixel NP (L11, C1)
A corrected pixel value can be calculated by linearly interpolating the pixel value of 3). However, since the number of consecutive defective pixels DP8 is also “2” in both the row direction and the column direction, there is a problem in which direction the normal pixel is used for interpolation. In such a case, the rules in the processing rule storage unit 23 are referred to. In other words, when both the row direction and the column direction are the minimum, reference is made to the rule of alternately switching to the corrected direction of the defective pixel processed previously. Here, the previously processed defective pixel is the processing in step S5, that is, the defective pixel DP3
That is. Since the defective pixel DP3 is corrected based on the normal pixels in the row direction (vertical direction), the defective pixel DP8 to be corrected this time is corrected based on the normal pixels in the column direction (horizontal direction). That is, similarly to the defective pixel DP7, the correction pixel value is calculated by linearly interpolating the pixel values of the normal pixel NP (L11, C10) and the normal pixel NP (L11, C13) located in this direction.

In step S6, defective pixels DP7, D
The pixel value of P8 is replaced, and the process proceeds to step S7 through step S7.
Return to 3. Defective pixel specifying processor 17 at this time
Is as follows. FIG. 9 schematically illustrates the digital image F at this time. Defective pixel DP1 (L9, C10) DP2 (L9, C11) DP4 (L10, C10) DP5 (L10, C11) DP6 (L10, C12)

The continuous number calculated in step S3 is as follows. Defective pixel number in row direction number in column direction DP1 (L9, C10) 2 2 DP2 (L9, C11) 2 2 DP4 (L10, C10) 2 3 DP5 (L10, C11) 2 3 DP6 (L10, C12) 1 3

In step S4, the defective pixel DP6 having the minimum continuous number "1" in the row direction is set as the minimum defective pixel.

In step S5, the normal pixels NP (L11, L11,
The corrected pixel value is calculated based on the pixel values of the normal pixel NP (L9, C12) and the normal pixel NP (L9, C12), and is replaced in Step S6. At this time, the defective pixel information of the defective pixel specifying processing unit 17 is as follows. The digital image F at this time is schematically shown in FIG. Defective pixel DP1 (L9, C10) DP2 (L9, C11) DP4 (L10, C10) DP5 (L10, C11)

In step S3, the number of continuations is calculated as follows. Defective pixel Continuous number in row direction Continuous number in column direction DP1 (L9, C10) 22 DP2 (L9, C11) 22 DP4 (L10, C10) 22 DP5 (L10, C11) 22

In step S4, the upper defective pixels DP4 and DP5 are set as the minimum defective pixels with reference to the rules stored in the processing rule storage unit 23. Then, in step S5, the respective corrected pixel values of the defective pixels DP4 and DP5 are replaced with the normal pixels NP (L10, C
9) and the normal pixel NP (L10, C12), and is corrected in step S6. The defective pixel information of the defective pixel identification processing unit 17 at this time is as follows. FIG. 11 schematically shows the digital image F at this time. Defective pixel DP1 (L9, C10) DP2 (L9, C11)

Hereinafter, each process is performed in each step as follows.

Step S3 Defective pixel Number of continuations in row direction Number of continuations in column direction DP1 (L9, C10) 1 2 DP2 (L9, C11) 1 2

Steps S4 to S6 When there is a defective pixel having the same number of continuous pixels in the column direction, the minimum defective pixel is determined to be defective pixel DP1 according to the rule of giving priority to the defective pixel on the left side. Normal pixel NP (L10, C
10) and a normal pixel NP (L8, C10) to calculate a correction pixel value to correct the defective pixel DP1. The defective pixel information at this time is as follows. The digital image F at this time is schematically shown in FIG. Defective pixel DP2 (L9, C11)

Step S 3 Defective Pixel Number of Consecutive Rows Number of Consecutive Rows DP 2 (L 9, C 11) 1 1

Steps S4 to S6 The minimum defective pixel is defined as defective pixel DP2. Correction direction (row direction) of defective pixel DP1 corrected before it according to the above rule
Normal pixels NP (L9, C1)
0) and the normal pixel NP (L9, C12) to calculate a correction pixel value, and correct the defective pixel DP2.

At this point, since all the defective pixel information of the defective pixel specifying processing section 17 is deleted, the process branches off and ends in step S7.

As described above, each of the defective pixels DP1 to DP
By performing the correction sequentially from the pixels which are closer to the normal pixels among the pixels 8, the pixel values of the nearby normal pixels can be reflected as much as possible. Therefore, unlike the conventional example shown in FIG. 14, all the defective pixels do not have the same pixel value, and it is possible to make it difficult for a sense of incompatibility with surrounding normal pixels. That is, it is possible to minimize the deterioration of the texture of the digital image.

FIG. 13 shows the order in which the defective pixels DP1 to DP8 are corrected. In other words, it indicates that the corrections have been made in the order shown by the signs A to F. By alternately switching the correction direction between the row direction and the column direction in this way, it is possible to prevent the occurrence of directivity in the corrected pixel value. Therefore, a decrease in texture can be further suppressed. Further, even if a defective pixel exists in a portion where a pixel value (color tone) called a vignette is changed, it is possible to prevent a large step from occurring in the pixel value and a large decrease in texture. it can.

In order to correct a defective pixel, it is necessary to first specify the defective pixel. However, in this embodiment, as described above, the operator only needs to first specify one position near the defective pixel. Effort can be minimized.
Thereby, it is possible to correct the defective pixel while minimizing the deterioration of the texture while minimizing the labor of the operator.

Although the above-described rules are stored in the processing rule storage unit 23 in advance, it is preferable to change the rules according to the digital image.

In the above embodiment, the operator specifies a pixel near the defective pixel in order to specify the defective pixel. However, various methods for specifying the defective pixel can be adopted. For example, (1)-
The defective pixel may be specified by a method such as (3).

In the above-described example, a digital image expressed in black and white gradation has been described as an object for easy understanding. However, a color digital image is generally processed in many cases. . When the color image is to be processed as described above, the pixel value of each color may be used when calculating the correction pixel value in step S5. That is, when a color digital image is represented by three colors of R, G, and B, for example, interpolation may be performed in the order of R, G, and B to obtain corrected pixel values.

Steps S2 to S7 shown in the flowchart of FIG. 2 correspond to the program of the defective pixel correction 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.

[0084]

As is apparent from the above description, according to the method of the present invention, the correction process is performed sequentially from the defective pixel closest to the normal pixel among the defective pixels. The pixel value of a normal pixel existing near each defective pixel can be reflected as much as possible. Therefore, it is possible to suppress the occurrence of uncomfortable feeling by correcting the defective pixel. As a result, it is possible to minimize a decrease in the texture of the digital image.

According to the second aspect of the present invention, the pixel value of a normal pixel existing near the minimum defective pixel can be better reflected by performing correction using linear interpolation. It is possible to further suppress a sense of incompatibility with the normal pixel. Therefore,
The deterioration of the texture of the digital image can be further suppressed.

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

According to the apparatus of the present invention, the method of the present invention 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 process of correcting a defective pixel.

FIG. 8 is a schematic diagram showing a process of correcting a defective pixel.

FIG. 9 is a schematic view showing a process of correcting a defective pixel.

FIG. 10 is a schematic diagram illustrating a process of correcting a defective pixel.

FIG. 11 is a schematic view showing a process of correcting a defective pixel.

FIG. 12 is a schematic diagram showing a process of correcting a defective pixel.

FIG. 13 is a schematic diagram showing the order of correcting defective pixels.

FIG. 14 is an explanatory diagram of a conventional example.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Image storage part (storage means) 3 ... Control part (control means) 5 ... Monitor (display means) 11 ... Storage device 13 ... Drive device M ... Recording medium 17 ... Defective pixel specification processing part (defective pixel specification means) 25 … Continuous number calculating unit (continuous number calculating unit) 27… Minimum defective pixel calculating unit (Minimum defective pixel calculating unit) 29… Corrected pixel value calculating unit (Corrected pixel value calculating unit) 31… Pixel correcting unit (Pixel correcting unit) F … Digital image NP… Normal pixel DP… Defective pixel

Claims (5)

[Claims] 1. A method for correcting a defective pixel occurring in a digital image due to dust or dust when an original image is converted into a digital image by a reading means, comprising: (a) presenting in the digital image; (B) determining the number of defective pixels that continue in the row direction for each defective pixel as the number of continuations in the row direction and determining the number of defective pixels that continue in the column direction as the number of continuations in the column direction And (c) determining the smallest one among the number of continuations in each row direction and the number of continuations in each column direction as the minimum number of continuations,
Determining a defective pixel corresponding to the minimum number of consecutive pixels as a minimum defective pixel; and (d) based on a pixel value of a normal pixel located in the direction of the minimum number of consecutive consecutive minimum defective pixels. Determining the pixel value of the minimum defective pixel as a corrected pixel value; (e) replacing the pixel value of the minimum defective pixel with the corrected pixel value; and (f) replacing the defective pixel with the corrected pixel value. Converting a pixel into a normal pixel; and (g) repeating the steps (b) to (f) until all of the defective pixels become normal pixels. Defective pixel correction method. 2. The method according to claim 1, wherein the corrected pixel value in the step (d) is:
A method of correcting a defective pixel of a digital image, wherein the defective pixel is calculated by linear interpolation from pixel values of two normal pixels sandwiching the minimum defective pixel. 3. An apparatus for correcting a defective pixel caused in a digital image due to dust or dust when an original image is converted into a digital image by a reading unit, wherein: a storage unit for storing the digital image; Display means for displaying the digital image; defective pixel specifying means for specifying defective pixels present in the digital image displayed on the display means; number of defective pixels continuous in the row direction for each defective pixel And the number of consecutive defective pixels in the column direction as the number of consecutive columns, and a continuous number calculating means for determining the number of consecutive pixels in the column direction as the number of consecutive columns, A minimum defective pixel calculating unit that obtains a defective pixel corresponding to the minimum continuous number as a minimum defective pixel while obtaining the minimum defective pixel; A correction pixel value calculation means for calculating a pixel value of the minimum defective pixel as a correction pixel value, based on a pixel value of a normal pixel sandwiching the minimum defect pixel, in the direction of the minimum number of consecutive pixels, Pixel correction means for substituting the corrected pixel value for the digital image and correcting the digital image to make the minimum defective pixel a normal pixel; and calculating the number of continuations until all of the defective pixels become normal pixels. Means for correcting a defective pixel of a digital image, comprising: means, a minimum defective pixel calculating means, a corrected pixel value calculating means, and a control means for repeatedly controlling the pixel correcting means. 4. The apparatus for correcting defective pixels of a digital image according to claim 3, wherein the corrected pixel value calculating means calculates the corrected pixel value by linear interpolation from pixel values of two normal pixels including the minimum defective pixel. An apparatus for correcting a defective pixel of a digital image, wherein the correction is performed. 5. A recording medium storing a program for correcting a defective pixel occurring in a digital image due to dust or dust when an original image is converted into a digital image by a reading means, (A) a process of identifying defective pixels present in the digital image; and (b) determining the number of defective pixels continuous in the row direction for each defective pixel as the number of continuous defective pixels in the row direction. (C) calculating the smallest number among the row-number continuation numbers and the column-direction continuation numbers as the minimum continuation number;
(D) a process of determining a defective pixel corresponding to the minimum number of consecutive pixels as a minimum defective pixel; and (d) based on a pixel value of a normal pixel sandwiching the minimum defective pixel and located in a direction of the minimum number of consecutive consecutive minimum defective pixels. (E) replacing the pixel value of the minimum defective pixel with the corrected pixel value; and (f) replacing the pixel value of the minimum defective pixel with the corrected pixel value. And (g) a process of repeatedly performing the processes (b) to (f) until all of the defective pixels become normal pixels. Recording medium that stores the program of.