JP5017567B2 - Image processing apparatus and surveillance camera - Google Patents

Description

  The present invention relates to an image processing apparatus and a surveillance camera.

  Patent Document 1 below discloses an image processing apparatus that performs edge enhancement processing on an input image using a Laplacian filter.

Japanese Patent Laid-Open No. 9-200530

  According to the image processing apparatus disclosed in Patent Document 1, since edge enhancement processing is unconditionally performed on an input image, not only edges but also noise is unnecessarily enhanced.

  The present invention has been made in view of such circumstances, and an object thereof is to obtain an image processing apparatus capable of enhancing only an edge without enhancing noise and a surveillance camera including the image processing apparatus.

An image processing apparatus according to a first aspect of the present invention includes: a first processing unit that determines an edge strength of a target pixel; and a process including an edge enhancement process by correcting a pixel value of the target pixel. A second processing unit to be executed on the pixel, and when the first processing unit determines that the edge intensity of the target pixel is equal to or higher than a first threshold value, the second processing unit Then, edge enhancement processing is executed using the first correction pattern, and the first processing unit determines that the edge intensity of the target pixel is less than the first threshold and greater than or equal to the second threshold. In this case, the second processing unit performs an edge enhancement process using a second correction pattern having a correction coefficient smaller than that of the first correction pattern, and the edge intensity of the target pixel is the second correction pattern. The first processing unit determines that it is less than the threshold value, In addition, when there is a pixel having an edge intensity equal to or higher than the first threshold value in a plurality of pixels around the target pixel, the second processing unit corrects more than the second correction pattern. Edge enhancement processing is executed using a third correction pattern having a small coefficient.

  According to the image processing apparatus according to the first aspect, the second processing unit does not unconditionally execute the edge enhancement process using the first correction pattern, but the edge intensity of the target pixel is the first. It is executed on condition that it is equal to or more than the threshold value. Therefore, it is possible to surely avoid that noise whose edge intensity is less than the first threshold is unnecessarily enhanced by the edge enhancement process.

In addition, when the edge intensity of the target pixel is in the vicinity of the first threshold value, a frame in which the edge enhancement process using the first correction pattern is executed and a frame in which the edge enhancement process is not executed are alternately repeated. As a result, the screen may flicker. Even in such a case, according to the image processing device according to the first aspect, the frame in which the edge enhancement process using the first correction pattern is executed and the edge enhancement using the second correction pattern are performed. Since the frame in which the process is executed is alternately repeated, the flickering of the screen is suppressed.

Further , according to the image processing apparatus according to the first aspect, regarding the peripheral pixels of the pixel having the edge intensity equal to or higher than the first threshold value, the edge intensity of the peripheral pixel itself is less than the second threshold value. Even if it exists, the edge emphasis processing using the third correction pattern is executed. As a result, for example, a line-shaped edge is corrected to be thick, so that the edge enhancement effect can be enhanced.

An image processing apparatus according to a second aspect of the present invention includes: a first processing unit that determines an edge strength of a target pixel; and a process including an edge enhancement process by correcting a pixel value of the target pixel. A second processing unit to be executed on the pixel, and when the first processing unit determines that the edge intensity of the target pixel is equal to or higher than a first threshold value, the second processing unit , Edge enhancement processing is performed using the first correction pattern, the first processing unit determines that the edge intensity of the pixel of interest is less than the first threshold, and the pixel of interest When there is a pixel having an edge strength equal to or higher than the first threshold value in a plurality of adjacent pixels, the second processing unit has a second correction coefficient smaller than that of the first correction pattern. Edge enhancement processing is executed using the correction pattern.

According to the image processing apparatus according to the second aspect, the second processing unit does not unconditionally execute the edge enhancement processing using the first correction pattern, but the edge strength of the target pixel is the first. It is executed on condition that it is equal to or more than the threshold value. Therefore, it is possible to surely avoid that noise whose edge intensity is less than the first threshold is unnecessarily enhanced by the edge enhancement process. For the peripheral pixels of the pixel whose edge intensity is equal to or higher than the first threshold value, the edge using the second correction pattern is used even if the peripheral intensity of the peripheral pixel itself is less than the first threshold value. Emphasis processing is executed. As a result, for example, a line-shaped edge is corrected to be thick, so that the edge enhancement effect can be enhanced.

A surveillance camera according to a third aspect of the present invention is connected to an imaging unit, a noise processing unit that performs a predetermined noise removal process on an image captured by the imaging unit, and a stage subsequent to the noise processing unit. In addition, the image processing apparatus according to the first or second aspect, and at least one of an image display unit and an image recording unit connected at a later stage than the image processing apparatus are provided.

According to the surveillance camera according to the third aspect, it is possible to display or record a high-quality video in which noise removal processing and edge enhancement processing are appropriately executed on a captured image.

  According to the present invention, it is possible to obtain an image processing apparatus capable of enhancing only edges without enhancing noise and a surveillance camera including the image processing apparatus.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In addition, the element which attached | subjected the same code | symbol in different drawing shall show the same or corresponding element.

  FIG. 1 is a block diagram schematically showing the overall configuration of a surveillance camera 1 according to the present invention. The surveillance camera 1 includes an imaging unit 2, an image processing unit 3, a display unit 4, and a recording unit 5. The imaging unit 2 includes an arbitrary imaging element such as a CCD or a CMOS image sensor, and captures an image of a desired monitoring target area. The image processing unit 3 includes a preprocessing unit 6 connected to the subsequent stage of the imaging unit 2, a noise processing unit 7 connected to the subsequent stage of the preprocessing unit 6, and an edge processing unit connected to the subsequent stage of the noise processing unit 7. 8. The display unit 4 and the recording unit 5 are respectively connected to the subsequent stage of the edge processing unit 8. However, both the display unit 4 and the recording unit 5 are not necessarily provided, and either one may be omitted. The display unit 4 has an arbitrary display device such as an LCD or an organic EL display. The recording unit 5 can record an image on an arbitrary recording medium such as a hard disk or a semiconductor memory.

  The image data S1 output from the imaging unit 2 is input to the preprocessing unit 6. The preprocessing unit 6 performs predetermined preprocessing such as white balance adjustment and black level correction on the image data S1. The image data S2 output from the preprocessing unit 6 is input to the noise processing unit 7. The noise processing unit 7 performs a predetermined noise removal process on the image data S2. Details of the configuration and operation of the noise processing unit 7 will be described later. The image data S3 output from the noise processing unit 7 is input to the edge processing unit 8. The edge processing unit 8 performs predetermined edge enhancement processing on the image data S3. Details of the configuration and operation of the edge processing unit 8 will be described later. The image data S4 output from the edge processing unit 8 is input to the display unit 4 and the recording unit 5, respectively. The display unit 4 displays an image based on the image data S4. The recording unit 5 records the image data S4.

  FIG. 2 is a block diagram showing a configuration of the noise processing unit 7 shown in FIG. The noise processing unit 7 includes line memories 10 to 12, registers A 1 to A 9, a product-sum operation circuit 13, and a storage unit 14. The registers A1 to A3 correspond to the line memory 10, the registers A4 to A6 correspond to the line memory 11, and the registers A7 to A9 correspond to the line memory 12. The registers A1 to A9 store a total of nine pixel values for 3 rows × 3 columns. The pixel whose pixel value is stored in the center register A5 is the target pixel. The storage unit 14 is configured by a semiconductor memory such as a RAM or a ROM. The storage unit 14 stores a spatial filter table T1.

  FIG. 3 is a diagram illustrating the spatial filter table T1. In the spatial filter table T1, a total of nine coefficients corresponding to 3 rows × 3 columns are set corresponding to the registers A1 to A9. In the example shown in FIG. 3, the spatial filter table T1 is an averaging filter, and the values of the nine coefficients are all “1/9”. However, the spatial filter table T1 may be another smoothing filter such as a median filter.

  Referring to FIG. 2, the product-sum operation circuit 13 uses the nine pixel values stored in the registers A1 to A9 and the nine coefficients set in the spatial filter table T1 for each corresponding position. Then, 9 multiplication results are added. As a result, the pixel value of the target pixel stored in the register A5 is corrected to the pixel value obtained as the addition result. By repeatedly executing the above processing while sequentially shifting the pixel values stored in the registers A1 to A9, image data S3 obtained by performing noise removal processing on the image data S2 is output from the noise processing unit 7. The

  FIG. 4 is a block diagram schematically showing the configuration of the edge processing unit 8 shown in FIG. The edge processing unit 8 includes an edge enhancement processing unit 20 and an edge strength determination processing unit 21. The edge enhancement processing unit 20 and the edge strength determination processing unit 21 are input with the image data S3 from the noise processing unit 7 shown in FIG. The edge enhancement processing unit 20 receives data D1 from the edge strength determination processing unit 21. The configurations and operations of the edge enhancement processing unit 20 and the edge strength determination processing unit 21 will be described in detail in first to fifth embodiments described later.

<First Embodiment>
FIG. 5 is a block diagram illustrating a configuration of the edge strength determination processing unit 21 according to the first embodiment. The edge strength determination processing unit 21 includes line memories 30 to 32, registers B1 to B9, a product-sum operation circuit 33, a storage unit 34, and a comparison unit 35. The registers B1 to B3 correspond to the line memory 30, the registers B4 to B6 correspond to the line memory 31, and the registers B7 to B9 correspond to the line memory 32. The registers B1 to B9 store a total of 9 pixel values for 3 rows × 3 columns. In the following example, the pixel value is a luminance value. However, the pixel value may be a color difference value. The pixel whose pixel value is stored in the central register B5 is the target pixel. The storage unit 34 is configured by a semiconductor memory such as a RAM or a ROM. The storage unit 34 stores a spatial filter table T2.

  FIG. 6 is a diagram illustrating the spatial filter table T2. In the spatial filter table T2, a total of nine coefficients corresponding to 3 rows × 3 columns are set corresponding to the registers B1 to B9. In the example shown in FIG. 6, the spatial filter table T2 is an 8-direction Laplacian filter, the value of the coefficient at the center is “−8”, and the values of the other coefficients are all “1”. However, the spatial filter table T2 may be another edge detection filter such as a four-way Laplacian filter or a Sobel filter.

  Referring to FIG. 5, the product-sum operation circuit 33 uses the nine pixel values stored in the registers B1 to B9 and the nine coefficients set in the spatial filter table T2 for each corresponding position. Then, 9 multiplication results are added. As a result, the edge strength of the target pixel stored in the register B5 is obtained as the addition result. The obtained edge strength is input to the comparison unit 35 as data D2.

  Here, threshold values TH1 and TH2 relating to the edge strength are preset and stored in a register (not shown) or the like that can be referred to by the comparison unit 35. An arbitrary value can be set as the threshold value TH1. As threshold value TH2, any value less than threshold value TH1 can be set.

  The comparison unit 35 compares the edge strength (data D2) with the threshold values TH1 and TH2, and outputs the comparison result as data D1.

  FIG. 7 is a block diagram illustrating a configuration of the edge enhancement processing unit 20 according to the first embodiment. The edge enhancement processing unit 20 includes line memories 40 to 42, registers C1 to C9, a product-sum operation circuit 43, a storage unit 44, and a selection unit 45. The registers C1 to C3 correspond to the line memory 40, the registers C4 to C6 correspond to the line memory 41, and the registers C7 to C9 correspond to the line memory 42. The registers C1 to C9 store a total of nine pixel values for 3 rows × 3 columns. A pixel whose pixel value is stored in the central register C5 is a target pixel. The storage unit 44 is configured by a semiconductor memory such as a RAM or a ROM. The storage unit 44 stores spatial filter tables T3 and T4 (correction patterns).

  FIG. 8 is a diagram showing the spatial filter table T3. In the spatial filter table T3, a total of nine coefficients (correction coefficients) for 3 rows × 3 columns are set corresponding to the registers C1 to C9. In the example shown in FIG. 8, the value of the coefficient at the center is “9”, and the values of the other coefficients are all “−1”. However, the spatial filter table T3 may be another edge enhancement filter.

  FIG. 9 is a diagram showing the spatial filter table T4. In the spatial filter table T4, a total of nine coefficients (correction coefficients) for 3 rows × 3 columns are set corresponding to the registers C1 to C9. In the example shown in FIG. 9, the value of the coefficient at the center is “9/2”, and the values of the other coefficients are all “−1/2”. That is, if the spatial filter table T3 shown in FIG. 8 is considered as a 100% edge enhancement filter, the spatial filter table T4 is a 50% edge enhancement filter. However, the spatial filter table T4 may be another edge enhancement filter having a lower edge enhancement effect (that is, a smaller correction coefficient) than the spatial filter table T3.

  FIG. 10 is a flowchart for explaining the operation of the edge processing unit 8 according to the first embodiment. Hereinafter, the operation of the edge processing unit 8 according to the first embodiment will be described with reference to FIGS.

  First, in step P11, the comparison unit 35 compares the edge strength X (data D2) with the threshold value TH1.

  If the edge strength X is greater than or equal to the threshold value TH1, that is, if the determination result in step P11 is “YES”, then in step P12, 100% edge enhancement processing is executed. Specifically, data D1 indicating that the edge strength X is greater than or equal to the threshold value TH1 is input to the selection unit 45, and the selection unit 45 selects the spatial filter table T3. Then, the product-sum operation circuit 43 multiplies the nine pixel values stored in the registers C1 to C9 and the nine coefficients set in the spatial filter table T3 for each corresponding position, and then , 9 multiplication results are added. Thereby, the pixel value of the target pixel stored in the register C5 is corrected as an addition result.

  On the other hand, if the edge strength X is less than the threshold value TH1, that is, if the determination result in step P11 is “NO”, then in step P13, the comparison unit 35 calculates the edge strength X and the threshold value TH2. Compare.

  If the edge strength X is greater than or equal to the threshold value TH2, that is, if the determination result in step P13 is “YES”, then in step P14, 50% edge enhancement processing is executed. Specifically, data D1 indicating that the edge strength X is less than the threshold value TH1 and greater than or equal to the threshold value TH2 is input to the selection unit 45, and the selection unit 45 selects the spatial filter table T4. Then, the product-sum operation circuit 43 multiplies the nine pixel values stored in the registers C1 to C9 and the nine coefficients set in the spatial filter table T4 for each corresponding position, and then , 9 multiplication results are added. Thereby, the pixel value of the target pixel stored in the register C5 is corrected as an addition result.

  On the other hand, when the edge strength X is less than the threshold value TH2, that is, when the determination result in Step P13 is “NO”, the process proceeds to Step P15, and the edge enhancement processing is not executed. Specifically, data D1 indicating that the edge strength X is less than the threshold value TH2 is input to the selection unit 45. The selection unit 45 sets the center coefficient to “1” and the other coefficients to “0”. A set 3 × 3 spatial filter table (not shown) is selected. The product-sum operation circuit 43 multiplies the nine pixel values stored in the registers C1 to C9 and the nine coefficients set in the spatial filter table for each corresponding position, and then 9 Add the multiplication results. As a result, the pixel value stored in the register C5 is output as the image data S4.

  By repeatedly executing the above processing while sequentially shifting the pixel values stored in the registers B1 to B9 and C1 to C9, the image data S4 that has been subjected to the edge enhancement processing on the image data S3 becomes the edge enhancement processing. Output from the unit 20.

  According to the edge processing unit 8 according to the first embodiment, the edge enhancement processing unit 20 does not unconditionally execute the edge enhancement processing on the image data S3, but the edge intensity X of the target pixel is at least Edge enhancement processing is executed on condition that the second threshold value TH2 or more. Therefore, it is possible to surely avoid that noise whose edge intensity X is less than the second threshold is unnecessarily enhanced by the edge enhancement process.

  Further, according to the edge processing unit 8 according to the first embodiment, even if the edge intensity X of the target pixel is less than the first threshold TH1, if it is equal to or higher than the second threshold TH2, Perform edge enhancement processing. If the edge strength X is less than the first threshold value TH1, the edge enhancement process is not executed. If the edge strength X is in the vicinity of the first threshold value TH1, the spatial filter table T3 is stored. A frame in which the used edge enhancement processing is executed and a frame in which the edge enhancement processing is not executed are alternately repeated, and a situation in which the screen flickers may occur. Even in such a case, according to the image processing device according to the first embodiment, the frame in which the edge enhancement process using the spatial filter table T3 is executed and the edge enhancement using the spatial filter table T4 are performed. Since the frame in which the process is executed is alternately repeated, the flickering of the screen is suppressed.

  In addition, according to the surveillance camera 1 according to the first embodiment, a high-quality video in which noise removal processing and edge enhancement processing are appropriately performed on a captured image is displayed or recorded on the display unit 4. 5 can be recorded.

<Second Embodiment>
The configuration and operation of the edge strength determination processing unit 21 according to the second embodiment are the same as those in the first embodiment.

  FIG. 11 is a block diagram illustrating a configuration of the edge enhancement processing unit 20 according to the second embodiment. The storage unit 44 stores a spatial filter table T5 (correction pattern) in addition to the spatial filter tables T3 and T4. Other configurations of the edge enhancement processing unit 20 are the same as those in the first embodiment.

  FIG. 12 is a diagram illustrating the spatial filter table T5. In the spatial filter table T5, a total of nine coefficients (correction coefficients) for 3 rows × 3 columns are set corresponding to the registers C1 to C9. In the example shown in FIG. 12, the value of the center coefficient is “9/4”, and the values of the other coefficients are all “−1/4”. That is, if the spatial filter table T3 shown in FIG. 8 is considered as a 100% edge enhancement filter, the spatial filter table T5 is a 25% edge enhancement filter. However, the spatial filter table T5 may be another edge enhancement filter having a lower edge enhancement effect (that is, a smaller correction coefficient) than the spatial filter table T4 shown in FIG.

  FIG. 13 is a flowchart for explaining the operation of the edge processing unit 8 according to the second embodiment. The operation of the edge processing unit 8 according to the second embodiment will be described below with reference to FIGS.

  The operations in steps P21 to P24 are the same as the operations in steps P11 to P14 shown in FIG.

  If the edge intensity X of the target pixel is less than the threshold value TH2, that is, if the determination result in step P23 is “NO”, then in step P25, the target pixel has an edge intensity equal to or greater than the threshold value TH1. It is determined whether or not the pixel is adjacent.

  FIG. 14 is a diagram illustrating pixels G11 to G13, G21 to G23, and G31 to G33 for 3 rows × 3 columns. The target pixel is the center pixel G22. Here, regarding the pixels G11 to G13, G21, it is assumed that the calculation of the edge strength has already been completed. In this case, in Step P25, it is determined whether or not there is a pixel having an edge strength equal to or higher than the threshold value TH1 among the pixels G11 to G13, G21. For example, the least significant bit of each pixel value of the pixels G11 to G13 and G21 is set to “0” or “1” in advance depending on whether the edge strength is greater than or equal to the threshold value TH1. Has been replaced. If one or more pixels with the least significant bit of the pixel value “0” are present in the pixels G11 to G13, G21, the determination result in step P25 is “YES”, and if there is no pixel. The determination result in step P25 is “NO”. Data D3 related to the determination result is input to the selection unit 45.

  If the determination result in step P25 is “YES”, then in step P26, 25% edge enhancement processing is executed. Specifically, data D3 indicating that the target pixel is adjacent to a pixel having an edge intensity equal to or greater than the threshold value TH1 is input to the selection unit 45, and the selection unit 45 selects the spatial filter table T5. Then, the product-sum operation circuit 43 multiplies the nine pixel values stored in the registers C1 to C9 and the nine coefficients set in the spatial filter table T5 for each corresponding position, and then , 9 multiplication results are added. Thereby, the pixel value of the target pixel stored in the register C5 is corrected as an addition result.

  On the other hand, if the target pixel is not adjacent to a pixel having an edge strength equal to or greater than the threshold TH1, that is, if the determination result in Step P25 is “NO”, the process proceeds to Step P27, and the edge enhancement process is not performed. The operation in Step P27 is the same as the operation in Step P15 shown in FIG.

  According to the edge processing unit 8 according to the second embodiment, regarding the peripheral pixels of the pixel whose edge strength X is equal to or higher than the first threshold value TH1, the edge strength X of the peripheral pixel itself is the second threshold. Even if it is less than the threshold value TH2, edge enhancement processing using the spatial filter table T5 is executed. As a result, for example, a line-shaped edge is corrected to be thick, so that the edge enhancement effect can be enhanced.

<Third Embodiment>
In the second embodiment, when the edge intensity X of the target pixel is less than the threshold value TH2, it is determined whether the target pixel is adjacent to a pixel having an edge intensity equal to or higher than the threshold value TH1. It has been executed. In the third embodiment, the determination as to whether or not the edge intensity X of the target pixel is less than the threshold value TH2 is omitted, and when the edge intensity X of the target pixel is less than the threshold value TH1, It is determined whether or not the pixel is adjacent to a pixel having an edge strength equal to or greater than the threshold value TH1.

  FIG. 15 is a block diagram illustrating a configuration of the edge strength determination processing unit 21 according to the third embodiment. The threshold value TH2 is not input to the comparison unit 35, and only the threshold value TH1 is input. Other configurations of the edge strength determination processing unit 21 are the same as those in the first embodiment.

  FIG. 16 is a block diagram illustrating a configuration of the edge enhancement processing unit 20 according to the third embodiment. The storage unit 44 stores spatial filter tables T3 and T5, and does not store the spatial filter table T4. Other configurations of the edge enhancement processing unit 20 are the same as those in the second embodiment.

  FIG. 17 is a flowchart for explaining the operation of the edge processing unit 8 according to the third embodiment. The operation of the edge processing unit 8 according to the third embodiment will be described below with reference to FIGS.

  The operations in steps P31 and P32 are the same as the operations in steps P11 and P12 shown in FIG.

  If the edge intensity X of the target pixel is less than the threshold value TH1, that is, if the determination result in step P31 is “NO”, then in step P33, the target pixel has an edge intensity equal to or higher than the threshold value TH1. It is determined whether or not the pixel is adjacent.

  The operations in Steps P33 to P35 are the same as the operations in Steps P25 to P27 shown in FIG.

  According to the edge processing unit 8 according to the third embodiment, the edge intensity X of the peripheral pixel itself is the first threshold for the peripheral pixels of the pixel whose edge intensity X is equal to or higher than the first threshold value TH1. Even if the threshold value is less than TH1, the edge enhancement process using the spatial filter table T5 is executed. As a result, for example, a line-shaped edge is corrected to be thick, so that the edge enhancement effect can be enhanced.

  Further, according to the edge processing unit 8 according to the third embodiment, the determination as to whether or not the edge intensity X of the pixel of interest is less than the threshold value TH2 is omitted as compared with the second embodiment. Therefore, the process can be simplified.

<Fourth embodiment>
In the first embodiment, when the edge intensity X of the target pixel is less than the threshold value TH2, the pixel value of the target pixel is output from the edge processing unit 8 as it is. In the fourth embodiment, when the edge intensity X of the pixel of interest is less than the threshold value TH2, the edge processing unit 8 performs noise removal processing.

  The configuration and operation of the edge strength determination processing unit 21 according to the fourth embodiment are the same as those in the first embodiment.

  FIG. 18 is a block diagram illustrating a configuration of the edge enhancement processing unit 20 according to the fourth embodiment. The storage unit 44 stores a spatial filter table T6 in addition to the spatial filter tables T3 and T4. The spatial filter table T6 is an averaging filter similar to that in FIG. However, the spatial filter table T6 may be another smoothing filter such as a median filter. Other configurations of the edge enhancement processing unit 20 are the same as those in the first embodiment.

  FIG. 19 is a flowchart for explaining the operation of the edge processing unit 8 according to the fourth embodiment. The operation of the edge processing unit 8 according to the fourth embodiment will be described below with reference to FIGS.

  The operations in steps P41 to P44 are the same as the operations in steps P11 to P14 shown in FIG.

  If the edge intensity X of the target pixel is less than the threshold value TH2, that is, if the determination result in step P43 is “NO”, then in step P45, a smoothing process is executed. Specifically, data D1 indicating that the edge strength X is less than the threshold value TH2 is input to the selection unit 45, and the selection unit 45 selects the spatial filter table T6. Then, the product-sum operation circuit 43 multiplies the nine pixel values stored in the registers C1 to C9 and the nine coefficients set in the spatial filter table T6 for each corresponding position, and then , 9 multiplication results are added. As a result, the pixel value of the target pixel stored in the register C5 is corrected to the pixel value obtained as the addition result.

  According to the edge processing unit 8 according to the fourth embodiment, when the edge intensity X of the target pixel is less than the second threshold value TH2, the edge enhancement processing unit 20 performs smoothing processing instead of edge enhancement processing. Execute. Therefore, since the smoothing process is executed by both the noise processing unit 7 and the edge processing unit 8 for the background portion having extremely low edge strength, the noise removal effect can be enhanced.

<Fifth embodiment>
In the fourth embodiment, the smoothing process is executed when the edge intensity X of the target pixel is less than the threshold value TH2. In the fifth embodiment, the determination as to whether or not the edge intensity X of the target pixel is less than the threshold value TH2 is omitted, and smoothing is performed when the edge intensity X of the target pixel is less than the threshold value TH1. Execute the conversion process.

  The configuration and operation of the edge strength determination processing unit 21 according to the fifth embodiment are the same as those in the third embodiment.

  FIG. 20 is a block diagram illustrating a configuration of the edge enhancement processing unit 20 according to the fifth embodiment. The storage unit 44 stores spatial filter tables T3 and T6, and does not store the spatial filter table T4. The other configuration of the edge enhancement processing unit 20 is the same as that of the fourth embodiment.

  FIG. 21 is a flowchart for explaining the operation of the edge processing unit 8 according to the fifth embodiment. The operation of the edge processing unit 8 according to the fifth embodiment will be described below with reference to FIGS.

  The operations in steps P51 and P52 are the same as the operations in steps P41 and P42 shown in FIG.

  If the edge intensity X of the target pixel is less than the threshold value TH1, that is, if the determination result in step P51 is “NO”, then in step P53, smoothing processing is executed.

  The operation in Step P53 is the same as the operation in Step P45 shown in FIG.

  According to the edge processing unit 8 according to the fifth aspect, when the edge intensity X of the target pixel is less than the first threshold value TH1, the edge enhancement processing unit 20 performs smoothing processing instead of edge enhancement processing. To do. Therefore, since the smoothing process is executed by both the noise processing unit 7 and the edge processing unit 8 for the background portion having extremely low edge strength, the noise removal effect can be enhanced.

  Further, according to the edge processing unit 8 according to the fifth embodiment, the determination as to whether or not the edge intensity X of the pixel of interest is less than the threshold value TH2 is omitted as compared with the fourth embodiment. Therefore, the process can be simplified.

It is a block diagram which shows roughly the whole structure of the surveillance camera which concerns on this invention. It is a block diagram which shows the structure of the noise process part shown in FIG. It is a figure which shows a spatial filter table. FIG. 2 is a block diagram schematically illustrating a configuration of an edge processing unit illustrated in FIG. 1. It is a block diagram which shows the structure of the edge strength determination process part which concerns on 1st Embodiment. It is a figure which shows a spatial filter table. It is a block diagram which shows the structure of the edge emphasis processing part which concerns on 1st Embodiment. It is a figure which shows a spatial filter table. It is a figure which shows a spatial filter table. It is a flowchart for demonstrating operation | movement of the edge process part which concerns on 1st Embodiment. It is a block diagram which shows the structure of the edge emphasis processing part which concerns on 2nd Embodiment. It is a figure which shows a spatial filter table. It is a flowchart for demonstrating operation | movement of the edge process part which concerns on 2nd Embodiment. It is a figure which shows the pixel for 3 rows x 3 columns. It is a block diagram which shows the structure of the edge strength determination process part which concerns on 3rd Embodiment. It is a block diagram which shows the structure of the edge emphasis processing part which concerns on 3rd Embodiment. It is a flowchart for demonstrating operation | movement of the edge process part which concerns on 3rd Embodiment. It is a block diagram which shows the structure of the edge emphasis processing part which concerns on 4th Embodiment. It is a flowchart for demonstrating operation | movement of the edge process part which concerns on 4th Embodiment. It is a block diagram which shows the structure of the edge emphasis processing part which concerns on 5th Embodiment. It is a flowchart for demonstrating operation | movement of the edge process part which concerns on 5th Embodiment.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Surveillance camera 2 Image pick-up part 3 Image processing part 4 Display part 5 Recording part 7 Noise processing part 9 Edge processing part 20 Edge emphasis processing part 21 Edge strength determination processing part T1-T6 Spatial filter table

Claims (3)

A first processing unit for determining the edge strength of the pixel of interest;
A second processing unit that performs processing including edge enhancement processing on the pixel of interest by correcting a pixel value of the pixel of interest;
If the edge strength of the target pixel is the first processing unit that the first threshold value or more is determined, the second processing unit executes the edge enhancement using the first correction pattern ,
When the first processing unit determines that the edge intensity of the target pixel is less than the first threshold and greater than or equal to the second threshold, the second processing unit performs the first correction Using the second correction pattern having a smaller correction coefficient than the pattern, the edge enhancement process is executed,
The first processing unit determines that the edge strength of the target pixel is less than the second threshold value, and the edge strength is within the plurality of pixels around the target pixel. When there is a pixel having a threshold value or more, the second processing unit executes an edge enhancement process using a third correction pattern having a correction coefficient smaller than that of the second correction pattern. .   A first processing unit for determining the edge strength of the pixel of interest;
  A second processing unit that executes processing including edge enhancement processing on the target pixel by correcting the pixel value of the target pixel;
With
  When the first processing unit determines that the edge intensity of the target pixel is equal to or higher than a first threshold value, the second processing unit executes edge enhancement processing using the first correction pattern. ,
  The first processing unit determines that the edge intensity of the pixel of interest is less than the first threshold value, and the edge intensity is within the plurality of pixels adjacent to the pixel of interest. When there is a pixel having a threshold value or more, the second processing unit executes an edge enhancement process using a second correction pattern having a correction coefficient smaller than that of the first correction pattern. .   An imaging unit;
  A noise processing unit that performs a predetermined noise removal process on the image captured by the imaging unit;
  The image processing apparatus according to claim 1, wherein the image processing apparatus is connected downstream of the noise processing unit.
  At least one of an image display unit and an image recording unit connected to a subsequent stage of the image processing apparatus;
A surveillance camera comprising:

Images