JP2017072966A - Image processing apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To generate a clear image appropriately from an original image.SOLUTION: An image processing apparatus includes: a setting unit which sets an operator formed of a plurality of pixels including a target pixel in an image to be processed; a parameter extraction unit which extracts a minimum grayscale value indicating a minimum value of pixel grayscale values and a maximum grayscale value indicating a maximum value of the pixel grayscale values, on the basis of the grayscale values of the pixels in the operator; and a grayscale value conversion unit which determines a gain, on the basis of the minimum grayscale value and the maximum grayscale value extracted by the parameter extraction unit, and applies the gain to a grayscale value of the target pixel, to determine a grayscale value of the target pixel after conversion.SELECTED DRAWING: Figure 2

Description

  One aspect of the present invention relates to an image processing apparatus.

  Conventionally, as shown in the following Patent Document 1, it is easy to see a screen in which extremely bright portions and dark portions are mixed in the same screen in an image (still image or moving image frame) taken by a surveillance camera or the like An image processing method for converting to a screen is known.

  In the image processing method, the image processing apparatus captures image data in units of pixels from an image obtained by photographing a subject, and generates a histogram of luminance after decomposing the captured image data into a specific color space. Means. The image processing device reads the image in a predetermined pattern for each color by the capturing means, generates an average histogram around the pixel at a specific position in the pattern using the histogram generating means, and specifies using the average histogram Sets the brightness of the pixel at the position.

Japanese Patent No. 4386959

  Various methods are known for obtaining a sharpened image by converting the gradation of each pixel in the captured image as in the above method. According to such a method, it is possible to obtain an image that is clear and easy to view. However, for example, if the degree of sharpening (level) is too strong, fine portions in the image are sharpened, and an image with noticeable noise may be generated. Therefore, there is a demand for an image processing technique that can appropriately sharpen the original image and generate an easy-to-view image.

  An image processing apparatus according to an aspect of the present invention provides a setting unit that sets an operator including a plurality of pixels including a target pixel in a processing target image, and a level of each pixel based on a gradation value of each pixel in the operator. A parameter extraction unit for extracting a minimum gradation value indicating the minimum value of the tone values and a maximum gradation value indicating the maximum value of the gradation value of each pixel; and the minimum gradation value and the maximum floor extracted by the parameter extraction unit A tone value conversion unit that determines a gain value based on the tone value and determines the tone value after conversion of the target pixel by applying the gain to the tone value of the target pixel.

  In such a form, a conversion process is performed in which the gain determined based on the minimum gradation value and the maximum gradation value of each pixel in the operator is applied to the gradation value of the target pixel in the operator. The converted tone value is determined. By executing the application of gain in units of operators as the target pixel for each pixel in the processing target image, an appropriate value determined depending on the distribution of gradation values of the respective pixels included in the operator for each operator. It is possible to achieve a degree of sharpening. Thereby, it is possible to obtain an easy-to-see image in which the degree of sharpening is appropriately adjusted.

  In the image processing apparatus according to another aspect, the gradation value conversion unit divides the gradation resolution indicating the number of gradation values that can be expressed in the processing target image by the difference between the maximum gradation value and the minimum gradation value. The tone value after conversion of the target pixel may be calculated by calculating the gain by multiplying the difference between the tone value of the target pixel and the minimum tone value by the gain. According to this configuration, the converted gradation value can be easily calculated using a predetermined calculation formula.

  In the image processing apparatus according to another aspect, the gradation value conversion unit applies a predetermined adjustment value to at least one of the minimum gradation value and the maximum gradation value before determining the gain and the converted gradation value. You may perform the adjustment process which adds or subtracts. According to this configuration, for example, by applying an adjustment value according to user preference, image characteristics, or the like to the minimum gradation value and / or the maximum gradation value, the degree of sharpening (for example, darkness or brightness is reduced). The degree of pulling up can be adjusted.

  An image processing apparatus according to another aspect obtains a gradation value of each pixel in an operator, and displays a histogram indicating the number of pixels of each gradation value from 0 to a natural number N based on the gradation value of each pixel. By adding the number of pixels of each gradation value from the gradation value 0 to the gradation value of the target pixel in the totalizing unit to be generated and the histogram, or each floor from the gradation value N to the gradation value of the target pixel By subtracting the number of pixels of the tone value from the value N, a second tone value conversion unit that determines the tone value after the second conversion of the target pixel, and the target pixel determined by the tone value conversion unit Outputs the gradation value obtained by adding the converted gradation value and the second converted gradation value of the target pixel determined by the second gradation value conversion unit in a predetermined mixing ratio. And a mixing unit. According to this configuration, the tone value converted by so-called local gain adjustment (the tone value after conversion) and the tone value converted by so-called histogram flattening (the tone value after the second conversion) It is possible to obtain an image in which the influence of noise is reduced.

  In the image processing apparatus according to another aspect, the parameter extraction unit is configured such that the second gradation value conversion unit converts the histogram from one end of the histogram indicating the gradation value 0 or the gradation value N for addition or subtraction of the number of pixels. In parallel with the process of referring to the number of pixels of each gradation value toward the other end, by referring to the number of pixels of each gradation value from one end of the histogram toward the other end, the minimum gradation value and the maximum gradation value May be extracted. According to this configuration, the process by the parameter extraction unit and the process by the second tone value conversion unit can be executed in parallel. As a result, the processing efficiency can be improved and the processing configuration (for example, circuit configuration) can be simplified.

  According to one aspect of the present invention, an original image can be appropriately sharpened to generate an easy-to-view image.

It is a figure which shows the hardware constitutions of the image processing apparatus which concerns on one Embodiment. It is a block diagram which shows the function structure of an image processing apparatus. It is a schematic diagram for demonstrating image quality adjustment processing. It is a figure which shows the circuit example which performs a gradation value conversion process. FIG. 5 is a diagram showing a configuration of first and second addition modules of the circuit shown in FIG. 4. It is a flowchart which shows operation | movement of an image processing apparatus. It is a figure which shows the other example of the circuit which comprises a 1st conversion part.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the description of the drawings, the same or equivalent elements are denoted by the same reference numerals, and redundant description is omitted.

  The image processing apparatus 1 according to an embodiment of the present invention captures images such as still images and moving image frames, and converts the gradation values of each pixel in the captured images, thereby making the images clearer and easier to see. It is a device for generating and outputting the resulting image. Although the image processing apparatus 1 is not limited to a specific application, for example, by executing the above-described processing on each frame of a video captured by a surveillance camera, it is possible to obtain a video in which each frame is clear and easy to see. . Here, the sharpening is image processing for making it easy to see a portion that is difficult to see due to a deviation in gradation value in an image. That is, sharpening is image processing that adjusts the gradation value of each pixel in an image. According to the sharpening, for example, it is possible to obtain an image in which a portion that is difficult to see because it is extremely bright (or extremely dark) in the original image becomes easy to see. Here, the gradation value is a numerical value that expresses gradations such as color and brightness in a stepwise manner. In the present embodiment, it is assumed that an image to be processed by the image processing apparatus 1 includes information such as resolution, gradation value in pixel (pixel) units, gradation resolution, and the like. The gradation resolution is the number of bits prepared for expressing gradation values in stages. For example, when the gradation resolution is 8 bits, the gradation value can be expressed by 256 levels from 0 to 255.

  FIG. 1 is a diagram illustrating an example of a hardware configuration of the image processing apparatus 1. As shown in this figure, the image processing apparatus 1 includes one or more CPUs (Central Processing Units) 101, a RAM (Random Access Memory) 102 and a ROM (Read Only Memory) 103, which are main storage devices, a keyboard and a mouse. A communication device 105 for performing data communication with an external device such as a database device for accumulating image data after storing the input device 104 and a device such as a monitoring camera from which an input image is acquired; An FPGA (Field-programmable gate array) 106, which is an integrated circuit, and an output device 107 such as a display are provided.

  For example, each functional component of the image processing apparatus 1 described later reads predetermined computer software on hardware such as the RAM 102, and the input device 104, the communication device 105, the FPGA 106, and the output device under the control of the CPU 101. This is realized by operating 107 and the like, and reading and writing data in the RAM 102 and the ROM 103. A circuit described later (see FIGS. 4, 5, and 7) is mounted in the FPGA 106 in advance, and for example, gradation value conversion processing (generated gradation values V1 and V2 after conversion described later) is generated by hardware processing. Processing) can be executed.

  Although FIG. 1 shows that the image processing apparatus 1 is configured as one computer, the functions of the image processing apparatus 1 may be distributed to a plurality of computers. In addition, the image processing apparatus 1 may be configured as an appliance specialized for a function that executes image processing such as sharpening of an input image, or as a function of the computer in a computer that executes a plurality of functions. May be incorporated.

  FIG. 2 is a block diagram illustrating a functional configuration of the image processing apparatus 1. As shown in FIG. 1, the image processing apparatus 1 includes a pre-processing unit 11, an operator setting unit 12, a first conversion unit 13, a second conversion unit 14, and a post-processing unit 15. The preprocessing unit 11 includes an image quality adjustment unit 111 and a resolution adjustment unit 112. The first conversion unit 13 includes a parameter extraction unit 131 and a gradation value conversion unit (first gradation value conversion unit) 132. The second conversion unit 14 includes a totaling unit 141 and a gradation value conversion unit (second gradation value conversion unit) 142. The post-processing unit 15 includes a mixing unit 151 and a mixing ratio adjusting unit 152.

  First, an outline of processing of the image processing apparatus 1 will be described. As shown in FIG. 2, in the image processing apparatus 1, first, the preprocessing unit 11 sequentially captures images taken by a surveillance camera or the like, and executes preprocessing on each frame of the captured images. A processing target image is generated. Specifically, the preprocessing unit 11 performs preprocessing using each of the captured video frames as an input image, and generates a processing target image. Here, the processing target image is an image that is a target of gradation value conversion processing of each of the first conversion unit 13 and the second conversion unit 14 described later. However, the preprocessing by the preprocessing unit 11 is not essential and can be omitted. When the preprocessing by the preprocessing unit 11 is omitted, the processing target image matches the input image.

  Subsequently, the operator setting unit 12, the first conversion unit 13, the second conversion unit 14, and the post-processing unit 15 execute each process using each pixel of the processing target image output from the preprocessing unit 11 as a processing target pixel. To do. That is, the processes of the operator setting unit 12, the first conversion unit 13, the second conversion unit 14, and the post-processing unit 15 are executed for each pixel of the processing target image. In this embodiment, as an example, the gradation value V0 of each pixel of the processing target image immediately after being generated by the preprocessing unit 11, the gradation value V1 of each pixel generated by the first conversion unit 13, and the second The gradation value V2 of each pixel generated by the conversion unit 14 is added at a predetermined mixing ratio by the mixing unit 151. In this manner, the post-processing unit 15 outputs an output image in which the gradation value of each pixel of the input image is converted from the viewpoints of both image quality improvement and sharpening. The mixing ratio can be set according to the state of the image, user preferences, and the like.

  Hereinafter, each functional component of the image processing apparatus 1 will be specifically described.

  The preprocessing unit 11 performs preprocessing on the input image prior to the tone value conversion processing (sharpening processing) by the first conversion unit 13 and the second conversion unit 14. As described above, the preprocessing by the preprocessing unit 11 is not essential and can be omitted in order to sharpen an image. However, by performing the preprocessing by the preprocessing unit 11, it can be expected that the image quality is improved as compared with the case where only the sharpening by the first conversion unit 13 and the second conversion unit 14 is performed. More specifically, the image after the sharpening by the first conversion unit 13 or the second conversion unit 14 by the preprocessing by the preprocessing unit 11 is made a beautiful image with a sharp appearance. Can do.

  When the preprocessing unit 11 acquires each frame of the video imaged by the surveillance camera or the like as an input image, the preprocessing unit 11 converts the gradation value of each pixel of the input image based on the characteristics of the input image. In the present embodiment, as an example, the preprocessing unit 11 converts the gradation value of each pixel based on the shape of a histogram related to the gradation value of each pixel of the input image. The function of the preprocessing unit 11 is realized by the image quality adjustment unit 111 and the resolution adjustment unit 112.

  The image quality adjustment unit 111 generates an overall histogram indicating the number of pixels of each gradation value from 0 to a natural number N based on the gradation value of each pixel in the input image. Here, “natural number N” is the maximum gradation value determined by the gradation resolution of the input image. For example, when the gradation resolution of the input image is 8 bits, since the gradation of each pixel is expressed in 256 levels from 0 to 255, the natural number N is 255.

  A graph (a) in FIG. 3 shows an example of the entire histogram generated by the image quality adjustment unit 111. When the whole histogram is visualized, a bar graph is obtained in which the horizontal axis indicates the gradation value and the vertical axis indicates the number of pixels. The graph (a) in FIG. 3 shows the whole histogram of such a bar graph. It is expressed as a line graph connecting adjacent vertices. In the entire histogram, a mountain-shaped distribution is formed in each of the area where the gradation value is from point S1 to point E1 and the area where the gradation value is from point S2 to point E2. Note that an image in which two peaks are formed in the entire histogram in this way is often an image taken in backlight.

  The image quality adjustment unit 111 converts the gradation value of each pixel in the input image based on the characteristics of the shape of the entire histogram generated as described above. Specifically, first, the image quality adjustment unit 111 extracts an area (useful gradation area) including information useful for constructing an image from the entire histogram. Here, the information useful for composing an image means information useful for recognizing an object reflected in the image.

  For example, in an overall histogram, an area having a low level (an index indicating the number of pixels corresponding to a gradation) and a small slope indicated by the rate of change in the number of pixels between adjacent gradation values Can be determined as an area (unnecessary gradation area) that has little useful information. On the contrary, the peak portion in the entire histogram (in the example of the graph (a) in FIG. 3) is useful in constructing an image for the area from the point S1 to the point E1 and the area from the point S2 to the point E2. It can be determined as a useful gradation area containing a lot of information. Based on the above, for example, the image quality adjustment unit 111 identifies an area where the level and the inclination of the entire histogram are each equal to or less than a predetermined threshold as an unnecessary gradation area, and sets the other areas as useful gradation areas. Can be extracted.

  Here, in many general images, an area having a small slope in the entire histogram is often seen in an area having a low level, but is hardly seen in an area having a high level (such as a mountain top). Utilizing such a property, the image quality adjustment unit 111 specifies an area whose inclination is equal to or smaller than a predetermined threshold in the whole histogram without considering the level as an unnecessary gradation area, and other areas. May be extracted as a useful gradation area.

  For example, the image quality adjustment unit 111 acquires the number of pixels of each gradation value from the gradation value 0 toward the direction in which the gradation value increases, and the two adjacent gradation values or a predetermined interval 2 is obtained. It may be determined whether the rate of change in the number of pixels is equal to or less than a threshold value between two gradation values. Specifically, when the rate of change in the number of pixels between two gradation values is equal to or less than a threshold value, it is determined that the area between the two gradation values is an unnecessary gradation area, and otherwise Alternatively, it may be determined that the area between the two gradation values is a useful gradation area.

  By executing such processing, the image quality adjustment unit 111 sets the point S1 shown in the graph (a) of FIG. 3 as the end point of the unnecessary gradation area on the side where the gradation value is small, that is, the first useful gradation. It can be determined as the start point of the area. Further, the image quality adjustment unit 111 can determine the point E1 shown in the graph (a) of FIG. 3 as the end point of the first useful gradation area by executing the same processing. In addition, the image quality adjustment unit 111 further determines the points S2 and E2 shown in the graph (a) of FIG. 3 as the start point and the end point of the second useful gradation area by further executing similar processing. it can. Here, the case where there are two useful gradation areas has been described as an example, but the same applies to the case where there is only one useful gradation area or three or more useful gradation areas. By this method, the useful gradation area and the unnecessary gradation area can be separated.

  Subsequently, the image quality adjustment unit 111 converts the gradation value of each pixel of the input image based on the useful gradation area and a gain determined according to the range of the useful gradation area. Here, the gain is a parameter indicating the degree to which the width of the distribution of the number of pixels of each gradation value is amplified. Specifically, the image quality adjustment unit 111 converts the entire gradation range in which the useful gradation area can be expressed by the gradation resolution of the input image in the entire histogram after converting the gradation value of each pixel of the input image. Determine the gain to occupy. Note that the gain here is a value determined by the distribution of gradation values of the entire input image, and is applied uniformly to all pixels. On the other hand, the gain determined by the first conversion unit 13 to be described later is a value locally determined in units of operators, and is applied individually to each pixel.

In the case of the example shown in the graph (a) of FIG. 3, the image quality adjustment unit 111 determines the gain by the following equation (1), and the gradation of each pixel of the input image by the following equations (2) and (3). Gain can be applied to the value. In the following formulas (2) and (3), vi represents a gradation value before conversion, and vo represents a gradation value after conversion.
Gain = (256 / ((E1-S1) + (E2-S2))) (1)
If vi <E1: vo = (vi−S1) × Gain (2)
If vi> S2: vo = (vi−S1− (S2−E1)) × Gain (3)

  When the calculation processing shown in the above equations (2) and (3) is executed for each pixel of the input image, the unnecessary gradation area is deleted as shown in the graph (b) of FIG. As shown in the graph (c), the useful gradation area is converted so as to occupy the entire gradation range that can be expressed by the gradation resolution of the input image. In the above-described processing by the image quality adjustment unit 111, the processing for separating the useful gradation area from the unnecessary gradation area (the processing for determining the points S1, E1, S2, and E2 in the above example) is executed by software processing. On the other hand, the calculation processing based on the above formulas (1) to (3) may be executed by hardware processing. Since it is necessary to execute the processing of the above formulas (2) and (3) for each pixel of the input image, the processing efficiency can be improved by executing the processing for each pixel in parallel by hardware processing. An image obtained by the image quality adjustment unit 111 (that is, an image in which the gradation value of each pixel of the input image is converted by the above equations (1) to (3)) is output to the resolution adjustment unit 112.

  The resolution adjustment unit 112 adjusts the gradation resolution of the input image to output the processing target image with the gradation resolution adjusted. Specifically, the gradation resolution is adjusted so that the number of pixels included in the operator set by the operator setting unit 12 described later matches the number of gradation values that can be expressed. An operator is a region composed of a plurality of pixels including target pixels in the processing target image. For example, when the operator set by the operator setting unit 12 is a rectangular area composed of 16 × 16 256 pixels, the resolution adjusting unit 112 can represent the gradation resolution of the input image with 256 step values. Adjust to 8 bits. For example, when the original gradation resolution of the input image is 10 bits, the resolution adjustment unit 112 converts the bit pattern of the original 10-bit gradation value to the right with respect to the gradation value of each pixel of the input image. By executing a shift operation shifted by 2 bits, the gradation resolution of the input image can be changed from 10 bits to 8 bits. By adjusting the gradation resolution in this way, calculation processing by the gradation value conversion unit 142 described later can be simplified, and the processing efficiency can be improved. The processing target image output by the resolution adjustment unit 112 is transferred to the operator setting unit 12 and the post-processing unit 15 (mixing unit 151).

  Next, the operator setting unit 12, the first conversion unit 13, the second conversion unit 14, and the post-processing unit 15 will be described. As described above, the processing of the operator setting unit 12, the first conversion unit 13, the second conversion unit 14, and the post-processing unit 15 is executed for each pixel in the processing target image. Specifically, the operator setting unit 12 scans each pixel in the processing target image in units of one pixel in a predetermined order, so that a pixel to be processed (target) from among the pixels in the processing target image. Pixel) is selected sequentially. Then, for each target pixel that is sequentially selected in this way, a series of processing by the operator setting unit 12, the first conversion unit 13, the second conversion unit 14, and the post-processing unit 15 is executed, so that the target pixel The gradation value of the pixel is converted. Pixels whose tone values have been converted in this way (tone value conversion pixels) are pixels that constitute the output image. By executing such a series of processing for all the pixels in the processing target image, the gradation value of each pixel in the processing target image is converted, and as a result, an image that is clear and easy to view is obtained. Obtained as an output image.

  The operator setting unit 12 sets an operator composed of a plurality of pixels including the target pixel in the processing target image. Here, the target pixel is a pixel that is selected as a pixel to be processed by the above-described scanning process, and is a pixel that is a target for converting a gradation value in each of the first conversion unit 13 and the second conversion unit 14. is there. The operator is typically set as a rectangular area having the target pixel as a central pixel. However, the operator may be anything as long as it includes a target pixel and a plurality of pixels existing in the vicinity of the target pixel, and may be, for example, a circle or any other shape. In the present embodiment, as an example, the operator setting unit 12 sets, as an operator, a rectangular area made up of 16 × 16 256 pixels with the target pixel as the central pixel. For example, when a pixel in contact with a boundary such as an upper side, a lower side, a left side, or a right side of the processing target image is set as a target pixel, an operator having the target pixel as a central pixel cannot be set. In this case, the operator setting unit 12 may exclude pixels that are in contact with the boundary of the processing target image from the target whose tone value is to be converted. Or the operator setting part 12 may set the operator of the arbitrary shapes suitable for these pixels.

  The first conversion unit 13 and the second conversion unit 14 are means for converting the gradation value of the target pixel based on the gradation value of each pixel in the operator set by the operator setting unit 12 by different processing methods. is there. Here, the original gradation value of the target pixel may match the converted gradation value. Therefore, the “gradation value conversion” here means not only changing the gradation value of the target pixel to a gradation value different from the original gradation value, but also the converted gradation as a result of the conversion process. This includes the case where the value matches the original gradation value.

  First, the first conversion unit 13 will be described. The first conversion unit 13 converts the gradation value of the target pixel by executing processing based on the same concept as the gain application processing by the image quality adjustment unit 111 described above for each operator. The conversion processing of the first conversion unit 13 is different from the gain application processing by the image quality adjustment unit 111 that is uniformly executed for the entire input image in that the conversion processing is performed individually for each operator. The first conversion unit 13 includes a parameter extraction unit 131 and a gradation value conversion unit 132 as components for executing the conversion process.

  Based on the gradation value of each pixel in the operator set by the operator setting unit 12, the parameter extraction unit 131 sets the minimum gradation value min indicating the minimum value of the gradation value of each pixel and the gradation value of each pixel. And a maximum gradation value max indicating the maximum value of. Although the extraction method by the parameter extraction unit 131 is arbitrary, in the present embodiment, as an example, the parameter extraction unit 131 extracts the minimum gradation value min and the maximum gradation value max by a circuit described later (see FIG. 5). Although described later in detail, the parameter extraction unit 131 can extract the minimum gradation value min and the maximum gradation value max based on a histogram generated by the aggregation unit 141 described later. Further, the parameter extraction unit 131 may extract the minimum gradation value min and the maximum gradation value max by executing a comparison operation (sorting process) of the gradation values of each pixel in the operator by software processing, for example. Good.

The gradation value conversion unit 132 determines the gain G based on the minimum gradation value min and the maximum gradation value max extracted by the parameter extraction unit 131, and applies the gain G to the gradation value Vi of the target pixel. As a result, the gradation value after conversion (first gradation value after conversion) V1 of the target pixel is determined. In the present embodiment, as an example, the gradation value conversion unit 132 calculates the converted gradation value V1 from the gradation value Vi of the target pixel by executing calculations according to the following equations (4) and (5). . That is, as shown in the following formula (4), the gradation value conversion unit 132 sets the gradation resolution Nmax (256 in the case of 8 bits) of the processing target image to the maximum gradation value max and the minimum gradation value min. The gain G is calculated by dividing by the difference (max−min). Then, the gradation value conversion unit 132 multiplies the difference (Vi−min) between the gradation value Vi of the target pixel and the minimum gradation value min by the gain G, thereby obtaining the converted gradation value V2 of the target pixel. calculate. Thereby, the converted gradation value V1 can be easily calculated using a predetermined calculation formula (the following formulas (4) and (5)).
G = Nmax / (max−min) (4)
V1 = (Vi−min) × G (5)

  Here, the gradation value conversion unit 132 determines the gain G and the converted gradation value V1 by the above equations (4) and (5) in order to adjust the effect level of the conversion of the gradation value. Before the adjustment process, a predetermined adjustment value (offset) may be added to or subtracted from at least one of the minimum gradation value min and the maximum gradation value max. Here, the effect level is an index indicating the degree of sharpening by the above-described gradation value conversion. For example, the darkness (or brightness) of the original image (the processing target image before gradation value conversion) is represented. Indicates the strength to enhance.

  For example, when the adjustment value dmax (> 0) is added to the maximum gradation value max without adjusting the minimum gradation value min (that is, “max” is changed to “max + dmax” in the above formulas (4) and (5)). When the gradation value V1 is calculated by replacement, the effect level of the gradation value conversion described above can be adjusted in a direction in which darkness is enhanced. This is due to the following reason. That is, by using max + dmax instead of the actual maximum gradation value max, the gain G calculated by the above equation (4) is adjusted to be reduced. For this reason, the converted gradation value V1 calculated by the above equation (5) is adjusted in a direction that is smaller (darkness is more pronounced) than when the adjustment value dmax is not added to the maximum gradation value max.

  On the other hand, when the adjustment value dmin (> 0) is subtracted from the minimum gradation value min without adjusting the maximum gradation value max (that is, “min” in the above equations (4) and (5) is “min−dmin”). When the gradation value V1 is calculated instead of “”, the effect level of the conversion of the gradation value can be adjusted in the direction in which the brightness is enhanced. This is due to the following reason. That is, by using min-dmin instead of the actual minimum gradation value min, adjustment is made in the direction in which “Vi-min” in the above equation (5) increases. For this reason, the converted gradation value V2 calculated by the above equation (5) is adjusted to be larger (brightness is enhanced) than when the adjustment value dmin is not subtracted from the minimum gradation value min.

  According to the configuration in which the adjustment is performed as described above, for example, by applying the adjustment values dmin and / or dmax according to the user's preference, image characteristics, and the like to the minimum gradation value min and / or the maximum gradation value max. The degree of sharpening (for example, the degree of darkness or lightness) can be adjusted. Here, the adjustment value dmax or the adjustment value dmin can be regarded as a movement range for moving the maximum gradation value max or the minimum gradation value min in the range from the gradation value 0 to the gradation resolution Nmax. Accordingly, the effect level (adjustment value dmax or movement width based on adjustment value dmin) can be adjusted at the maximum number of steps that matches the gradation resolution Nmax. For example, when the gradation resolution Nmax is 8 bits (= 256), the effect level can be adjusted in 256 steps.

  Further, the adjustment value dmax (or dmin) may be, for example, a value common to each pixel of the processing target image (for example, a fixed value set in advance according to the user's preference). However, in this case, the influence of the adjustment in the former case is larger than in the latter case when the distribution width (max-min) of the gradation value of each pixel in the operator is small and when the distribution width is large. Will become bigger. Specifically, since the adjustment width for the distribution width is larger in the former case than in the latter case, the influence of the adjustment is greater. Therefore, when the adjustment value is a fixed value, there is a possibility that the adjustment is not properly performed depending on the distribution of gradation values of each pixel in the operator. Therefore, the gradation value conversion unit 132 calculates a value calculated according to the distribution of gradation values of each pixel in the operator (for example, a predetermined ratio for the difference between the maximum gradation value max and the minimum gradation value min). The multiplied value or the like) may be the adjustment value dmax (or dmin). In this way, the adjustment value can be variably set according to the distribution of gradation values of each pixel in the operator, and the adjustment value dmax for each pixel of the processing target pixel (that is, the target pixel in each operator). The magnitude of the adjustment by (or dmin) can be made constant.

  The gradation value conversion unit 132 determines the converted gradation value V1 of the target pixel by the above-described calculation, and outputs the determined gradation value V1 to the post-processing unit 15.

  Next, the 2nd conversion part 14 is demonstrated. The second conversion unit 14 generates a histogram of gradation values of each pixel in the operator, and executes a process of adding or subtracting the number of pixels of each gradation value from one end of the histogram to the gradation value of the target pixel. Thus, the gradation value of the target pixel is converted. The conversion method performed by the second conversion unit 14 is a method classified as so-called histogram flattening. The second conversion unit 14 includes a counting unit 141 and a gradation value conversion unit 142 as components for executing the conversion process.

  The totalization unit 141 acquires the gradation value of each pixel in the operator set by the operator setting unit 12, and based on the gradation value of each pixel, 0 to a natural number N (gradation resolution Nmax-1). A histogram indicating the number of pixels of each gradation value is generated. For example, the totalization unit 141 scans each pixel in the operator in a predetermined order in units of one pixel, and executes a counting process that increases the number of gradation values of the operation target pixel by one. Alternatively, the totalization unit 141 may acquire the gradation value of each pixel in the operator in parallel and count the number of each gradation value. Thereby, a histogram indicating the number of pixels of each gradation value is generated. For example, when the gradation resolution Nmax is 256, the histogram is information in which the corresponding number of pixels X0 to X255 is associated with each gradation value from the gradation value 0 to the gradation value 255. The histogram generated by the totalization unit 141 and the gradation value Vi of the target pixel are transferred to the gradation value conversion unit 142.

  The gradation value conversion unit 142 adds a new gradation value V2 (by adding the number of pixels of each gradation value from the gradation value 0 to the gradation value Vi of the target pixel in the histogram generated by the totalization unit 141. (Gradation value after the second conversion) is calculated, and the gradation value Vi of the target pixel is converted into the new gradation value V2. The gradation value conversion unit 142 performs the above-described arithmetic processing using, for example, a logic circuit configured in the FPGA 106.

  The gradation value conversion unit 142 determines the converted gradation value V2 of the target pixel as described above, and outputs the determined gradation value V2 to the post-processing unit 15.

  Here, the parameter extraction unit 131 is configured so that the gradation value conversion unit 142 increases each gradation value from one end of the histogram indicating the gradation value 0 or gradation value N to the other end of the histogram for addition or subtraction of the number of pixels. In parallel with the process of referring to the number of pixels, the minimum gradation value min and the maximum gradation value max may be extracted by referring to the number of pixels of each gradation value from one end to the other end of the histogram. . Specifically, the parameter extraction unit 131 simultaneously refers to the number of pixels having the same gradation value when the gradation value conversion unit 142 refers to the number of pixels of each gradation value from one end of the histogram to the other end. . When the gradation value conversion unit 142 refers to each pixel number from the gradation value 0 toward the gradation value N for addition of the number of pixels, the parameter extraction unit 131 determines that the number of pixels other than 0 is The gradation value detected first is determined as the minimum gradation value min, and the gradation value in which the number of pixels other than 0 is detected last is determined as the maximum gradation value max. On the other hand, when the gradation value conversion unit 142 refers to each pixel number from the gradation value N toward the gradation value 0 for subtraction of the number of pixels, the parameter extraction unit 131 determines that the number of pixels other than 0 is The gradation value detected first is determined as the maximum gradation value max, and the gradation value in which the number of pixels other than 0 is detected last is determined as the minimum gradation value min.

  According to such a configuration, the process by the parameter extraction unit 131 and the process by the tone value conversion unit 142 can be executed in parallel. Thereby, the processing efficiency can be improved and the processing configuration (circuit configuration) can be simplified. Specifically, the circuit configuration can be simplified as in the example of the circuit described later (FIGS. 5 and 6).

  The post-processing unit 15 converts the gradation value V 0 of the target pixel converted by the pre-processing unit 11, the gradation value V 1 of the target pixel converted by the gradation value conversion unit 132, and the gradation value conversion unit 142. Based on the gradation value V2 of the target pixel, post-processing for determining a gradation value to be finally output is executed. The post-processing unit 15 includes a mixing unit 151 and a mixing ratio adjusting unit 152 as components for executing post-processing.

The mixing unit 151 finally outputs the gradation value Vo calculated by adding the gradation value V0, the gradation value V1, and the gradation value V2 at a predetermined mixing ratio (R0: R1: R2). Output as the gradation value of the target pixel. The mixing unit 151 can determine the gradation value Vo, for example, by executing a calculation process of the following equation (6). In the following formula (6), R0, R1, and R2 are integer values of 0 or more and 1 or less, respectively, and satisfy “R0 + R1 + R2 = 1”. Here, R0 indicates a ratio at which the gradation value V0 (that is, the adjustment result by the image quality adjustment unit 111) is reflected in the final gradation value Vo. R1 represents a ratio at which the gradation value V1 (that is, the adjustment result by the first conversion unit 13) is reflected in the final gradation value Vo. R2 indicates a ratio at which the gradation value V2 (that is, the adjustment result by the second conversion unit 14) is reflected in the final gradation value Vo.
Vo = V0 × R0 + V1 × R1 + V2 × R2 (6)

  The mixing ratio (R0, R1, R2) in the above formula (6) may be manually set according to the user's preference, or may be automatically adjusted according to the distribution of gradation values within the operator. . In this embodiment, as an example, a mixing ratio adjusting unit 152 for automatically adjusting the mixing ratio according to the distribution of gradation values in the operator is provided. For example, the mixing ratio adjustment unit 152 acquires the histogram generated by the totalization unit 141, and appropriately sets the mixing ratio (R0, R1, R2) based on the distribution of gradation values in the operator indicated in the histogram. To do.

  For example, when the distribution of gradation values in the operator is biased toward a specific gradation value, that is, the number of pixels of a specific gradation value is the number of pixels in the operator (the operator is a 16 × 16 rectangle). In the case of a region, when the image is matched with 256), if the sharpening by the second conversion unit 14 described above is executed, the tone value V2 after the sharpening becomes an extreme value of 0 or 255. May not be able to obtain a properly converted image. Therefore, the mixture ratio adjustment unit 152 does not use the conversion result (tone value V2) by the second conversion unit 14 when the distribution of the tone values in the operator is biased toward a specific tone value. In order to do so, R2 may be set to zero.

  Further, when the gradation value distribution in the operator is almost flat, the image converted by the second conversion unit 14 may fluctuate (noise), which may be difficult to view. Therefore, the mixture ratio adjustment unit 152 determines whether or not the gradation value distribution in the operator is flat based on a predetermined criterion. If it is determined that the distribution is flat, R2 is determined not to be flat. It may be set to a value lower than the value set in the case of being performed. Thereby, in a situation where there is a possibility that noise may be generated by the conversion by the second conversion unit 14, the influence of the conversion result (tone value V2) by the second conversion unit 14 can be reduced, and the occurrence of fluctuation is suppressed. be able to.

  Note that the mixing unit 151 does not necessarily reflect all the gradation values V0, V1, and V2 in the final gradation value Vo. The mixing unit 151 may output the final gradation value Vo, for example, by adding the gradation value V1 and the gradation value V2 with a predetermined mixing ratio. In this case, in the above equation (6), R0 is set to 0, and the adjustment result (tone value V0) by the preprocessing unit 11 is not reflected at all in the final tone value Vo. Similarly, R2 may be set to 0 when the conversion result (tone value V2) by the second converter 14 is not reflected in the final tone value Vo. In this case, the second conversion unit 14 can be omitted from the configuration of the image processing apparatus 1. However, the gradation value V1 obtained by the first conversion unit 13 (a conversion result obtained by so-called local (operator unit) gain adjustment) and the gradation value V2 obtained by the second conversion unit 14 By mixing with (the conversion result obtained by so-called histogram flattening), it becomes possible to obtain an easy-to-view image in which each conversion result is reflected in a balanced manner. For example, an image that has only been subjected to histogram flattening (ie, an image that reflects only the gradation value V2) may have a sharpening level that is too strong to emphasize noise. In such a case, it is possible to obtain an image in which the influence of noise is reduced by mixing the conversion results (tone value V1) obtained by local gain adjustment.

  Hereinafter, an example of a circuit that performs processing by the parameter extraction unit 131, the gradation value conversion unit 132, the gradation value conversion unit 142, and the mixing unit 151 will be described with reference to FIGS. Here, as an example, it is assumed that the gradation resolution Nmax of the processing target image is adjusted to 8 bits (= 256) by the resolution adjustment unit 112. In this case, the gradation of each pixel of the processing target image takes any value from gradation value 0 to gradation value 255. Here, for the sake of simplicity, it is assumed that the gradation value V0 converted by the preprocessing unit 11 is not used (not mixed in the mixing unit 151).

  First, an outline of the operation of the circuit shown in FIG. 4 will be described. The circuit shown in FIG. 4 is a circuit in which Nmax-1 (255 in this case) adder modules A1 to A255 are configured in multiple stages, and the processes of the adder modules A1 to A255 are sequentially executed. ing. In this circuit, from the addition module Ak (k = 1 to 254) in the previous stage to the addition module Ak + 1 in the subsequent stage, the addition result ak in the previous addition module Ak and the subtraction result bk of the gradation value Vi of the target pixel are sequentially obtained. Communicated. Finally, the gradation value V2 is output from the addition module A255 to the mixing unit 151 (for example, a circuit for executing the calculation of the above formula (6)).

  Further, the minimum gradation value mink and the maximum gradation value maxk at the time of processing in the addition module Ak, and the gradation value Vi of the target pixel are sequentially transmitted from the previous addition module Ak to the subsequent addition module Ak + 1. Finally, from the addition module A255 to the gradation value conversion unit 132 (a circuit for executing the calculations of the above equations (4) and (5)), the determined minimum gradation value min and maximum gradation value max, and A gradation value Vi is output. Thereafter, the gradation value conversion unit 132 calculates the gradation value V1 by executing the calculations of the above formulas (4) and (5) based on the min, max, and Vi received from the addition module A255. The gradation value V1 is output to the mixing unit 151.

  Finally, based on the gradation value V2 received from the addition module A255 and the gradation value V1 received from the gradation value converter 132, the mixing unit 151 calculates the above equation (6) (here, R0 = 0). ) To calculate the final gradation value Vo.

  Next, details of the processing of the addition module will be described with reference to FIG. FIG. 5 is a diagram showing the configuration of the first and second addition modules A1 and A2 of the circuit shown in FIG.

  First, the part in which the addition module operates as the gradation value conversion unit 142 will be described.

  The first addition module A1 includes registers A11 to A13, a zero register A14 in which 0 is stored, a subtracter A15, a selector A16, and an adder A17. The registers A11 and A12 store the pixel number X0 of the gradation value 0 and the pixel number X1 of the gradation value 1 acquired from the aggregation unit 141, respectively, and the target pixel acquired from the aggregation unit 141 is stored in the register A13. Are stored. The subtracter A15 subtracts one gradation value Vi of the target pixel stored in the register A13. The selector A16 compares the subtraction result b1 (= Vi-1), which is the value after subtraction by the subtractor A15, with 0, and if the subtraction result b1 is greater than 0, connects the register A12 to the adder A17. When the subtraction result b1 is 0 or less, the zero register A14 is connected to the adder A17. The adder A17 adds the pixel number X0 of the gradation value 0 stored in the register A11 and the value (pixel number X1 or 0) stored in the register A12 or zero register A14 connected by the selector A16, The addition result a1 is transferred to the second addition module A2.

  In the arithmetic processing of the first addition module A1, when the gradation value Vi of the target pixel is 2 or more, the subtraction result b1 by the subtracter A15 becomes larger than 0, so that the register A12 is added to the adder A17 by the selector A16. And a value (X0 + X1) obtained by adding the number of pixels X0 having the gradation value 0 and the number X1 of the gradation value 1 is passed to the second addition module A2 as the addition result a1. On the other hand, when the gradation value Vi of the target pixel is 1 or less, since the subtraction result b1 by the subtracter A15 is 0 or less, the zero register A14 is connected to the adder A17 by the selector A16, and the gradation value 0 A value obtained by adding the number of pixels X0 and 0 (that is, X0 stored in the register A11) is directly transferred to the second addition module A2 as the addition result a1.

  Similar to the first addition module A1, the second addition module A2 includes registers A21 to A23, a zero register A24 in which 0 is stored, a subtractor A25, a selector A26, and an adder A27. The register A21 stores the addition result a1 by the first addition module A1. In the register A22, the pixel value X2 of the gradation value 2 is stored in synchronization with the timing at which the arithmetic processing in the first addition module A1 is completed by the delay processing in the delay circuit Z. The register A23 stores the subtraction result b1 by the subtracter A15. The subtracter A25 subtracts one subtraction result b1 stored in the register A23. The selector A26 compares the subtraction result b2 (= b1-1), which is the value after subtraction by the subtractor A25, with 0, and if the subtraction result b2 is greater than 0, connects the register A22 to the adder A27. If the subtraction result b2 is 0 or less, the zero register A24 is connected to the adder A27. The adder A27 adds the addition result a1 stored in the register A21 and the value (number of pixels X2 or 0) stored in the register A22 or the zero register A24 connected by the selector A26, and the addition result a2 is added to the first result. 3 to the addition module A3.

  In the arithmetic processing of the second addition module A2, when the gradation value Vi of the target pixel is 3 or more, the subtraction result b2 by the subtractor A25 becomes larger than 0, so that the register A22 is added to the adder A27 by the selector A26. And the value (X0 + X1 + X2) obtained by adding the addition result a1 (in this case, X0 + X1) stored in the register A21 and the number of pixels X2 of the gradation value 2 is passed to the third addition module A3. On the other hand, when the gradation value Vi of the target pixel is 2 or less, since the subtraction result b2 by the subtracter A25 is 0 or less, the zero register A24 is connected to the adder A27 by the selector A26 and stored in the register A21. The result obtained by adding the addition result a1 and 0 (that is, a1 stored in the register A21) is directly transferred to the third addition module A3 as the addition result a2.

  Thereafter, in the third to 255th addition modules A3 to A255, the same processing as that of the first and second addition modules A1 and A2 described above is executed in series. According to this circuit, in the addition module that executes the arithmetic processing after the number of pixels of each gradation value from gradation value 0 to “gradation value Vi−1 of the target pixel” is added, the subtraction result by the subtractor Becomes 0 or less, and since the zero register is connected to the adder by the selector, the addition of the number of pixels is stopped. Therefore, in the above circuit, the addition result (gradation value V2) finally output from the 255th addition module A255 is the gradation value from gradation value 0 to "gradation value Vi-1 of the target pixel". As a result, the number of pixels is added.

  In addition, in the determination process of the selector in each addition module, whether or not 0 is included in the boundary condition can be arbitrarily determined. For example, in the determination process of the selector in each addition module, when the subtraction result by the subtracter is less than 0, a zero register is connected to the adder, and when the subtraction result by the subtractor is 0 or more, the corresponding gradation A register storing a value may be connected to the adder. In this case, the addition result (gradation value V2) output from the 255th addition module A255 is the result of adding the number of pixels of each gradation value from the gradation value 0 to “the gradation value Vi of the target pixel”. Become. As described above, how the boundary condition of the determination process of the selector in each addition module is an arbitrary setting item. Therefore, in this specification, from the gradation value 0 to “the gradation value Vi of the target pixel” or “ Collectively, the number of pixels of each gradation value up to “the gradation value Vi-1 of the target pixel” is simply “the number of pixels corresponding to each gradation value from the gradation value 0 to the gradation value Vi of the target pixel”. That's it.

  In addition, the above circuit is configured to sequentially add the number of pixels of each gradation value from gradation value 0 to gradation value Vi of the target pixel. As the maximum gradation value 255, a circuit modified to sequentially subtract the number of pixels of each gradation value from the gradation value 255 to the gradation value Vi of the target pixel may be used. That is, the gradation value conversion unit 142 may calculate a new gradation value by subtracting from 255 the number of pixels of each gradation value from the gradation value 255 to the gradation value Vi of the target pixel. The circuit that executes such processing can also output the result of adding the number of pixels of each gradation value from the gradation value 0 to the gradation value Vi of the target pixel, as in the above-described circuit.

  Next, the part where the addition module operates as the parameter extraction unit 131 will be described. In the present embodiment, as an example, in order to simplify the circuit configuration, the gradation value 0 is excluded from the candidates for the minimum gradation value min.

  As shown in FIG. 5, as a component for operating as the parameter extraction unit 131, the first addition module A1 includes a minimum value register A18 and a maximum value register A19. Similarly, the second addition module A2 includes a minimum value register A28 and a maximum value register A29. Hereinafter, a mechanism for obtaining the minimum gradation value min and the maximum gradation value max by these circuit elements will be described.

  First, a mechanism for obtaining the minimum gradation value min will be described. The first addition module A1 determines whether or not the number of pixels X1 of the gradation value 1 stored in the register A12 is greater than 0 by a minimum value detection mechanism (not shown). When it is determined that the number of pixels X1 is greater than 0, the addition module A1 uses a value indicating the number of stages of the addition module A1 (here, “1”) as a provisional minimum value min1 indicating a provisional minimum gradation value. Is stored in the minimum value register A18. On the other hand, when it is not determined that the pixel number X1 is greater than 0 (that is, when X1 = 0), the addition module A1 stores “0” as the provisional minimum value min1 in the minimum value register A18. The provisional minimum value min1 stored in the minimum value register A18 is transferred to the second addition module A2 at the subsequent stage and stored in the minimum value register A28.

  The second addition module A2 determines whether or not the provisional minimum value min1 stored in the minimum value register A28 is greater than 0 by a minimum value detection mechanism (not shown). Here, the provisional minimum value min1 being larger than 0 means that a pixel having a gradation value smaller than the gradation value 2 exists. Therefore, when the provisional minimum value min1 is larger than 0, the addition module A2 does not rewrite the value of the provisional minimum value min1 stored in the minimum value register A28. On the other hand, the provisional minimum value min1 being “0” means that there is no pixel having a gradation value smaller than the gradation value 2. Therefore, when the temporary minimum value min1 is “0”, the addition module A2 further determines whether or not the number of pixels X2 of the gradation value 2 stored in the register A22 is greater than zero. If it is determined in this determination that the number of pixels X2 is greater than 0, the addition module A2 uses the provisional minimum value min1 stored in the minimum value register A28 as a value indicating the number of stages of the addition module A2 (here, “2 ]). On the other hand, when it is not determined that the number of pixels X2 is greater than 0 (that is, when X2 = 0), the addition module A2 rewrites the value (0) of the provisional minimum value min1 stored in the minimum value register A28. Absent. After the above-described processing is executed, the provisional minimum value min1 stored in the minimum value register A28 is transferred to the subsequent third addition module A3 as the provisional minimum value min2.

  The third to 255th addition modules A3 to A255 are also provided with a minimum value detection mechanism and a minimum value register similar to those of the second addition module A2, and the same processing (minimum as the second addition module A2). Execute value register rewrite processing). With the above mechanism, the gradation value (that is, the minimum gradation value min) is stored in the minimum value register of the addition module as a provisional minimum value when a gradation value having the number of pixels larger than 0 is first detected. Is done. Then, the provisional minimum value is sequentially transmitted to the subsequent addition module without being rewritten. As a result, the minimum gradation value min is finally output to the gradation value conversion unit 132 by the 255th addition module A255.

  Next, a mechanism for obtaining the maximum gradation value max will be described. The first addition module A1 determines whether or not the number X1 of gradation values 1 stored in the register A12 is greater than 0 by a maximum value detection mechanism (not shown). When it is determined that the number of pixels X1 is greater than 0, the addition module A1 uses a value indicating the number of stages of the addition module A1 (here, “1”) as a provisional maximum value max1 indicating a provisional maximum gradation value. Is stored in the maximum value register A19. On the other hand, when it is not determined that the pixel number X1 is greater than 0 (that is, when X1 = 0), the addition module A1 stores “0” in the maximum value register A19 as the provisional maximum value max1. The provisional maximum value max1 stored in the maximum value register A19 is transferred to the second addition module A2 at the subsequent stage and stored in the maximum value register A29.

  The second addition module A2 determines whether or not the pixel number X2 of the gradation value 2 stored in the register A22 is greater than 0 by a maximum value detection mechanism (not shown). When the number of pixels X2 is greater than 0, the addition module A2 rewrites the provisional maximum value max1 stored in the maximum value register A29 to a value (here, “2”) indicating the number of stages of the addition module A2. On the other hand, when it is not determined that the pixel number X2 is greater than 0 (that is, when X2 = 0), the addition module A2 does not rewrite the value of the provisional maximum value max1 stored in the maximum value register A29. After the above-described processing is executed, the provisional maximum value max1 stored in the maximum value register A29 is transferred as the provisional maximum value max2 to the subsequent third addition module A3.

  The third to 255th addition modules A3 to A255 are also provided with a maximum value detection mechanism and a maximum value register similar to those of the second addition module A2, and the same processing (maximum) as the second addition module A2 is performed. Execute value register rewrite processing). With the above mechanism, the provisional maximum value is rewritten in the maximum value register of the addition module every time a gradation value having a number of pixels larger than 0 is detected. That is, the provisional maximum value is sequentially rewritten until no more gradation value having the number of pixels larger than 0 is found. As a result, the maximum gradation value max is finally output to the gradation value conversion unit 132 by the 255th addition module A255.

  As shown in FIG. 5, the second addition module A2 includes a register A20 for storing the gradation value Vi of the target pixel. Specifically, the gradation value Vi stored in the register A13 of the first addition module A1 is transferred to the second addition module A2 and stored in the register A20. Similarly to the second addition module A2, the third to 255th addition modules A3 to A255 are also provided with a register for storing the gradation value Vi, and the previous addition module is changed from the previous addition module via the register. The gradation value Vi is passed to As a result, the gradation value Vi of the target pixel is finally output to the gradation value conversion unit 132 by the 255th addition module A255.

  In the circuits shown in FIGS. 4 and 5, the processing by the parameter extraction unit 131 and the processing by the gradation value conversion unit 142 are executed in parallel in each addition module. Specifically, in the above-described circuit, a configuration for detecting a maximum value and a minimum value is incorporated in an addition module for executing processing by the gradation value conversion unit 142. In the above-described circuit, the minimum value register and the maximum value register in each addition module function as the parameter extraction unit 131 that extracts the minimum gradation value min and the maximum gradation value max. The parameter extraction unit 131 configured as described above uses the histogram generated by the totalization unit 141 (that is, the number of pixels X1 to X255 of each gradation value) to obtain the minimum gradation value min and the maximum gradation value max. Extract. According to this configuration, the minimum gradation value min and the maximum gradation value max can be extracted using the histogram necessary for the processing by the gradation value conversion unit 142, so that the entire processing configuration is simplified. be able to. Specifically, as illustrated in FIGS. 4 and 5, the circuit is configured to execute the process of extracting the minimum gradation value min and the maximum gradation value max and the process of the gradation value conversion unit 142 in parallel. Therefore, the processing efficiency can be improved and the circuit configuration can be simplified.

  Subsequently, the operation of the image processing apparatus 1 will be described with reference to FIG.

  First, the preprocessing unit 11 acquires each frame of a video shot by a monitoring camera or the like as an input image, and executes preprocessing for converting the gradation value of each pixel of the input image based on the characteristics of the input image. (Step S1). Subsequently, the processing from step S2 to step S7 is executed for each pixel of the processing target image after the gradation value of each pixel is converted by the preprocessing unit 11.

  Specifically, first, an operator composed of a plurality of pixels including the target pixel in the processing target image is set by the operator setting unit 12 (step S2). Subsequently, the aggregation unit 141 acquires the gradation value of each pixel in the operator, and generates a histogram indicating the number of pixels corresponding to each gradation value from 0 to a natural number N based on the gradation value of each pixel. (Step S3).

  Subsequently, for example, the parameter extraction unit 131 realized as the circuit illustrated in FIGS. 4 and 5 extracts the maximum gradation value max and the minimum gradation value min (step S4). Thereafter, the gradation value conversion unit 132 converts the maximum gradation value max and the minimum gradation value min extracted by the parameter extraction unit 131 and the gradation value Vi of the target pixel into the above-described formulas (4) and (5). By inputting and executing the calculation, the gradation value V1 is determined (step S5). In parallel with the processing of Step S4 and Step S5, the gradation value conversion unit 142 adds the number of pixels of each gradation value from the gradation value 0 to the gradation value Vi of the target pixel (or The gradation value V2 is determined by subtracting the number of pixels of each gradation value from the gradation value 255 to the gradation value Vi of the target pixel from 255 (step S6).

  Subsequently, the post-processing unit 15 performs post-processing (step S7). Specifically, the mixing unit 151 converts the gradation value V0 of the target pixel converted by the preprocessing unit 11, the gradation value V1 of the target pixel converted by the gradation value conversion unit 132, and the gradation value conversion. The gradation value Vo of the target pixel, which is the final conversion result, is calculated by adding the gradation value V2 of the target pixel converted by the unit 142 with a predetermined mixing ratio (R0, R1, R2). By this post-processing (mixing process), the gradation value Vo of the target pixel whose sharpening intensity is appropriately adjusted according to the user's preference, the illuminance distribution within the operator, or the like is output. By performing the processing from steps S2 to S7 for all the pixels in the processing target image, it is possible to obtain an appropriately sharpened image.

  In the image processing apparatus 1 described above, the conversion process for applying the gain G determined based on the minimum gradation value min and the maximum gradation value max of each pixel in the operator to the gradation value Vi of the target pixel in the operator. Is executed, and the gradation value V1 after conversion of the target pixel is determined. By executing the application of gain in units of operators as the target pixel for each pixel in the processing target image, an appropriate value determined depending on the distribution of gradation values of the respective pixels included in the operator for each operator. It is possible to achieve a degree of sharpening. Thereby, it is possible to obtain an easy-to-see image in which the degree of sharpening is appropriately adjusted. Further, by adding the above-described gradation values V0, V2 and the like at a predetermined mixing ratio to the gradation value V1 obtained in this way, an image that is easier to see and improved according to the user's preference and the like is obtained. It becomes possible.

  The present invention has been described in detail based on the embodiments. However, the present invention is not limited to the above embodiment. The present invention can be variously modified without departing from the gist thereof. For example, the gradation value conversion unit 132 may convert the gradation value Vi of the target pixel using a calculation expression other than the expressions (4) and (5).

  In the above embodiment, the circuit example (FIGS. 4 and 5) in which the processing by the parameter extraction unit 131 is executed concurrently with the processing by the gradation value conversion unit 142 has been described. The process may be performed as a separate process. FIG. 7 shows another example of a circuit that executes the processing of the first conversion unit 13. In the circuit shown in FIG. 7, the parameter extraction unit 131 determines the magnitude relationship between two input values, and outputs the input value determined to be large and the input value determined to be small to respective predetermined output destinations. It comprises a plurality of large and small sorters configured as described above.

  Specifically, 128 size selectors B1 (half the number of pixels included in the operator) are arranged in the first stage, and the first stage size selector in the subsequent stage (second stage). As many size sorters as B1 are arranged. The second-stage size selector is determined to be small by the 64 size selectors B21 for comparing the size relationships between those determined to be large by the first-size selector B1 and the size selector B1. It consists of 64 size selectors B21 for comparing the size relationship between the two.

  In the subsequent stage (third stage) of the second stage size selectors B21 and B22, half (64 pieces) of the size selectors of the second stage size selectors B21 and B22 are arranged. The The third-stage size selector has 32 size selectors B31 for comparing the size relationships between those determined to be large by the second-stage 64 size selectors B21, and the second-stage size selector It consists of 32 size selectors B32 that compare the size relationships between those determined to be small by 64 size selectors B22. Similarly, in the fourth and subsequent stages, the magnitude relations between those determined to be large in the previous stage are compared so that the total number of the large and small sorters arranged is half the total number of the large and small sorters in the previous stage. The size selectors B42, B52, B62, B72, and B82 for comparing the size relationship between the size selectors B41, B51, B61, B71, and B81 and those determined to be small in the previous stage are arranged.

  The operation of the circuit shown in FIG. 7 will be described below. First, each of the first and second size selectors B21 is selected not to overlap among 256 pieces of pair information in which each gradation value in the operator and the number of pixels X0 to X255 of each gradation value are associated. Two pair information is input. Here, the input to the first-stage size selector B21 is given from, for example, a buffer circuit (not shown) that accumulates the information of the histogram generated by the counting unit 141. Hereinafter, the pair information of the gradation value k and the number of pixels Xk of the gradation value k is represented as [k, Xk] (k = 0 to 255).

  For example, the size selector B1 at the top of the first level in FIG. 7 accepts the pair information [0, X0] and the pair information [1, X1] as inputs, and the number of pixels of each input pair information. The magnitude relationship between (X0 and X1 in this case) is compared. The large / small sorter B1 is a subsequent large / small sorter that compares the magnitude relation between the pair information [1, X1] that is determined to be large (one X1 as an example here) that is determined to be large. The data is output to B21 (any one of 64 large and small sorters B21). On the other hand, the large / small sorter B1 is a subsequent large / small sorter that compares the magnitude relationship between the pair information [0, X0] that is determined to be small in the pair information [0, X0] associated with the smaller one (here, X0 as an example). The data is output to B22 (any one of the 64 large and small sorters B22).

  As described above, the maximum gradation value max candidates are narrowed down to 128, which is half of the number of pixels included in the operator (256 as an example here), by the processing of the first and second size selector B1. Then, the 128 candidates are compared in size by the second size selector B21, whereby the candidates for the maximum gradation value max are further reduced to 64, which is a half. In this way, the magnitude comparison is advanced from the previous stage to the subsequent stage, so that the magnitude selector B81 in the eighth stage finally outputs the maximum gradation value max to the gradation value conversion unit 132.

  Similarly, the candidate of the minimum gradation value min is narrowed down to 128, which is half of the number of pixels included in the operator, by the processing of the first and the second size selector B1. Then, the 128 candidates are compared in size by the second size selector B22, whereby the candidates of the minimum gradation value min are further reduced to 64, which is half. Thus, the magnitude comparison is advanced from the preceding stage to the succeeding stage, so that the magnitude selector B82 in the eighth stage finally outputs the minimum gradation value min to the gradation value converting unit 132.

  In addition, the buffer circuit (not shown) includes a delay circuit so that the gradation value Vi of the target pixel is output to the gradation value conversion unit 132 at the same timing as that of the eighth stage size selectors B81 and B82. The gradation value Vi is output to the gradation value conversion unit 132 via Z. Finally, the gradation value conversion unit 132 receives the maximum gradation value max output from the large / small selector B81, the minimum gradation value min output from the large / small selector B82, and the delay circuit Z. The gradation value Vi is received, and the gradation value V2 is calculated by calculation using the above equations (4) and (5). The tone value V2 calculated in this way is output to the mixing unit 151.

DESCRIPTION OF SYMBOLS 1 ... Image processing apparatus, 11 ... Pre-processing part, 111 ... Image quality adjustment part, 112 ... Resolution adjustment part, 12 ... Operator setting part, 13 ... 1st conversion part, 131 ... Parameter extraction part, 132 ... Tone value conversion part , 14 ... second conversion unit, 141 ... aggregation unit, 142 ... gradation value conversion unit (second gradation value conversion unit), 15 ... post-processing unit, 151 ... mixing unit, 152 ... mixing ratio adjustment unit, 101 ... CPU, 102 ... RAM, 103 ... ROM, 104 ... input device, 105 ... communication device, 106 ... FPGA, 107 ... output device.

Claims (5)

A setting unit for setting an operator composed of a plurality of pixels including the target pixel in the processing target image;
Based on the gradation value of each pixel in the operator, the minimum gradation value indicating the minimum gradation value of each pixel and the maximum gradation value indicating the maximum gradation value of each pixel are extracted. A parameter extraction unit to perform,
A gain is determined based on the minimum gradation value and the maximum gradation value extracted by the parameter extraction unit, and the gain is applied to the gradation value of the target pixel to thereby convert the target pixel after conversion. A tone value conversion unit for determining a tone value;
An image processing apparatus comprising: The gradation value conversion unit calculates the gain by dividing a gradation resolution indicating the number of gradation values that can be expressed in the processing target image by a difference between the maximum gradation value and the minimum gradation value. Calculating a converted gradation value of the target pixel by multiplying the difference between the gradation value of the target pixel and the minimum gradation value by the gain;
The image processing apparatus according to claim 1. The gradation value conversion unit adds or subtracts a predetermined adjustment value to or from at least one of the minimum gradation value and the maximum gradation value before determining the gain and the converted gradation value. Run the
The image processing apparatus according to claim 1. A totalization unit that obtains a gradation value of each pixel in the operator and generates a histogram indicating the number of pixels corresponding to each gradation value from 0 to a natural number N based on the gradation value of each pixel;
In the histogram, by adding the number of pixels of each gradation value from gradation value 0 to the gradation value of the target pixel, or for each gradation value from gradation value N to the gradation value of the target pixel A second gradation value conversion unit that determines a second converted gradation value of the target pixel by subtracting the number of pixels from the value N;
A gradation value after conversion of the target pixel determined by the gradation value conversion unit and a gradation value after conversion of the target pixel determined by the second gradation value conversion unit are determined in advance. A mixing unit that outputs a gradation value obtained by adding together the obtained mixing ratio;
The image processing apparatus according to claim 1. The parameter extraction unit is configured such that each gradation from one end of the histogram to which the second gradation value conversion unit indicates gradation value 0 or gradation value N for addition or subtraction of the number of pixels from the other end of the histogram. In parallel with the process of referring to the number of pixels of the value, the minimum gradation value and the maximum gradation value are extracted by referring to the number of pixels of each gradation value from one end to the other end of the histogram.
The image processing apparatus according to claim 4.

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