JP2010198068A - Simulation device for image processing circuit, simulation method for image processing circuit, design method for image processing circuit, and simulation program for image processing circuit - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a simulation device of an image processing circuit for simplifying the qualitative and quantitative evaluation of the effects of image processing results by visualization. <P>SOLUTION: The simulation device 1 of an image processing for simulating the operation of the image processing circuit includes: an image processing module equipped with a function corresponding to the image processing circuit; a module execution means 63 for executing the image processing module, and for performing image processing to one or more input images; and a result grouping execution means 66 for executing grouping to the image data to which the image processing based on the image processing module executed by the module execution means 63 has been performed. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an image processing circuit simulation apparatus, an image processing circuit simulation method, an image processing circuit design method, an image processing circuit simulation program, and the like.

2. Description of the Related Art Conventionally, programs for simulating results of executing various functions are known for function evaluation and debugging of software systems that can execute a plurality of functions.
For example, the test sequencer described in Patent Document 1 is configured to include a management module and an execution module. When a new function is added to a test executive to be tested or a function is corrected, Proposals have been made to easily check whether or not the function interferes.

Further, in the software test apparatus described in Patent Document 2, an apparatus that interfaces with input and output to software to be verified and receives and evaluates an output group according to an operation procedure, setting contents, and the like has been proposed. .
Further, in the software component system described in Patent Document 3, pre-condition definition information indicating a state before executing another software component and post-condition definition information indicating a subsequent state are stored in the database in executing the software component. Aside, it has been proposed to accurately test software components.

Furthermore, in the image quality evaluation apparatus described in Patent Document 4, the image obtained by taking in the image is differentiated, the contour portion of the unevenness is revealed, and the image quality index obtained by using the area for each gradation value, A method for quantitatively evaluating the image quality of an inspection screen has been proposed.
Further, in the image quality evaluation method described in Patent Document 5, a method has been proposed in which, for example, contrast intensity is determined using a granularity test pattern to compare image quality between devices and image quality over time. .
Furthermore, in the image quality evaluation apparatus described in Patent Document 6, there has been proposed an apparatus that quantitatively evaluates an image using a gradation image whose gradation changes continuously.
Furthermore, in the image processing apparatus described in Patent Document 7, there has been proposed an apparatus that evaluates statistical properties of an image by measuring a histogram of vector components in an image detected from an object.

By the way, in an image display device such as a projector and an FPD (Flat Panel Display), an image process is performed on input image data to form an appropriate display image. Is expanding.
Therefore, it is possible to form an image processing circuit capable of performing multi-functional image processing by combining various image processing such as color conversion, resolution conversion, gamma conversion, etc. into partial image processing times that are chipped in units of image processing. Has been done.
Conventionally, when designing such an image processing circuit, a technique has been adopted in which partial image processing circuits are prototyped, combined with each other to form an image processing circuit and evaluated.

JP 2006-53924 A JP 2006-48310 A JP 2006-91944 A JP 2000-215310 A JP 2000-278722 A JP 2003-16443 A JP 2003-196666 A

However, the trial production of such a partial image processing circuit has a problem that not only error verification takes time but also the trial production cost increases.
In addition, there are a number of partial image processing circuits that are incorporated into the image processing circuit as functions are expanded even if they are actually incorporated into the image processing circuit, and it is determined whether the parameter setting in the image processing is effective. There is a problem that it is very difficult to do.
Furthermore, there is an error that appears only when parameters after image processing are combined, and it is very difficult to verify this.
In general, a display image formed by an image display device is composed of a large number of pixels. However, it is difficult to evaluate the results processed by the partial image processing circuit for each pixel. It cannot be applied to the evaluation of the image quality of the image after the image processing by the image processing apparatus.

  The present invention has been made in view of the technical problems as described above, and one of its purposes is an image processing circuit capable of facilitating qualitative and quantitative evaluation of the effect of visual image processing results. The object is to provide a simulation apparatus, a simulation method for an image processing circuit, a design method for an image processing circuit, a simulation program for an image processing circuit, and the like.

  (1) According to one aspect of the present invention, an image processing circuit simulation device that simulates an operation of an image processing circuit executes an image processing module having a function corresponding to the image processing circuit, and the image processing module. A module execution unit that performs the image processing on one or a plurality of input images, and a result group that performs grouping on the image data on which the image processing has been performed by the image processing module executed by the module execution unit And execution means.

  According to this aspect, since the image data after the image processing by the image processing module for one or a plurality of input images is grouped, qualitative and quantitative evaluation of the visual effect of the image processing becomes easy, Verification of the result image can be made more efficient. Furthermore, according to this aspect, it is possible to easily grasp the effect of changing the parameter applied to the image processing.

  (2) In another aspect of the invention, the result grouping execution unit includes the input image data of the original input image and the processed image obtained by performing image processing on the input image data by the image processing module. The grouping is executed based on the difference information with the data.

  According to this aspect, since the grouping is performed based on the difference information between the input image and the result image after the image processing, the grouping corresponding to the visual effect of the image processing can be realized by a simple arithmetic processing. It becomes like this.

  (3) In another aspect of the present invention, the image processing module includes a result grouping condition setting unit that sets a grouping condition for the image processing result of the image processing module, and the result grouping execution unit sets the result grouping condition. Based on the grouping condition set by the means, grouping is executed for each image data after image processing of the input image.

  According to this aspect, since grouping conditions can be set, qualitative and quantitative evaluation of visual effects of desired image processing is facilitated, and verification of result images can be made more efficient.

  (4) In another aspect of the present invention, the result grouping condition setting unit performs processing after image processing performed by the image processing module on the input image data of the original input image and the input image data. At least one of a calculation method for calculating difference information with image data, a method for specifying a pixel as a calculation target of the difference information, a method for counting the difference information, and a method for specifying a range for grouping the difference information Set.

  According to this aspect, since at least one of the calculation method, the method of specifying the pixel to be calculated, the counting method, and the range to be grouped can be set, the qualitative characteristics corresponding to the visual effect of the target image processing And quantitative evaluation can be made possible.

  (5) In another aspect of the present invention, the calculation method includes a difference in lightness between pixels to be calculated in the difference information, a difference in saturation and hue between the pixels, a color difference between the pixels, and At least one of edge value differences based on the input image data and the processed image data.

  According to this aspect, it becomes easy to qualitatively and quantitatively evaluate the effects of visual image processing such as gradation, color uniformity (color unevenness), and sharpness that are generally performed, and more efficiently verify the result image. It becomes possible to become.

  (6) In another aspect of the present invention, a plurality of image processing modules each having a function corresponding to each of a plurality of partial image processing circuits constituting the image processing circuit, and among the plurality of image processing modules, Module selecting means for selecting an image processing module to be executed, wherein the module executing means sequentially executes the image processing modules selected by the module selecting means, performs image processing of input image data, and outputs the result. The grouping execution means executes grouping on the image data that has been subjected to image processing by the plurality of image processing modules executed by the module execution means.

  According to this aspect, in addition to the above-described effects, when a plurality of image processes are combined, the image data subjected to the image processing by the plurality of image processing modules is grouped. The visual effects of typical image processing can be analyzed, and the optimum combination of parameters applied to each image processing can be easily found.

  (7) According to another aspect of the present invention, the image processing module includes a module execution procedure setting unit that sets an execution procedure of the image processing module selected by the module selection unit, and the module execution unit is the module execution procedure setting unit. According to the set execution procedure, the image processing modules selected by the module selection means are sequentially executed, and image processing of the input image data is performed.

  According to this aspect, since the image data after the image processing obtained by easily changing the order of the image processing and combining the plurality of image processing is grouped, the image processing that can obtain a desired image processing result The module selection and execution procedure can be easily found, the error verification time can be shortened, and the manufacturing cost of the image processing circuit can be reduced. In addition, according to this aspect, even if the types of partial image processing circuits constituting the image processing circuit increase, each execution order and optimum parameter selection can be performed reliably and easily. This makes it easy to verify errors that appear depending on the combination of parameters.

  (8) In another aspect of the invention, the plurality of image processing modules include at least a resolution conversion module, a color conversion module, and a gamma characteristic conversion module.

  According to this aspect, among various image processing, resolution conversion, color conversion, and gamma characteristic conversion include color conversion processing, sharpness processing, and contrast processing in the modules that execute each image processing. Even when there is a difference in image quality of the result image after image processing depending on the processing order, it is possible to find a combination of image processing modules that can obtain an optimum result image.

  (9) According to another aspect of the present invention, an image processing circuit simulation method for simulating the operation of an image processing circuit executes an image processing module having a function corresponding to the image processing circuit. Performing image processing on the input image, and performing grouping on the image data on which the image processing has been performed on the one or more input images.

  According to this aspect, since the image data after image processing by the image processing module for one or a plurality of input images is grouped, qualitative and quantitative evaluation of the visual effect of the image processing becomes easy, Verification of the result image can be made more efficient. Furthermore, according to this aspect, it is possible to easily grasp the effect of changing the parameter applied to the image processing.

  (10) In another aspect of the present invention, based on difference information between input image data of an original input image and post-processing image data obtained by performing image processing on the input image data by the image processing module. Perform the grouping.

  According to this aspect, since the grouping is performed based on the difference information between the input image and the result image after the image processing, the grouping corresponding to the visual effect of the image processing can be realized by a simple arithmetic processing. It becomes like this.

  (11) In another aspect of the present invention, the method includes a step of setting a grouping condition for image processing results of the image processing module, and the image processing is performed on an input image based on the set grouping condition. The grouping is executed for each image data for which.

  According to this aspect, the grouping condition can be set, so that the qualitative and quantitative evaluation of the visual effect can be easily performed for the desired image processing effect, and the verification of the result image can be made more efficient. become.

  (12) In another aspect of the present invention, difference information between the input image data of the original input image and the processed image data obtained by performing image processing on the input image data by the image processing module is calculated. At least one of a calculation method, a method for specifying a pixel that is a calculation target of the difference information, a method for counting the difference information, and a method for specifying a range in which the difference information is grouped is set.

  According to this aspect, since at least one of the calculation method, the method of specifying the pixel to be calculated, the counting method, and the range to be grouped can be set, the qualitative characteristics corresponding to the visual effect of the target image processing And quantitative evaluation can be made possible.

  (13) In another aspect of the invention, an image processing module to be executed is selected from among a plurality of image processing modules having a function corresponding to each of the plurality of partial image processing circuits constituting the image processing circuit. Including steps, the selected image processing modules are sequentially executed, image processing of input image data is performed, and grouping is performed on image data that has been subjected to image processing by a plurality of image processing modules.

  According to this aspect, in addition to the above-described effects, when a plurality of image processes are combined, the image processing results of a plurality of image processing modules are grouped, so that qualitative and quantitative image processing can be performed. The visual effect can be analyzed, and the optimum combination of parameters applied to each image processing can be easily found.

  (14) According to another aspect of the present invention, after the image processing circuit design method performs the above-described image processing circuit simulation method to obtain a combination of image processing modules, a part of the image processing circuit A combination of image processing circuits is determined.

  According to this aspect, since the image processing results obtained by combining the plurality of image processing by simply changing the order of the image processing are grouped, the image processing module that obtains the desired image processing results can be obtained. The selection and execution procedure can be easily found, the error verification time can be shortened, and the manufacturing cost of the image processing circuit can be reduced. In addition, according to this aspect, even if the types of partial image processing circuits constituting the image processing circuit increase, each execution order and optimum parameter selection can be performed reliably and easily. This makes it easy to verify errors that appear depending on the combination of parameters.

  (15) In another aspect of the present invention, an image processing circuit simulation program causes a computer to execute any one of the image processing circuit simulation methods described above.

  According to this aspect, it is possible to provide a simulation program for an image processing circuit that can facilitate qualitative and quantitative evaluation of the effect of visual image processing results.

The block diagram of the structural example of the simulation apparatus which concerns on one Embodiment of this invention. The figure which shows an example of the screen displayed on the display of FIG. FIG. 4 is an explanatory diagram of selection and execution procedures of an image processing module to be written on a memory. The figure which shows an example of the result grouping condition setting screen displayed on a display. The flowchart of the example of a process of the simulation apparatus in this embodiment. The flowchart of the process example of the result grouping condition setting process in this embodiment. The flowchart of the process example of the result grouping process in this embodiment. FIG. 8A to FIG. 8E show examples of parameter files. FIG. 9A to FIG. 9C are explanatory diagrams of parameters in FIG. 8A to FIG. Explanatory drawing of the operation example of this embodiment. Explanatory drawing of the effect of the simulation apparatus in this embodiment.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. The embodiments described below do not unduly limit the contents of the present invention described in the claims. Moreover, not all of the configurations described below are indispensable configuration requirements for solving the problems of the present invention.

  FIG. 1 shows a block diagram of a configuration example of a simulation apparatus according to an embodiment of the present invention.

The simulation device 1 is configured as a computer including an arithmetic processing device 2 and a memory 3. That is, the arithmetic processing device 2 reads out the program stored in the memory 3 and executes processing using the program and data stored in the memory 3, thereby realizing a simulation of the operation of the image processing circuit. Alternatively, the arithmetic processing device 2 performs arithmetic processing on the data stored in the memory 3 using a dedicated hardware circuit, thereby realizing a simulation of the operation of the image processing circuit. The simulation apparatus 1 can simulate the operation of an image processing circuit configured by combining a plurality of partial image processing circuits.
In the memory 3, a program for executing the image processing circuit simulation according to the present embodiment and a plurality of image processing modules are stored. Each image processing module is software (program) that can be executed on a computer, and has a function corresponding to each partial image processing circuit.
Although not shown in the figure, the input side of the simulation apparatus 1 is connected to an image data output device such as a scanner, digital camera, hard disk device or the like, and an input for evaluation for evaluating the image after the image processing result from each device. Image data VIDEO is input.

On the other hand, on the output side of the simulation apparatus 1, a hard disk device 4 as a recording medium and a display 5 as an image display device are connected.
The hard disk device 4 stores the image processing module selected by the simulation device 1, its execution procedure, and result data (result image data and the like) obtained by performing image processing in each image processing module.
A display image is formed on the display 5 based on the result image data obtained by performing the image processing of the image processing module.

  The arithmetic processing unit 2 includes a module management unit 6, an output unit 7, and a writing unit 8, and each of these functional units 6 to 8 is executed on the OS (Operating System) of the arithmetic processing unit 2. Is configured as a program group.

  FIG. 2 shows an example of a screen displayed on the display 5 of FIG.

  The module management means 6, the output means 7, and the writing means 8 are stored in the memory 3, and are activated when a predetermined icon displayed on the display 5 is selected while the simulation apparatus 1 is activated. Yes. Then, the screen G1 as shown in FIG. 2 is displayed to prompt the operator to input, and based on the selection result based on the operator's input, the selection of the image processing module and the parameter applied to the image processing module Set the selection and execution procedure.

The module name displayed by default on the screen G1 reads and displays the image processing module stored in the memory 3 in advance. In order to read out a new image processing module, a new image processing module can be read out by clicking on the readout button G8 at the lower right on the screen G1 and selecting it on the selection screen.
Note that the image processing module desirably covers all image processing performed by the image display device to be subjected to image processing. In particular, the conversion processing from the RGB color space to the Yuv color space, and the inverse of the color space conversion processing. Examples include conversion processing, gamma characteristic conversion, and conversion processing from high resolution to low resolution.
These image processings are common in that sharpness processing, contrast processing, and color conversion processing are performed in the in-module processing. Depending on the order of image processing, the processing may interfere with each other in the image resulting from the image processing. Phenomena such as general defects and color unevenness of the entire image may occur.

  The module management means 6 selects the image processing module, sets the execution procedure of the selected image processing module, executes the image processing module, and performs image processing by the image processing module as the image processing result. This is a part for setting the grouping conditions (grouping conditions, result grouping conditions) and grouping the image processing results. The module selection means 61, the module execution procedure setting means 62, the module execution means 63, and the parameter selection. Means 64, result grouping condition setting means 65, and result grouping execution means 66 are provided. Here, grouping of image data (image processing results) refers to an operation of distributing the image processing results to any of a plurality of groups.

  The module selection means 61 is a part for selecting an image processing module, and as shown in FIG. 2, the screen G1 prompting the operator to select is displayed on the display 5, and the operator selects on the screen G1. The image processing module is selected as the image processing module to be executed.

The selection on the screen G1 by the operator is performed by checking the check box G2 displayed on the left side of the screen G1 with an input device such as a keyboard or a mouse.
A box G3 on the right side of the check box G2 is used to set whether to output result image data and display output of the result image. When the box G3 is clicked with a mouse, for example, the box G3 is white, blue, red. In the case of white (the white box in FIG. 2), the result image and the result image data (result data) are not output. When the result image is not displayed on the display 5 and only the result image data is output to the hard disk device 4 and the result image is red (the box with the lower left diagonal line in FIG. 2), the result image is displayed on the display 5 and the result Settings such as outputting image data to the hard disk device 4 can be made.

  The module execution procedure setting unit 62 is a part for setting the execution procedure of the image processing module selected by the module selection unit 61. The module execution procedure setting means 62 causes the operator to select an image processing module to be operated on the screen G1 shown in FIG. The image processing module selected by the operator is displayed in a state surrounded by a rectangle G4 on the screen G1. The operator can change the execution procedure by changing the order of the image processing modules by moving the selected image processing module up and down by clicking the execution procedure change buttons G5 and G6 at the bottom of the screen G1. It has become. Then, the selection and execution procedure of the image processing module set in this way is written on the memory 3.

  FIG. 3 shows an explanatory diagram of the selection and execution procedure of the image processing module written on the memory 3.

The writing on the memory 3 is written as a table T1, for example, as shown in FIG. This table T1 records the selected module name, presence / absence of execution, presence / absence of image output, presence / absence of image data output (data output), and the parameter name used in each image processing module.
The parameter is an operation parameter value at the time of execution of each image processing module. For example, in the case of a curve gamma value conversion module, a value such as γ = 2.2 is stored. This parameter is stored in the memory 3 together with the module management means 6.

  The module execution means 63 is a part for sequentially executing the image processing modules selected by the module selection means 61 based on the execution procedure set by the module execution procedure setting means 62. Image processing by the selected image processing module is sequentially executed on one or a plurality of types of input image data VIDEO for evaluation.

Specifically, the module execution means 63 executes the image processing module from the upper level of the table T1 shown in FIG. 3 described above. At this time, referring to the presence / absence of execution and parameters in the table T1, the memory 3 is searched, and image processing by the searched image processing module is performed. In this embodiment, the image processing module is executed by clicking the execution button G7 in FIG. 2, and one image processing module is executed each time the operator clicks the execution button G7.
Image data obtained as a result of the image processing by the module execution unit 63 is output to the output unit 7.

  The parameter selection means 64 is a part for selecting parameters of the image processing module executed by the module execution means 63, and displays a screen G1 for prompting the operator to select on the display 5 as shown in FIG. The parameter file selected on the screen G1 by the operator is selected as the parameter of the selected image processing module.

  The result grouping condition setting means 65 is a part for setting conditions for grouping image data (image processing results) after image processing by a series of image processing modules executed by the module execution means 63. FIG. When the operator clicks the result grouping condition setting button G9 on the screen G1 shown in FIG. 6, a result grouping condition setting screen G20 is displayed on the display 5.

  In the present embodiment, by grouping image data that has been subjected to a series of image processing by a series of image processing modules for a plurality of input images, processing result analysis processing is realized, and qualitative and visual effects of processing results are realized. In addition to facilitating quantitative evaluation, verification of image processing can be made more efficient. In the present embodiment, in order to analyze the processing results of the series of image processing modules, the image data of the original input image and the image data of the processing results of the series of image processing modules (post-processing images) for each of a plurality of input images. Difference information with respect to (data) is obtained, and the difference information is grouped. The grouped difference information is used for generating a histogram, for example.

  FIG. 4 shows an example of the result grouping condition setting screen G20 displayed on the display 5.

The result grouping condition setting screen G20 prompts the operator to set the result grouping condition, and the result grouping condition setting unit 65 sets the result grouping condition based on the setting result based on the input of the operator. .
The setting on the result grouping condition setting screen G20 includes a radio button G21 for designating one of a plurality of types of computation methods provided in advance, a radio button G22 for designating a pixel to be subjected to calculation of difference information, and difference information. This is done by clicking the radio button G23 specifying the totaling method, and the range (grouping information for grouping) of the totalized difference information is specified in the text field G24. This text field G24 may be composed of, for example, a combo box.

With the radio button G21, the difference ΔL of L ^* in the CIELV color space between the original input image and the image processed image, and the u ^* in the CIELV color space between the original input image and the image processed image are set. Difference Δu, v ^* difference Δv in the CIELV color space between the original input image and the image processed image, Color difference ΔEuv in the CIELV color space between the original input image and the image processed image, or the original The edge value difference ΔEdge between the input image and the image-processed image can be designated. Note that the radio button G21 may be configured to specify difference information in a color space other than the CIELV color space.

  In the radio button G22, the calculation method designated by the radio button G21 is performed between each pixel constituting the input image and each pixel constituting the corresponding output image after image processing, or the input image is constituted. It is possible to specify whether to perform between a given sampling pixel and a sampling pixel constituting an output image after image processing corresponding to the given sampling pixel. Note that the radio button G22 may be configured so that the calculation method specified by the radio button G21 can be specified so as to calculate between other pixels.

  In the radio button G23, the maximum value among the calculation results between the images specified by the radio buttons G21 and G22 is acquired, or the average value of the calculation results between the images specified by the radio buttons G21 and G22 is acquired. Can be specified. Note that with the radio button G23, the calculation results between the images specified by the radio buttons G21 and G22 may be aggregated by another method.

  In the text field G24, it is possible to specify to which group the values acquired by the calculation method specified by the radio button G23 are calculated by the calculation results specified by the radio buttons G21 and G22. For example, when “1.0” is designated in the text field G24, the processing result is “0.0” to “1.0”, “1.0” by a series of image processing modules according to the acquired value. ”To“ 2.0 ”,“ 2.0 ”to“ 3.0 ”, and so on. For example, when “1.0” is designated in the text field G24 and the acquired value is “5.5”, the text field G24 is grouped into groups “5.0” to “6.0”.

  In the result grouping condition setting screen G20 of FIG. 4, the method specified by the radio buttons G21 to G23 and the text field G24 is set as the result grouping condition by clicking the button G25 with the mouse. The setting process ends. On the other hand, by clicking the button G26 on the result grouping condition setting screen G20, the method specified by the radio buttons G21 to G23 and the text field G24 is not set as the result grouping condition, and the result grouping condition is set. The setting process ends.

In FIG. 1, the output means 7 is a part for outputting the result of image processing of the input image data VIDEO by the image processing module in the module execution means 63 and the grouped result. The result display section 71 and the result writing section 72.
The result display unit 71 is a part for displaying the image processing result of the input image data VIDEO by the image processing module on the display 5, and whether or not to display is displayed in the column of presence / absence of image output in the table T1 in FIG. Judge based. The result display unit 71 is also a part that displays the processing results grouped by the result grouping execution unit 66 on the display 5 as a histogram, for example.
The result writing unit 72 is a part that writes the image processing result of the input image data VIDEO by the image processing module as the result image data to the hard disk device 4, and whether or not writing is performed is whether or not the data of the table T1 in FIG. Judgment based on the column. The result display unit 71 is also a part for writing the processing results grouped by the result grouping execution unit 66 to the hard disk device 4.

  The writing unit 8 is a part for writing the execution procedure of the image processing module set by the module management unit 6 and the result grouping condition set by the result grouping condition setting unit 65 to the hard disk device 4, and the result grouping condition Writing means 81 is provided. When the operator clicks the write button G10 at the lower right of the screen G1 with a mouse or the like, the writing means 8 uses the execution procedure of the image processing module set on the screen G1 shown in FIG. Write to device 4. Alternatively, the result grouping condition writing means 81 of the writing means 8 is a result grouping condition setting screen shown in FIG. 3 when the operator clicks the write button G10 at the lower right of the screen G1 with a mouse or the like. The result grouping condition set on G20 is written to the hard disk device 4.

Next, the operation of this embodiment will be described.
FIG. 5 shows a flowchart of a processing example of the simulation apparatus 1 in the present embodiment. For example, the arithmetic processing unit 2 can perform the processing shown in FIG. 4 by reading a program corresponding to the processing example shown in FIG. 4 stored in the memory 3 and executing processing corresponding to the program. In this case, the function of each means constituting the arithmetic processing device 2 is realized by the arithmetic processing device 2 that executes the program read from the memory 3.

When activated, the module management means 6 displays the screen G1 shown in FIG. 2 on the display 5, and allows the operator to select an image processing module and parameters applied to image processing executed by the selected image processing module. Encourage selection.
When the operator selects an image processing module to be executed by clicking the check box G2 with a mouse or the like, the module selection unit 61 sets the execution of the selected image processing module in the table T1 as “present” and executes the image processing module. Is selected (step S1).
Subsequently, when the operator clicks the read button G8 with a mouse or the like and selects a parameter file in which parameters to be applied to image processing are recorded for each image processing module, the parameter selection means 64 selects each image processing module. The corresponding parameter file is selected (step S2). The parameter selection unit 64 prompts the user to select a parameter for each image processing module on the screen G1. When the operator selects a parameter file in which the parameter is set for each image processing module, the parameter selection unit 64 sets the selected parameter for each image processing module. To go.

Next, the module execution procedure setting means 62 changes and selects the execution procedure in the table T1 according to the execution procedure changed by pressing the execution procedure change buttons G5 and G6 for the image processing module selected by the operator using the rectangle G4. An execution procedure of the image processing module is set (step S3).
Then, the module execution procedure setting means 62 determines whether or not the result image of the table T1 is output and the result image data based on the state of the box G3 set by the operator clicking the mouse or the like on the screen G1 in FIG. Is set (step S4).
In this embodiment, the execution procedure is set by the module execution procedure setting unit 62 first, and the setting of whether to output the result image or the result image data is performed later. However, the present invention is not limited to this. The output setting of the result image data may be performed first.

When the selection of the image processing module and the parameter file corresponding thereto and the setting of the execution procedure are completed as described above, the writing unit 8 monitors whether or not the operator clicks the writing button G10 on the screen G1. Then, the table T1 set on the clicked screen G1 is written and stored in the hard disk device 4 (step S6).
Although the execution procedure is written by the operator at this timing in the present embodiment, actually, after the execution processing of all the image processing modules by the module execution means 63 or during the execution of the module execution means 63 It can be made at any timing.

Next, the result grouping condition setting unit 65 performs a result grouping condition setting process started when the operator clicks the result grouping condition setting button G9 on the screen G1 (step S7).
The result group condition setting process by the operator is performed at this timing in the present embodiment, but actually, before the execution of all the image processing modules by the module execution unit 63 or the execution of the module execution unit 63 It can be made at any timing.

  FIG. 6 shows a flowchart of a processing example of the result grouping condition setting processing in the present embodiment. For example, the arithmetic processing unit 2 can perform the process shown in FIG. 6 by reading a program corresponding to the process example shown in FIG. 6 stored in the memory 3 and executing the process corresponding to the program. The process of FIG. 6 is executed by the result grouping condition setting unit 65.

  The result grouping condition setting means 65 monitors whether or not the operator clicks the result grouping condition setting button G9 on the screen G1 (step S20), and when clicked, the result grouping condition setting means 65 is shown on the display 5 in FIG. The result grouping condition setting screen G20 is displayed to prompt the user to set the result grouping condition.

  The result grouping condition setting means 65 selects the radio button G21 to G23 or the text field G24 on the result grouping condition setting screen G20 as shown in FIG. The result grouping conditions set by the buttons G21 to G23 and the text field G24 are set (step S21).

  When the setting of the result grouping condition is completed as described above, the result grouping condition writing unit 81 determines whether or not the operator clicks the write button G10 on the screen G1 or a dedicated write button (not shown). The result grouping condition setting information corresponding to the result grouping condition set on the clicked result grouping condition setting screen G20 is written and stored in the hard disk device 4 (step S23).

Next, as shown in FIG. 5, the module execution means 63 executes the image processing module selected according to the order set in the table T1.
First, the module execution means 63 reads the input image data VIDEO based on the description in the first row of the table T1 (step S8).
Subsequently, the module execution unit 63 reads out the parameters based on the parameter file name described in the third row (not executed in the second row) of the table T1 (step S9), and the image processing module in the same row. Based on the name, the corresponding image processing module is obtained by searching the memory 3 (step S10).
The module execution unit 63 executes the searched image processing module and performs image processing on the input image data VIDEO (step S11).

When the image processing by the image processing module is completed, the result display unit 71 of the output unit 7 determines whether or not the result image is output from the table T1 of the image processing module (step S12). An image obtained as a result of the image processing is displayed on the display 5 (step S13).
Similarly, the result writing unit 72 of the output means 7 determines the presence / absence of data output in the table T1 (step S14), and if it is set to “present”, writes the result image data to the hard disk device 4; Store and save (step S15).

Subsequently, when the execution of the image processing module by the module execution unit 63 is completed, the result grouping execution unit 66 performs a result grouping process (step S16).
Note that the result grouping process by the operator is performed at this timing in this embodiment. Actually, however, after the execution of each image processing module, either the result display process or the result storage process is performed. It can also be possible at timing.

  FIG. 7 shows a flowchart of a processing example of the result grouping processing in this embodiment. For example, the arithmetic processing device 2 can perform the processing shown in FIG. 7 by reading a program corresponding to the processing example shown in FIG. 7 stored in the memory 3 and executing processing corresponding to the program. The processing in FIG. 7 is executed by the result grouping execution means 66.

The result grouping execution unit 63 monitors the execution status of the image processing module by the module execution unit 63, and determines whether or not the execution of the image processing module by the module execution unit 63 has been completed for all pixels (step S30). ).
When the execution of the image processing module by the module execution unit 63 is not completed for all pixels, the result grouping execution unit 66 calculates the calculation method and the calculation among the result grouping conditions set by the result grouping condition setting unit 65. According to the information of the target designated pixel, the designated calculation is performed on the pixel value of the input image and the pixel value of the result image (step S31). The result grouping execution means 66 uses the pixel values of the input image and the pixel values of the result image to specify the input image and the input image as specified by the radio buttons G21 and G22 on the result grouping condition setting screen G20 of FIG. Difference information from the result image is obtained by a known calculation method.

  Next, the calculation result obtained by the result grouping execution means 66 is written and stored in the hard disk device 4 by the result writing unit 72 (step S32), and the result grouping execution means 66 again returns to the module execution means. The monitoring of the execution status of the image processing module by 63 is continued (step S30).

  When the execution of the image processing module by the module execution means 63 is completed for all pixels, the result grouping execution means 66 follows the summation method and range information among the result grouping conditions set by the result grouping condition setting means 65. Then, a result grouping process is performed (step S33). The result grouping execution unit 66 calculates the calculation result obtained using the pixel value of the input image and the pixel value of the result image for each execution result by the series of image processing modules performed on one input image. Grouping is performed according to the totaling method and range specified by the radio button G23 and the text field G24 on the result grouping condition setting screen G20 of FIG.

  As a result grouping process executed by the result grouping execution unit 66, a series of image processing results may be distributed and stored in any of a plurality of groups provided in advance. You may make it update by incrementing the counter value of an applicable group among the several groups in which a counter value is provided for every.

  Thereafter, as shown in FIG. 5, the module execution means 63 determines from the table T1 whether or not there is an image processing module to be executed next (step S17). End (end).

  Here, an operation example of the present embodiment will be described.

FIG. 8A to FIG. 8E show examples of parameter files. FIGS. 8A to 8E schematically illustrate an example of a parameter file applied to R component color conversion processing of RGB when the image processing module performs color conversion processing (image processing). To express.
9A to 9C are explanatory diagrams of the parameters of FIGS. 8A to 8E. FIG. 9A shows an explanatory diagram of the parameters in FIG. 8A, FIG. 9B shows an explanatory diagram of the parameters in FIG. 8D, and FIG. 9C shows the parameters in FIG. The explanatory view of the parameter of E) is represented.
FIG. 10 shows an explanatory diagram of an operation example of the present embodiment.

  In each of FIGS. 8A to 8E, the correction amount y with respect to the pixel value x of the R component is discretely set, and the image processing module performs known interpolation for the pixel value that is not set. The correction amount can be obtained by processing. Therefore, for example, FIGS. 9A to 9C perform different color conversion processes based on the reference lines P1 to P3 where the pixel values before and after correction are equal.

In this embodiment, for example, for each input image constituting one or a plurality of input images, a parameter for each image process is set to a plurality of types while changing the execution order of the one or a plurality of image processes including the color conversion process described above. By setting, a plurality of result images can be obtained. Then, as shown in FIG. 10, for each result image, the difference information from the input image IMGin is calculated and digitized, and the calculation results are grouped. For example, result images IMGO ₁ and IMGO ₂ having different image processing results are separated from each other. By grouping into groups, it is possible to facilitate qualitative and quantitative evaluation of the effect of visual image processing results.

In this way, various combinations of image processing modules capable of varying the parameters to which they are applied are simulated, and the selection of the image processing module and the execution procedure so as to obtain an optimal image processing result are obtained. Designing an image processing circuit for mounting a partial image processing circuit.
Specifically, the mounting layout may be designed in the partial image processing circuit in the image processing circuit so that the image processing procedure is similar to the execution procedure of the image processing module.

  In the present embodiment, the following effects can also be obtained.

  In FIG. 11, explanatory drawing of the effect of the simulation apparatus 1 in this embodiment is shown. In FIG. 11, the same parts as those in FIG.

  In the simulation apparatus 1 according to the present embodiment, for example, as illustrated in FIG. 11, a series of image processing modules of Module 1 to Module N (N is a natural number of 2 or more) can be sequentially executed by the module management unit 6. By displaying the intermediate output image on the display 5 by each image processing module, it is possible to easily confirm which image processing module has caused the image quality degradation. In FIG. 11, the management information associated with each of Modules 1 to N means the presence / absence of module execution, presence / absence of result image output, presence / absence of result image data, and parameter file set on the screen G1 described above.

For example, in FIG. 11, when evaluating the image processing result of Module 2, if an intermediate image is output before and after Module 2, and image processing by Module 2 is performed, there is a problem before the image processing. However, after image processing, the operator can easily confirm on the display 5 that horizontal line-shaped image quality deterioration has occurred in a predetermined area.
Note that image quality degradation due to image processing is not only locally caused, but also appears as color unevenness that occurs on the entire screen, jaggy or block noise that occurs during conversion from high resolution to low resolution, and blur on the entire screen. Yes, these image quality degradations can be evaluated by visual comparison.

The combination of image processing modules can be freely set by the operator on the screen G1, so that simulation can be performed by easily changing the selection of image processing modules and the order of image processing. It is easy to find a combination of various image processing modules easily and in a short time.
Further, since the result writing unit 72 can write the result image data to the hard disk device 4, comparison evaluation with the input image data VIDEO is performed by executing known evaluation software on the computer. It is also possible. As a comparative evaluation method, for example, if the luminance, color unevenness, etc. of each pixel are converted into numerical values and compared, and statistical processing is performed and the change exceeds a certain threshold, it is regarded as image quality deterioration. A method that determines that there is no deterioration in image quality can be employed unless the value exceeds.

Note that, as the image processing executed by the image processing module in the present embodiment, for example, color conversion processing for uniformly changing the gamma curve over the entire screen has been described as an example, but the present invention is not limited to this. For example, as the image processing executed by the image processing module, color unevenness correction processing that varies the gamma curve for each divided area of the screen is adopted, and the target image for correcting the color unevenness of the optical system is set as an input image, and the result image A combination of parameters such that the maximum value of ΔEuv between sampling pixels is reduced may be obtained, and a combination of image processing modules that can obtain the effect of color unevenness correction may be found.
Alternatively, for example, as an image process executed by the image processing module, a three-dimensional lookup table conversion process is adopted, a gradation image is used as an input image, an edge value of each pixel of the result image is obtained, and the maximum value is reduced. A combination of image processing modules that can reduce the occurrence of pseudo contours during contrast enhancement and edge enhancement may be found.

  In the present embodiment, the result grouping condition setting process is a process in which the input image data of the original input image and the image processing by the image processing module are performed on the input image data, as shown in FIG. As an example, a calculation method for calculating difference information with post-image data, a method for specifying a pixel that is a calculation target of this difference information, a method for counting the above difference information, and a method for specifying a range for grouping the above difference information Although described, the present invention is not limited to this. For example, a calculation method for calculating the difference information between the input image data of the original input image and the processed image data, a method for specifying a pixel that is the calculation target of the difference information, a method for counting the difference information, and the difference At least one of the designation methods of the range for grouping information may be set in the result grouping condition setting process.

  Further, in the present embodiment, as a calculation method for calculating the difference information, a difference in brightness between pixels that are the calculation target of the difference information, a difference in saturation and hue between pixels, a color difference between pixels, and input image data Although the difference between edge values based on image data after image processing has been described as an example, the present invention is not limited to this. As a calculation method for calculating the difference information, for example, a difference in lightness between pixels that is a calculation target of difference information, a difference in saturation and hue between pixels, a color difference between pixels, and input image data and image data after image processing It is only necessary to include at least one of the difference between the edge values based on.

As described above, according to the present embodiment, the image processing order can be easily obtained by easily changing the order of image processing and easily simulating a combination of a plurality of image processing. The selection and execution procedure can be easily found, and an image processing circuit corresponding to this can be provided. As a result, the error verification time can be shortened and the manufacturing cost of the image processing circuit can be reduced.
In addition, even if the types of partial image processing circuits that make up the image processing circuit increase, the execution order of each and the selection of optimal parameters can be performed reliably and easily, depending on the combination of these parameters. This makes it easier to verify errors that are revealed. Note that even if the number of pixels increases, the execution order of image processing and the selection of the optimum parameters are still reliable and easy.

Furthermore, by grouping the result images after a series of image processing, qualitative and quantitative evaluation of visual effects can be facilitated, and verification of the result images can be made more efficient.
In addition, even if a series of image processing is added and deleted, and a parameter applied to each image processing is changed, the above evaluation becomes easy, and an image processing with high expandability can be evaluated.
Furthermore, by performing image processing on a wide variety of images and grouping the image processing results, it is possible to obtain an effect that the effect of changing the parameter applied to each image processing can be easily grasped.

DESCRIPTION OF SYMBOLS 1 ... Simulation apparatus, 2 ... Arithmetic processing apparatus, 3 ... Memory,
4 ... Hard disk device, 5 ... Display, 6 ... Module management means,
7 ... Output means, 8 ... Writing means, 61 ... Module selection means,
62 ... Module execution procedure setting means, 63 ... Module execution means,
64 ... parameter selection means, 65 ... result grouping condition setting means,
66 ... result grouping execution means, 71 ... result display section, 72 ... result writing section,
81 ... Result grouping condition writing means, G1 ... screen, G2 ... check box,
G3, G25, G26 ... button, G4 ... rectangle, G5, G6 ... execution procedure change button,
G7 ... execute button, G8 ... read button, G9 ... result grouping condition setting button,
G10 ... Write button, G20 ... Result grouping condition setting screen,
G21, G22, G23 ... radio buttons, G24 ... text fields,
P1 to P3 ... reference line, T1 ... table, VIDEO ... input image data

Claims (15)

An image processing circuit simulation apparatus for simulating the operation of an image processing circuit,
An image processing module having a function corresponding to the image processing circuit;
Module execution means for executing the image processing module and performing the image processing on one or a plurality of input images;
A simulation apparatus for an image processing circuit, comprising: result grouping execution means for performing grouping on image data on which the image processing by the image processing module executed by the module execution means is performed. In claim 1,
The result grouping execution means includes:
The grouping is executed based on difference information between input image data of an original input image and processed image data obtained by performing image processing on the input image data by the image processing module. Processing circuit simulation device. In claim 1 or 2,
A result grouping condition setting means for setting a grouping condition for image processing results of the image processing module;
The result grouping execution means includes:
An apparatus for simulating an image processing circuit, wherein grouping is executed for each image data after image processing of an input image based on the grouping condition set by the result grouping condition setting means. In claim 3,
The result grouping condition setting means includes:
A calculation method for calculating difference information between input image data of an original input image and post-processing image data obtained by performing image processing on the input image data by the image processing module, and pixels for which the difference information is calculated A simulation apparatus for an image processing circuit, characterized in that at least one of a specifying method, a totaling method of the difference information, and a specifying method of a range in which the difference information is grouped is set. In claim 4,
The calculation method is as follows:
Difference in brightness between pixels that are the calculation target of the difference information, saturation and hue difference between the pixels, color difference between the pixels, and difference in edge value based on the input image data and the processed image data An image processing circuit simulation apparatus comprising at least one of the following. In any one of Claims 1 thru | or 5,
A plurality of image processing modules each having a function corresponding to each of a plurality of partial image processing circuits constituting the image processing circuit;
Module selection means for selecting an image processing module to be executed from among the plurality of image processing modules;
The module execution means
The image processing modules selected by the module selection means are sequentially executed, and image processing of input image data is performed.
The result grouping execution means
A simulation apparatus for an image processing circuit, wherein grouping is performed on image data on which image processing has been performed by a plurality of image processing modules executed by the module execution means. In claim 6,
Module execution procedure setting means for setting the execution procedure of the image processing module selected by the module selection means;
The module execution means
A simulation of an image processing circuit characterized in that the image processing modules selected by the module selection means are sequentially executed according to the execution procedure set by the module execution procedure setting means, and image processing of input image data is performed. apparatus. In claim 6 or 7,
The image processing circuit simulation apparatus, wherein the plurality of image processing modules include at least a resolution conversion module, a color conversion module, and a gamma characteristic conversion module. An image processing circuit simulation method for simulating the operation of an image processing circuit,
Executing an image processing module having a function corresponding to the image processing circuit and performing image processing on one or a plurality of input images;
And a step of grouping the image data on which the image processing has been performed on the one or more input images. In claim 9,
The grouping is executed based on difference information between input image data of an original input image and processed image data obtained by performing image processing on the input image data by the image processing module. Processing circuit simulation method. In claim 9 or 10,
Setting a grouping condition for image processing results of the image processing module;
A simulation method for an image processing circuit, wherein grouping is executed for each image data on which an image process has been performed on an input image based on the set grouping condition. In claim 11,
A calculation method for calculating difference information between input image data of an original input image and post-processing image data obtained by performing image processing on the input image data by the image processing module, and pixels for which the difference information is calculated A method for simulating an image processing circuit, wherein at least one of a method for specifying the difference information, a method for counting the difference information, and a method for specifying a range in which the difference information is grouped is set. In any of claims 9 to 12,
Including a step of selecting an image processing module to be executed from among a plurality of image processing modules having a function corresponding to each of a plurality of partial image processing circuits constituting the image processing circuit,
An image characterized by sequentially executing selected image processing modules, performing image processing on input image data, and performing grouping on image data on which image processing has been performed by a plurality of image processing modules Processing circuit simulation method. An image processing circuit design method comprising:
After carrying out the image processing circuit simulation method according to claim 13 to obtain a combination of image processing modules,
A design method of an image processing circuit, wherein a combination of partial image processing circuits in the image processing circuit is determined.   A simulation program for an image processing circuit, which causes a computer to execute the image processing circuit simulation method according to claim 9.