JP2008198207A - Image processor and image processing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To effectively reduce noise, without deteriorating important information such as edge information on an object. <P>SOLUTION: This image processor has a fixed pattern detecting means for detecting a predetermined fixed pattern by using pixel data being a processing object and data of its peripheral pixel, and a fixed pattern correcting means for performing correction processing only to a pixel of detecting the fixed pattern by the fixed pattern detecting means. The fixed pattern correcting means determines a signal level of a noticeable pixel by applying a predetermined arithmetic operation to the signal level of the noticeable pixel, based on a value of multiplying a difference value between the noticeable pixel and a signal level of an adjacent pixel larger in a difference in the signal level by a predetermined factor, among signal levels of the noticeable pixel and two adjacent pixel adjacent to both next sides of the noticeable pixel. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to an image processing apparatus and an image processing method that can reduce fringe noise that cannot be corrected by gain adjustment between channels when a captured image obtained by reading a subject image as a plurality of channel outputs is subjected to signal processing.

  2. Description of the Related Art Conventionally, there is an image sensor having a plurality of channel outputs such as an all-pixel readout type CCD (abbreviation of charge coupled device). For example, a two-channel readout type CCD has two horizontal transfer registers in order to lower the driving frequency, and simultaneously transfers signal charges of odd lines and signal charges of even lines using separate horizontal transfer registers, Signal charges for two lines are read out within one horizontal transfer period.

  In a CCD having a plurality of channel outputs, when a gain variation occurs between channels, the variation becomes a level difference of output signals between channels and appears as fringe noise in an image. Therefore, in order to correct the gain variation between channels, as described in JP-A-10-276976, the output of each channel is sampled, and the average value is compared. The gain of the output is adjusted to match the gain between the channels. However, when different types of shading occur between a plurality of channels, variations between channels cannot be corrected, and as a result, fringe noise may remain in the image.

  As another prior art, Japanese Patent Laid-Open No. 62-296668 discloses a pixel of interest when correcting the pixel of interest signal based on pixel signals located before, after, and after the pixel signal of interest in the image signal. An image correction circuit is disclosed that performs control so that correction is not performed when the difference in density between a signal and pixel signals located in the front, rear, left, and right is within a predetermined range, and outputs correction values at other times. .

  Japanese Patent Laid-Open No. 4-239886 discloses a pixel value group that outputs pixel values of a pixel of interest and a neighboring pixel group that is two-dimensionally adjacent to the pixel of interest from an image signal composed of a plurality of scanning lines. A noise determination unit that determines whether the pixel of interest includes noise by detecting whether the pixel value of the pixel of interest is greater than a predetermined threshold with respect to the adjacent pixel value group; There is disclosed an image noise device having pixel value selection means for selecting and outputting any one of the pixel values of the target pixel and the neighboring pixel group based on the determination result by the means.

  Further, JP-A-9-218940 discloses a screen processing apparatus for interpolating a defective image in an image, an image input means for inputting an image in which a plurality of effective image areas composed of a plurality of pixels are scattered, and a defective image And an interpolating unit for interpolating the defective image with an image obtained from a peripheral region including at least one effective image region around the effective image region in which the defective image exists An image processing apparatus including the above is disclosed. Thus, a good output image can be obtained by interpolating the defective image in an image in which the defective image exists across a plurality of pixels.

  Furthermore, Japanese Patent Laid-Open No. 11-308625 discloses an image pickup apparatus including a camera signal processing circuit that forms a video signal from a digitally converted input signal, and the camera signal processing circuit detects an edge of the input signal. An edge detection unit for detection, a luminance signal processing unit for extracting luminance information of the input signal, and a color difference signal processing unit for extracting color information of the input signal are provided, and 3 continuous in the horizontal direction of the image The signal amounts D1, D2, and D3 of each of the pixels and the predetermined set value A are | D1-D2 |> A and | D1-D3 |> A or | D1-D3 |> A and | D2-D3. An imaging device is disclosed in which a color difference signal processing unit suppresses a color difference signal when a condition satisfying |> A is satisfied by an edge detection unit.

However, in any of the above-mentioned JP-A-62-296668, JP-A-4-239886, JP-A-9-218940, and JP-A-11-308625, an imaging device having a plurality of channel outputs In the case of performing signal processing on images of a plurality of channels, no means is described for solving the problem that fringe noise remains in an image that cannot be corrected by gain adjustment between channels.
JP 10-276976 A (page 1-2, FIG. 1) JP 62-296668 A (page 1-2, Fig. 1) JP-A-4-39886 (page 1-3, FIG. 1) Japanese Patent Laid-Open No. 9-218940 (page 1-3, FIG. 1) Japanese Patent Laid-Open No. 11-308625 (page 1-3, FIG. 1)

  As a method for correcting fringe noise described in the above-mentioned Japanese Patent Application Laid-Open No. 10-276976, there is a method of correcting the entire image by performing a smoothing process. However, necessary information such as the edge of the subject is also blurred. As a result, the image quality deteriorates.

  In view of the problems described above, the present invention does not degrade necessary information such as the edge of a subject, and does not completely correct correction by gain adjustment. An object of the present invention is to provide an image processing apparatus and an image processing method capable of reducing only fringe noise.

  An image processing apparatus according to the present invention is a fixed pattern that detects a predetermined fixed pattern using pixel data to be processed and data of surrounding pixels in an image processing apparatus that performs signal processing on input image data. Detection means, and fixed pattern correction means for performing correction processing only on pixels for which a fixed pattern has been detected by the fixed pattern detection means, wherein the fixed pattern correction means determines the signal level of the target pixel A value obtained by multiplying a difference value between a signal level of an adjacent pixel having a larger signal level difference from the target pixel by a predetermined coefficient among signal levels of two adjacent pixels adjacent to both sides of the pixel and the target pixel. Based on the above, it is obtained by performing a predetermined calculation on the signal level of the target pixel.

  The image processing method according to the present invention is a step of performing signal processing on input image data, a step for detecting a predetermined fixed pattern using pixel data to be processed and data of surrounding pixels. Performing a correction process on the pixel in which the predetermined fixed pattern is detected in the step, and the step of performing the correction process sets the signal level of the target pixel to the target pixel and the adjacent pixel of the target pixel. Of the pixel of interest based on a value obtained by multiplying a difference value between the signal level of the adjacent pixel having a larger signal level difference from the pixel of interest among the signal levels of two adjacent pixels adjacent to the pixel by a predetermined coefficient The signal level is obtained by performing a predetermined calculation on the signal level.

  According to the present invention, fixed patterns such as vertical stripe noise, horizontal stripe noise, and oblique noise are detected, and correction processing such as gain adjustment and smoothing processing is performed only on the portion where the fixed pattern is detected. Thus, noise can be effectively reduced without degrading important information such as edge information of the subject.

  Embodiments of the present invention will be described below with reference to the drawings.

  1 to 12 relate to a first embodiment of the present invention, FIG. 1 is a block diagram showing a basic configuration of an image processing apparatus, and FIG. 2 is a fringe generated without correcting variations between channels. FIG. 3 is a diagram showing the state of noise, FIG. 3 is a diagram showing the signal level between AB in FIG. 2, FIG. 4 is a flowchart showing the processing flow of the fixed pattern detection unit in FIG. 1, and FIG. FIG. 6 and FIG. 7 are diagrams showing examples of conditions not detected in processing step S3 of FIG. 4, and FIG. 8 is a diagram showing detection of fringe noise in processing step S10 of FIG. FIG. 9 is an explanatory diagram for explaining an example of the condition for performing the detection, FIG. 9 is an explanatory diagram for explaining an example of the condition for not detecting the fringe noise in the processing step S10 of FIG. 4, and FIG. FIG. 11 shows a fringe noise correction unit in FIG. Flowchart showing a processing flow, FIG. 12 is a diagram showing a processing result by the apparatus or method of the present embodiment.

  In the present embodiment, an image processing apparatus that performs signal processing for effectively removing vertical stripe noise is shown. Vertical stripe noise is, for example, fringe noise generated without being able to correct variations between channels. Here, consider the case of vertical stripe noise every other dot. When the captured image is enlarged, vertical stripe noise may occur every other dot or more, but in this case, the detection condition can be adjusted to the stripe noise, and the basic idea remains the same. . In the present embodiment, vertical stripe noise every other dot will be described in order to simplify the description.

Before describing the configuration of the image processing apparatus according to the present invention with reference to FIG. 1, vertical stripe noise will be described with reference to FIGS.
FIG. 2 shows a state of vertical stripe noise (fixed pattern) of an image displayed on a monitor screen (an octagonal shape in the figure). The signal level of the portion where the vertical stripe noise is generated (between AB in FIG. 2) is low when the image of a uniform subject such as a white chart is picked up with a pixel having a high signal level every other dot as shown in FIG. The pixels are arranged alternately.

  When the gain variation of the signal level is corrected using a smoothing filter or the like as in the past, the portion where the fringe noise is not generated is also smoothed. For example, the minute edge change of the subject is lost. As a result, the image quality deteriorates.

Also, even in the image portion where fringe noise is generated, if there is an edge that is not fringe noise, for example, when the subject is a resolution chart etc., the edge that changes rapidly with a fine bitch is blurred and deteriorated. There was a case.

  In view of such a point, the present invention provides an image processing apparatus that can detect only fringe noise and correct it.

  That is, the image processing apparatus according to the present invention detects a predetermined fixed pattern using pixel data to be processed and data of surrounding pixels in an image processing apparatus that performs signal processing on input image data. And a fixed pattern correction unit that performs correction processing only on the pixels for which the fixed pattern is detected by the fixed pattern detection unit.

  The image processing apparatus of the present invention shown in FIG. 1 adjusts the gain of two signals of an odd line and an even line obtained from, for example, a two-channel readout type image sensor, and corrects variations between channels at that time. In FIG. 1, after the gain adjustment of the two signals of the odd line and the even line between the channels, the two channel signals after the gain adjustment are synthesized. A configuration for correcting the fringe noise of an image signal is shown.

  The image processing apparatus shown in FIG. 1 includes a fixed pattern detection unit 1 that detects a fixed pattern for each pixel using pixel data to be processed from the input image data and data of surrounding pixels, and an input image. A correction amount calculation unit 2 that calculates a correction amount for each pixel from data, and a fringe noise correction unit that performs correction based on the correction amount calculated by the correction amount calculation unit 2 only for pixels in which a fixed pattern is detected 3. The fixed pattern detector 1 constitutes a fixed pattern detector, and the correction amount calculator 2 and the fringe noise corrector 3 constitute a fixed pattern corrector.

Next, the operation of the fixed pattern detection unit 1 of FIG. 1 will be described using the flowchart of FIG.
As shown in S1 to S5 in FIG. 4, the input image is processed from data A that is not delayed, data B that is delayed by 1 dot (step S1), and data C that is delayed by 2 dots (step S2). The pixel data (corresponding to B) is compared with the adjacent pixel data to determine whether it is a convex type or a concave type (step S3). In step S3, as shown in FIG. 5, the pixel at position B has a higher signal level than both adjacent pixels, and if the signal level difference between the adjacent pixels is within 10%, it is determined to be convex. Although not shown, conversely, when both signal levels are low and the signal level difference between the adjacent pixels is within 10%, it is determined to be concave and 1 is substituted into the variable “Flag” (step S4). As shown in FIG. 6, when the difference in signal level with the neighbor is 10% or more, or when the change is stepwise as shown in FIG. 7, 0 is substituted into the variable “Flag” (step S5). .

  In the present embodiment, for simplification of explanation, the signal level difference between adjacent pixels generated by vertical stripe noise is assumed to be within 10% of the signal level. Since it varies depending on the characteristics and the method of correcting the variation between channels, it may be determined by appropriately changing in consideration of, for example, within 2, 4, 8, 16% of the signal level, or 2-8. %, 4 to 16%, etc., are not limited to “within 10% of the signal level” of the conditions described in the present embodiment.

  Next, as shown in S6 to S12 of FIG. 4, a flag that is not delayed, a flag that is delayed by 1 dot (step S6), a flag that is delayed by 2 dots (step S7), a flag that is delayed by 3 dots (step S8) Whether the convex type or the concave type is continuous in the adjacent pixels is determined from the flag D that has been delayed by 4 dots (step S9). In step S10, when the flag of the pixel corresponding to the position of c in FIG. 8 is 1, the flags of the pixels i, b, and c are all 1, or the flags of the pixels c, 2, and e are both 1, or If Flags of B, C, and D are all 1, it is determined that a fixed pattern of vertical stripes has been detected, and 1 is assigned to the variable “Shima” (step S11). In other cases, assuming that a fixed pattern of vertical stripes has not been detected, 0 is substituted into the variable “Shima” (step S12).

  In the case of FIG. 8, the flags of the pixels C, D, and H are all 1, and the flags of the pixels B, C, and D are both 1. Therefore, 1 is assigned to the variable “Shima”. For example, in the case of FIG. 9, even if the variable “Flag” of any pixel is 1, detection is not performed as vertical stripe noise.

  According to the processing method of FIG. 4 described above, it is possible to detect only vertical stripe noise that occurs every other dot. The detection condition of the vertical stripe noise is not limited to the above method. For example, when the number of memories is increased and four convex shapes or concave shapes are continuous, or when the memory is reduced, convex shapes or concave shapes are used. For example, it may be determined that there is vertical stripe noise when only one exists.

Next, the operation of the correction amount calculation unit 2 in FIG. 1 will be described using the flowchart in FIG.
The image data input to the correction amount calculation unit 2 includes data A that is not delayed, data B that is delayed by 1 dot (step S21), and data C that is delayed by 2 dots (step S22). BC is calculated (steps S23 and S24). In step S25, the larger value of | B−A | and | B−C | is selected (step S25), and assigned to the variable “H” (steps S26 and S27). Thereafter, the variable “H” is halved and output as a correction value (step S28).

  By setting the correction value to ½ of the larger signal level difference with the adjacent pixel, for example, when capturing a uniform subject such as a white chart, the fringe noise correction unit 3 at the rear stage of FIG. The corrected signal level becomes the same signal level as that of the adjacent pixel as shown in FIG. 12, and vertical stripe noise is corrected.

Next, the operation of the fringe noise correction unit 3 of FIG. 1 will be described using the flowchart of FIG.
It is determined whether or not the variable “Shima” of the image input from the fixed pattern detection unit 1 is 1 (step S31), and for the pixel with the variable “Shima” = 1, the input image data and the correction amount calculation unit 2 When the correction value H / 2 is used to determine the convex pattern in the fixed pattern processing step S3 of FIG. 4, (image data) − (correction value H / 2), and when the concave pattern is determined. , (Image data) + (correction value H / 2) is output (step S32).

  In step S31, the input image data is output as it is for the pixels whose variable “Shima” = 0 (step S33).

  As described above, according to the image processing apparatus of the present embodiment, as shown in FIG. 12, a portion having a large signal level difference from the adjacent pixel, such as a portion where an edge of a subject exists, or the like The signal level difference between the adjacent pixels, such as the part where no noise is generated, is not corrected, and the signal level of only the part where the vertical stripe noise is generated is not corrected. Since correction is performed to reduce the difference from the signal level, it is possible to efficiently reduce only vertical stripe noise without degrading the subject edge information, etc., compared to the conventional method using a smoothing filter. It becomes.

  In the present embodiment, an image processing apparatus applicable to vertical stripe noise has been described. However, even in the case of horizontal stripe noise, if the 1-dot delay process in FIGS. 4 and 10 is changed to a 1-line delay process, the same applies. The image processing apparatus can be applied to horizontal stripe noise. In addition, in the present embodiment, stripe fringe noise such as beat noise can be applied to an image processing apparatus having exactly the same configuration because stripe detection is performed using only information in the horizontal direction or vertical direction. It is.

FIG. 13 is a block diagram showing a configuration of an image processing apparatus according to the second embodiment of the present invention.
As shown in FIG. 13, the image processing apparatus according to the present embodiment includes a one-line memory 11a that delays input image data by one line, and a one-line memory 11b that further delays the output of the one-line memory 11a by one line. A subtractor 12a for subtracting the input image data and the output of the 1-line memory 11a, a subtractor 12b for subtracting the outputs of the 1-line memory 11a and the 1-line memory 11b, outputs of the subtractors 12a and 12b, and a 1-line memory. 11a, the condition detection unit 13 for detecting a pixel whose signal level is higher or lower than both adjacent pixels, the one-line memory 14a for delaying the output of the condition detection unit 13 by one line, and the output of the one-line memory 14a. Further, the 1-line memory 14b for delaying one line and the output of the 1-line memory 14b for further delaying 1 line A one-line memory 14d that further delays the output of the in-memory 14c and the one-line memory 14c by one line; an output of the condition detection unit 13; and a horizontal stripe noise detection unit 15 that detects horizontal stripe noise from the outputs of the one-line memories 14a to 14d; The correction value calculation unit 16 that calculates a correction value from the outputs of the subtraction units 12a and 12b, the output of the horizontal stripe noise detection unit 15, the output of the correction value calculation unit 16, and the horizontal stripe noise from the outputs of the one-line memories 11a and 14b. A horizontal stripe noise correction unit 17 for correction is provided.

Next, the operation of FIG. 13 will be described.
The image processing apparatus according to the present embodiment is an image processing apparatus capable of correcting horizontal stripe noise that operates in the same manner as in the first embodiment.

  First, in the input image data, the difference between the signal levels of the upper and lower pixels, that is, the input image data and the output of the 1-line memory 11b is calculated with the output of the 1-line memory 11a as the central pixel. The subtractor 12a calculates (output of 1 line memory 11a)-(input image data), and the subtractor 12b calculates (output of 1 line memory 11a)-(output of 1 line memory 11b).

  The calculated signal level difference is input to the condition detection unit 13. The condition detection unit 13 determines from the difference between these signal levels and the signal level of the center pixel whether the signal level of the center pixel is higher or lower than the signal levels of the upper and lower pixels. When the outputs of the subtracting units 12a and 12b are both positive values and within 10% of the signal level of the central pixel, it is determined as a convex type and +1 is output. When the outputs of the subtracting units 12a and 12b are both negative values and within 10% of the signal level of the central pixel, it is determined to be concave and -1 is output.

  The horizontal stripe noise detection unit 15 detects horizontal stripe noise from the output of the condition detection unit 13 and the outputs of the one-line memories 14a to 14d. The detection method is basically the same as that of the first embodiment. In S6 to S9 in FIG. 4, horizontal line noise can be detected by performing one line delay instead of one dot delay. It is. Including the output of the one-line memory 14b, the “condition detection unit 13, the one-line memory 14a, the one-line memory 14b”, the “one-line memory 14a, the one-line memory 14b, the one-line memory 14c”, the “one-line memory 14b, When the three patterns of the outputs of the 1-line memory 14c and the 1-line memory 14d apply to “+1, −1, +1” or “−1, +1, −1”, it is determined that the pixel has horizontal stripe noise. Note that, similarly to the first embodiment, the horizontal stripe noise detection condition is not limited to the above-described condition.

  As in the first embodiment, the correction value calculation unit 16 selects the larger value from the outputs of the subtraction units 12a and 12b, halves the value, and outputs it as a correction value.

  When the output of the 1-line memory 14b is +1 with respect to the pixel determined to have the horizontal stripe noise by the horizontal stripe noise detection unit 15, the horizontal stripe noise correction unit 17 uses the original image data output from the 1-line memory 11a. The output of the correction value calculation unit 16 is subtracted. When the output of the 1-line memory 14b is -1, the output of the correction value calculation unit 16 is added to the original image data output from the 1-line memory 11a.

  As described above, as in the first embodiment, it is possible to efficiently reduce only the horizontal stripe noise without degrading the subject edge information and the like. In the present embodiment, the memory for adjusting the timing of the arithmetic processing is not particularly shown, but using it as necessary does not depart from the spirit of the present invention.

  14 and 15 relate to the third embodiment of the present invention, FIG. 14 is a block diagram illustrating the configuration of the imaging device 20, and FIG. 15 is vertical stripe noise included in the signal processing unit 25 of the imaging device 20. 3 is a block diagram illustrating a configuration of a processing unit 250. FIG.

  As shown in FIG. 14, the imaging apparatus 20 of the present embodiment includes a CCD 21, a process circuit 22, an A / D converter 23, a gain adjustment circuit 24 that corrects variations between channels of the CCD 21, and vertical stripe noise processing. The signal processing circuit 25 having the section 250, the enlargement circuit 26, and the D / A converter 27 are provided. The CCD 21 is a two-channel readout type CCD, and the processing system from the CCD 21 to the gain adjustment circuit 24 has a two-system circuit configuration having two signal lines of odd dots and even dots, but is simplified in FIG. For the sake of simplicity, the CCD 21, the process circuit 22, the A / D converter 23, and the gain adjustment circuit 24 are each represented by only one block.

  As shown in FIG. 15, the signal processing circuit 25 is provided with a vertical stripe noise processing section 250 for correcting vertical stripe noise that has been generated by the previous gain adjustment circuit 24 without being able to correct variations between channels. Note that the enlargement circuit 26 performs electronic enlargement processing on a digital video signal made into one system after vertical stripe noise processing at an enlargement ratio corresponding to the size of an image displayed on a monitor (not shown).

  Next, the configuration of the vertical stripe noise processing unit 250 provided in the signal processing circuit 25 of the imaging device 20 will be described. As shown in FIG. 15, the vertical stripe noise processing unit 250 includes a 1-dot delay memory 251 a that delays input image data by 1 dot, and a 1-dot delay memory 251 b that further delays the output of the 1-dot delay memory 251 a by 1 dot. The subtractor 252a for subtracting the input image data and the output of the 1-dot delay memory 251a, the subtractor 252b for subtracting the outputs of the 1-dot delay memory 251a and the 1-dot delay memory 251b, and the subtractors 252a and 252b A condition detection unit 253 that detects a pixel whose signal level is higher or lower than both adjacent pixels from the output of the memory 251a, a 1-dot delay memory 254a that delays the output of the condition detection unit 253 by 1 dot, and a 1-dot delay memory 254a A one-dot delay memory 254b that further delays the output of A one-dot delay memory 254c that further delays the output of the one-dot delay memory 254b by one dot, a one-dot delay memory 254d that further delays the output of the one-dot delay memory 254c by one dot, an output of the condition detection unit 253, and a one-dot delay A vertical stripe noise detection unit 255 that detects vertical stripe noise from the outputs of the memories 254a to 254d, and an output of the vertical stripe noise detection unit 255 and a vertical stripe noise correction unit 256 that corrects vertical stripe noise from the outputs of the one-dot delay memories 251a and 254b. Configured.

Next, operations of the imaging device 20 in FIG. 14 and the vertical stripe noise processing unit 250 in FIG. 15 will be described.
In the imaging device 20, a video signal visualized by a CCD 21, a process circuit 22 provided with a CCD driver, a preamplifier, and the like is converted from an analog signal to a digital signal by an A / D converter 23. Variations between channels of the CCD 21 are corrected. The signal processing circuit 25 is provided with a vertical stripe noise processing unit 250, which corrects vertical stripe noise caused by shading of the same channel that could not be corrected by the gain adjustment circuit 24. Thereafter, the image is enlarged by the enlargement circuit 26, and the video signal is converted into an analog signal by the D / A converter 27 and output, or directly output as a digital signal.

  In the vertical stripe noise processing unit 250, the input image data and the one-dot delay memory are input to the left and right pixels, that is, the output of the one-dot delay memory 251a, with the output of the one-dot delay memory 251a as the central pixel. The difference of each signal level from the output of 251b is calculated. The subtractor 252a calculates (output of 1 dot delay memory 251a)-(input image data), and the subtractor 252b calculates (output of 1 dot delay memory 251a)-(output of 1 dot delay memory 251b).

  The calculated signal level difference is input to the condition detection unit 253. In the condition detection unit 253, it is determined from the difference between these signal levels and the signal level of the center pixel whether the signal level of the center pixel is higher or lower than the signal levels of the left and right pixels. When both the outputs of the subtracting units 252a and 252b are positive values and are within 10% of the signal level of the central pixel, it is determined as a convex type and +1 is output. When the outputs of the subtracting units 252a and 252b are both negative values and within 10% of the signal level of the central pixel, it is determined to be concave and -1 is output.

  The vertical stripe noise detection unit 255 detects vertical stripe noise from the output of the condition detection unit 253 and the outputs of the one-dot delay memories 254a to 254d. “Condition detection unit 253, 1 dot delay memory 254a, 1 dot delay memory 254b”, “1 dot delay memory 254a, 1 dot delay memory 254b, 1 dot delay memory 254c”, including the output of 1 dot delay memory 254b, Vertical stripes when the three patterns of output of “1 dot delay memory 254b, 1 dot delay memory 254c, 1 dot delay memory 254d” apply to “+1, −1, +1” or “−1, +1, −1” Judge as a pixel with noise. As in the first and second embodiments, the vertical stripe noise detection conditions are not limited to the above-described conditions.

  When the output of the 1-dot delay memory 254b is +1 with respect to the pixel determined to have vertical stripe noise by the vertical-stripe noise detection unit 255, the vertical stripe noise correction unit 256 outputs the original image (original image). 5% of the signal level of (data) is subtracted. When the output of the 1-dot delay memory 254b is -1, 5% of the signal level of the output (original image data) of the 1-dot delay memory 254a is added.

  As described above, as in the first and second embodiments, it is possible to efficiently reduce only the vertical stripe noise without deteriorating the edge information of the subject. In this embodiment, the memory for adjusting the timing of the arithmetic processing is not particularly shown. However, as in the second embodiment, use as necessary deviates from the gist of the present invention. is not.

  In the present invention, as a fringe noise correction method, a method mainly using gain adjustment has been described. However, smoothing processing using a spatial filter such as 3 × 3, 1 × 3, or 5 × 5 may be performed. .

1 is a block diagram showing a basic configuration of an image processing apparatus according to a first embodiment of the present invention. The figure which shows the mode of the stripe noise which generate | occur | produced without fully correcting the dispersion | variation between channels in the image projected on a monitor screen. The figure showing the signal level between AB of FIG. The flowchart which shows the processing flow of the fixed pattern detection part of FIG. The figure which shows the example of the conditions detected by process step S3 of FIG. The figure which shows the example of the conditions which are not detected by process step S3 of FIG. The figure which shows the example of the conditions which are not detected by process step S3 of FIG. Explanatory drawing for demonstrating the example of the conditions which detect fringe noise by process step S10 of FIG. Explanatory drawing for demonstrating the example of the conditions which do not detect fringe noise by process step S10 of FIG. The flowchart which shows the processing flow of the correction amount calculation part of FIG. The flowchart which shows the processing flow of the fringe noise correction | amendment part of FIG. The figure which shows the processing result by the apparatus or method of this Embodiment. The block diagram which shows the structure of the image processing apparatus which concerns on the 2nd Embodiment of this invention. The block diagram which shows the structure of the imaging device based on the 3rd Embodiment of this invention. The block diagram which shows the structure of the vertical stripe noise process part contained in the signal processing circuit of the imaging device of FIG.

Explanation of symbols

1... Fixed pattern detection unit (fixed pattern detection means)
2 ... Correction amount calculation unit (fixed pattern correction means)
3 ... fringe noise correction unit (fixed pattern correction means)

Claims (8)

In an image processing apparatus that performs signal processing on input image data,
Fixed pattern detecting means for detecting a predetermined fixed pattern using pixel data to be processed and data of surrounding pixels; and
Fixed pattern correction means for performing correction processing only on pixels in which a fixed pattern is detected by the fixed pattern detection means;
With
The fixed pattern correcting means sets the signal level of the target pixel to the adjacent pixel having the larger signal level difference between the target pixel and the signal level of the two adjacent pixels adjacent to both sides of the target pixel. An image processing apparatus characterized in that it is obtained by performing a predetermined calculation on the signal level of the target pixel based on a value obtained by multiplying a difference value from the signal level by a predetermined coefficient.   2. The fixed pattern correction unit obtains the signal level of the target pixel by adding or subtracting a value obtained by multiplying the difference value by a predetermined coefficient to the signal level of the target pixel. The image processing apparatus described.   3. The image processing apparatus according to claim 1, wherein the fixed pattern detection unit and the fixed pattern correction unit are provided in a subsequent stage of a unit for correcting variation between channels of the image sensor.   The image processing apparatus according to claim 1, wherein the fixed pattern detection unit and the fixed pattern correction unit are provided in front of the enlargement processing unit. In an image processing method for performing signal processing on input image data,
A step for detecting a predetermined fixed pattern using pixel data to be processed and data of surrounding pixels; and
Performing a correction process on the pixels in which the predetermined fixed pattern is detected in the step;
Including
The step of performing the correction processing includes setting the signal level of the target pixel to an adjacent pixel having a larger signal level difference between the target pixel and the signal level of the two adjacent pixels adjacent to both sides of the target pixel. An image processing method comprising: obtaining a signal level of a pixel of interest by performing a predetermined calculation based on a value obtained by multiplying a difference value with a signal level of a pixel by a predetermined coefficient.   The step of performing the correction process is characterized in that the signal level of the target pixel is obtained by adding or subtracting a value obtained by multiplying the difference value by a predetermined coefficient to the signal level of the target pixel. An image processing method described in 1.   Imaging a step of detecting a predetermined fixed pattern using pixel data to be processed and data of surrounding pixels, and a step of performing a correction process on the pixel in which the predetermined fixed pattern is detected in the step The image processing method according to claim 5, wherein the image processing method is provided after the step of correcting the inter-channel variation of the element.   A step of detecting a predetermined fixed pattern using pixel data to be processed and data of peripheral pixels thereof; a step of performing a correction process on a pixel in which the predetermined fixed pattern is detected in the step; The image processing method according to claim 5, wherein the image processing method is provided before the step of performing the enlargement process.

Images