JP2011035873A - Apparatus and method for simulating image processing circuit, method of designing image processing circuit, and simulation program for image processing circuit - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a simulation apparatus or the like for an image processing circuit, in which qualitative and quantitative evaluations of effects of a result of image processing to a moving image by viewing can be facilitated. <P>SOLUTION: The simulation apparatus 1 for the image processing circuit simulates operation of the image processing circuit performing image processing on a moving image constituted of a plurality of frame images. The simulation apparatus includes: an image processing module comprising a function corresponding to the image processing circuit; a module execution means 63 for executing the image processing module and performing the image processing onto each of the frame images; a result grouping execution means 66 for performing grouping on image data on which the image processing has been performed by the image processing module executed by the module execution means 63; and a storage means for storing given arithmetic results for past frame-processed image data obtained by performing image processing on one frame or each of a plurality of frames prior to the relevant frame. <P>COPYRIGHT: (C)2011,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 includes 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 and the like into a partial image processing circuit that is 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, the display image of each frame constituting the moving image formed by the image display device is composed of a large number of pixels, but it is difficult to evaluate the result processed by the partial image processing circuit for each pixel. Patent Documents 1 to 7 described above cannot be applied to the evaluation of the image quality of an image after image processing by the image processing apparatus.
Furthermore, the techniques disclosed in Patent Documents 1 to 7 are processes for still images. Therefore, even if these techniques are applied to a moving image as they are, the same effect as a still image is not always obtained, and the effect when applied to a moving image is unknown.

  The present invention has been made in view of the technical problems as described above, and one of its purposes is an image that can facilitate qualitative and quantitative evaluation of the effect of image processing results on a moving image by visual observation. A processing circuit simulation apparatus, an image processing circuit simulation method, an image processing circuit design method, and an image processing circuit simulation program are provided.

  (1) In one embodiment of the present invention, an image processing circuit simulation apparatus that simulates an operation of an image processing circuit that performs image processing on a moving image including a plurality of frame images corresponds to the image processing circuit. An image processing module having a function, a module execution unit that executes the image processing module and performs the image processing on each frame image, and the image processing by the image processing module executed by the module execution unit performs the image processing. Result grouping execution means for performing grouping on the broken image data, and past frame processed image data obtained by performing the image processing on each frame image of one or a plurality of frames before the frame. Storage means for storing a given calculation result, and the result grouping execution means Using a given computation result for the current frame processed image data obtained by performing the image processing on the frame image of the frame and the computation result for the past frame processed image data stored in the storage means Then, grouping is performed on the image data after the current frame processing.

  According to this aspect, since the image data after the image processing by the image processing module for the moving image composed of a plurality of frame images is grouped, the qualitative and quantitative evaluation of the visual effect of the image processing is performed. And the 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 the simulation apparatus according to another aspect of the present invention, the result grouping execution unit distributes the current frame processed image data to the past frame processed image data stored in the storage unit. When allocating to a group different from the group, at least a part of the stored contents of the storage means is cleared.

  According to this aspect, even if it is determined that the effect of image processing on consecutive frame images is different and is distributed to another group, the effect in the past frame can be referred to. Evaluation is possible.

  (3) In the simulation apparatus according to another aspect of the present invention, the result grouping execution unit distributes the current frame processed image data to the past frame processed image data stored in the storage unit. When allocating to a group different from the group, using the calculation result for the current frame processed image data and the calculation result for the past frame processed image data for at least one frame stored in the storage unit, Grouping is performed on the image data after the current frame processing.

  According to this aspect, when grouping the image data after the current frame processing, the calculation result for the image data after the past frame processing for at least one frame is referred to. Qualitative and quantitative evaluation of effects can be facilitated.

  (4) In the simulation apparatus according to another aspect of the present invention, the result grouping execution unit includes input frame image data and a processed image obtained by performing image processing on the input frame 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 frame image and the result frame image after the image processing, the grouping corresponding to the visual effect of the image processing on the moving image can be simplified. It can be realized by arithmetic processing.

  (5) The simulation apparatus according to another aspect of the present invention includes a result grouping condition setting unit that sets a grouping condition for image processing results of the image processing module, and the result grouping execution unit includes the result group Based on the grouping condition set by the grouping condition setting means, grouping is executed for each image data after image processing of the input frame 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 frame images can be made more efficient. .

  (6) In the simulation apparatus according to another aspect of the present invention, the number of frames of the calculation result for the past frame processed image data stored in the storage unit can be set.

  According to this aspect, the degree of referring to the past frame can be variably set, and it is possible to contribute to the efficiency of the optimal verification according to the moving image.

  (7) In the simulation apparatus according to 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 the plurality of image processing modules An image processing module for selecting an image processing module to be executed, wherein the module execution means sequentially executes the image processing modules selected by the module selection means, and the image data of the input frame image Processing is performed, and the result grouping execution unit 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 unit.

  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.

  (8) The simulation apparatus according to another aspect of the present invention includes module execution procedure setting means for setting an execution procedure of the image processing module selected by the module selection means, and the module execution means includes the module execution procedure. According to the execution procedure set by the setting means, the image processing modules selected by the module selection means are sequentially executed to perform image processing of the image data of the input frame image.

  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.

  (9) In the simulation apparatus according to another aspect of the present 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 the image quality of the result frame 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 frame image.

  (10) In another aspect of the present invention, an image processing circuit simulation method for simulating an operation of an image processing circuit that performs image processing on a moving image composed of a plurality of frame images corresponds to the image processing circuit. A module execution step of executing an image processing module having a function to perform the image processing on each frame image, and each frame image subjected to the image processing by the image processing module executed in the module execution step A result grouping execution step of performing grouping on the image data of the current frame, and the result grouping execution step includes image data after current frame processing in which the image processing is performed on a frame image of the frame And the past frame stored in the storage means. Using said calculation result for processing image data, said performing a grouping for the current frame processed image data.

  According to this aspect, since the image data after the image processing by the image processing module for the moving image composed of a plurality of frame images is grouped, the qualitative and quantitative evaluation of the visual effect of the image processing is performed. And the 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.

  (11) In another aspect of the present invention, after the image processing circuit design method performs the image processing circuit simulation method described above to obtain a combination of image processing modules, the partial image in the image processing circuit Determine the combination of processing circuits.

  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.

  (12) In another aspect of the present invention, an image processing circuit simulation program causes a computer to execute the above-described image processing circuit simulation method.

  According to this aspect, it is possible to provide a simulation program for an image processing circuit capable of facilitating qualitative and quantitative evaluation of the effect of image processing results on a moving image by visual observation.

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. 8A and 8B are explanatory diagrams of the FIFO buffer referred to by the result grouping execution unit. FIG. 9A to FIG. 9E show examples of parameter files. 10 (A) to 10 (C) are explanatory diagrams of the parameters of FIGS. 9 (A) to 9 (E). Explanatory drawing of the operation example of 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. Here, the image processing circuit receives a moving image composed of a plurality of frame images, and performs image processing on each frame image. 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 an image after image processing results from each device. Frame 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 frame image data (processed frame image data), etc.) obtained by performing image processing on each image processing module. Is done.
In addition, a result frame image is formed on the display 5 as a display image based on the result frame 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. These functional units 6 to 8 are 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 in 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, and depending on the order of image processing, in the frame image as a result of image processing, each other's processing interferes, There may be a phenomenon in which partial defects or color unevenness of the entire image is emphasized.

  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.

First, an input of an input moving image file name in the text field B1 and an output moving image file name in the text field B2 is accepted via an input device such as a keyboard by the operator. In FIG. 2, the moving image file specified by the input moving image file name “in.avi” stores moving image data (a plurality of frame image data) each composed of a plurality of frame images that can be specified by frame numbers. ing. Then, the frame image data subjected to the image processing is stored in an output file having an output moving image file name “out.avi” or an output file having a file name obtained by adding a grouping condition to the file name.
Thereafter, the operator selects an image processing module on the screen G1 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 or not to output result frame image data and display output of the result frame image. When the box G3 is clicked with a mouse, for example, the box G3 is white, blue, or blue. In the case of white (the white box in FIG. 2), the result frame image and the result frame image data (result data) are not output, and in the case of blue (the box in the lower right diagonal line in FIG. 2) ), The result frame image is not displayed on the display 5 and only the result frame image data is output to the hard disk device 4. It is possible to perform settings such as displaying on the top and outputting the result frame image data to the hard disk device 4.

  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 allows 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 frame image data output (data output), and the parameter names used in each image processing module are recorded in association therewith. .
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 that sequentially executes 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, and constitutes input frame image data VIDEO. The image processing by the selected image processing module is sequentially executed for each frame image data to be performed.

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.
The result frame image data after 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 unit 65 sets conditions for grouping the result frame image data (processed frame image data, image processing result) after image processing by the series of image processing modules executed by the module execution unit 63. The result grouping condition setting screen G20 is displayed on the display 5 when the operator clicks the result grouping condition setting button G9 on the screen G1 shown in FIG.

  In the present embodiment, a moving image composed of a plurality of frame images is input, and the result of image processing performed by a series of image processing modules on the frame image data of each frame image is the number of past frames, for example. By grouping the specified calculation results that are referenced by the amount, processing results can be analyzed, making it easy to qualitatively and quantitatively evaluate the visual effects of the processing results, and to improve the efficiency of image processing verification. become able to. In this embodiment, in order to analyze the processing results of the series of image processing modules, for each frame image, the original input frame image and the result of the processing of the series of image processing modules for the input frame image are obtained. The difference information is obtained, the difference information in each frame is totaled for several past frames, and grouped based on the result. Therefore, in the present embodiment, the writing unit 8 includes a FIFO buffer 82 (storage unit in a broad sense), and can store difference information for at least one past frame. The FIFO buffer 82 stores difference information for a plurality of consecutive frames belonging to the same group, and when it is determined that the frames belong to different groups, the difference information in some or all of the past frames is cleared.

  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 for designating the totaling method, and the range (grouping information for grouping) of the totaling results is designated in the text field G24. This text field G24 may be composed of, for example, a combo box. The text field G25 designates the number of past frames in which the result of designating each frame is stored, and the text field G26 evaluates the afterimage effect by visual inspection, so that the difference is not cleared to the FIFO buffer 82. The number of past frames in which the specified calculation result is stored is specified.

With the radio button G21, the difference ΔL in L ^* in the CIELV color space between the original input frame image and the processed result frame image, and CIELV between the original input frame image and the processed result frame image. The difference Δu in u ^{* in} the color space, the difference Δv in v ^* in the CIELV color space between the original input frame image and the result frame image after image processing, and the result frame image after the original input frame image and image processing Either the color difference ΔEuv in the CIELV color space between or the edge value difference ΔEdge between the original input frame image and the result frame image after image processing 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 frame image and each pixel constituting the output image after image processing corresponding thereto, or the input frame image Can be designated between a given sampling pixel and a corresponding sampling pixel constituting an output image after image processing corresponding thereto. 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.

  The radio button G23 obtains the maximum value among the calculation results corresponding to the number of past frames between the frame images designated by the radio buttons G21 and G22, or between the frame images designated by the radio buttons G21 and G22 and the past. It is possible to specify whether to obtain the average value of the calculation results for the number of frames. Note that with the radio button G23, the calculation results between the frame images designated by the radio buttons G21 and G22 and the number of past frames may be calculated 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”.

The number of past frames stored in the FIFO buffer 82 can be set from the outside. In the text field G25, when the number of past frames to be referred to when grouping is specified, between the pixels of the input frame image and the result frame image after image processing by the calculation method specified by the radio buttons G21 and G23. The calculation results obtained in the above are aggregated within the designated number of past frames, and grouping is performed. For example, if the difference ΔL is designated by the radio button G21, “Maximum” is designated by the radio button G23 as the counting method, and “100” is designated as the past frame number by the text field G25, the frame image and image of that frame are designated. The maximum value of the difference ΔL obtained for each pixel from the processed result frame image is obtained as a calculation result for one frame, and the maximum value for the past 100 frames is extracted. Then, grouping is performed based on the maximum value.
In order to perform the aggregation as described above, the calculation results of the past frames are glare so as not to refer to the calculation results of the past frames between different groups. However, in order to reflect the afterimage effect observed by human eyes, the calculation results for the number of past afterimage frames are left behind, and these are referred to and aggregated. The number of afterimage frames is designated in the text field G26.

  In the result grouping condition setting screen G20 of FIG. 4, the method specified by the radio buttons G21 to G23 and the text fields G24 to G26 is set as a result grouping condition by clicking the button G27 with the mouse. The initialization condition setting process ends. On the other hand, when the button G28 is clicked on the result grouping condition setting screen G20, the method specified by the radio buttons G21 to G23 and the text fields G24 to G26 is not set as the result grouping condition. The initialization condition setting process ends.

In FIG. 1, the output means 7 is a part for outputting the result of image processing of the input frame image data VIDEO by the image processing module in the module execution means 63 and the grouped result. Part 72 is provided.
The result display unit 71 is a part for displaying the image processing result of the input frame image data VIDEO by the image processing module on the display 5, and whether or not to display it is a column of presence / absence of image output in the table T1 in FIG. Judgment based on.
The result writing unit 72 is a part that writes the image processing result of the input frame image data VIDEO by the image processing module into the hard disk device 4 as a single moving image file of continuous result frame image data of the same group. Is determined based on the data output presence / absence column of the table T1 in FIG. The result writing unit 72 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.
The writing means 8 includes the FIFO buffer 82 as the storage means as described above, and the above calculation results for the result frame image data for a plurality of past frames are accumulated, and the result grouping execution means 66 and the like appropriately. Configured to be referenced.

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 frame image of the table T1 is output and the result frame based on the state of the box G3 set by the operator clicking the mouse or the like on the screen G1 in FIG. Whether to output image data is set (step S4).
In the present embodiment, the execution procedure is set by the module execution procedure setting unit 62 first, and the setting of whether to output the result frame image or the result frame image data is performed later. The output setting of the frame image or result frame 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 is selected by the operator using the radio buttons G21 to G23 and the text fields G24 to G26 on the result grouping condition setting screen G20 as shown in FIG. 4 and clicking the button G27. The result grouping conditions set by the radio buttons G21 to G23 and the text fields G24 to G26 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 frame 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 means 63 executes the searched image processing module and performs image processing on the input frame 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). A frame image is displayed on the display 5 as a result of image processing (step S13).
Similarly, the result writing unit 72 of the output means 7 determines whether or not the data of the table T1 is output (step S14), and if it is set to “present”, writes the result frame image data to the hard disk device 4. The memory is stored (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.
FIGS. 8A and 8B are explanatory diagrams of the FIFO buffer 82 referred to by the result grouping execution unit 66. FIG.

The result grouping execution unit 66 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 has not been completed for all pixels (step S30: N), the result grouping execution unit 66 sets the result grouping condition set by the result grouping condition setting unit 65. In accordance with the calculation method and the information of the designated pixel to be computed, designated computation is performed on the pixel value of the input frame image and the pixel value of the result frame image (step S31). The result grouping execution means 66 uses the pixel values of the input frame image and the pixel values of the result frame image as input by the radio buttons G21 and G22 on the result grouping condition setting screen G20 of FIG. Difference information between the frame image and the result frame 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 unit 63 is completed for all pixels (step S30: Y), the result grouping execution unit 66 totals the calculation results of the specified calculation for one frame by the specified totaling method. The result is calculated (step S33). For example, when the designated counting method is an average, the total value of the designated calculation results between the pixels is obtained by dividing by the total number of pixels of one frame image. Alternatively, for example, when the designated aggregation method is the maximum, the maximum value of the designated calculation result between each pixel is extracted. The result grouping execution means 66 additionally stores the total results obtained in this way in the FIFO buffer 82 (step S34).

  Subsequently, the result grouping execution means 66 further calculates the average value or the maximum value for the past one or a plurality of frames stored in the FIFO buffer 82 by the designated counting method, and totals the past frames. A value is obtained (step S35). For example, if the frame is the Mth frame (M is a natural number), and the FIFO buffer 82 stores the aggregation results for the number of L frames (L is an integer of 2 or more), the result grouping execution unit 66 For example, with reference to the summation results of the Mth frame to the (M− (L−1)) th frame, the average value or the maximum value is obtained as the past frame summation value. Then, the result grouping execution unit 66 groups the frames based on the past frame total values obtained in step S35 with “0” as a reference within the total result range specified in the text field G24 of FIG. Is performed (step S36).

  When the result of grouping in step S36 is the same group as the previous frame (step S37: Y), the result grouping execution means 66 concatenates the result frame image data of the frame with the previous frame and adds it as a moving image file. Save (step S40) and return to step S30. For example, after a scene change, there is a possibility that the result of image processing may change suddenly, and the result is distributed to another group. Alternatively, sudden noise or the like can be distributed to the same group to be considered by counting using the FIFO buffer 82. In addition to additionally storing as a moving image file, it is desirable to store the group name that has been distributed as a result of grouping in association with identification information such as the frame number of the frame image.

  In step S37, if the result of grouping in step S36 is not the same group as the previous frame (step S37: N), the result grouping execution unit 66 newly moves the moving image of the group to which the result frame image of the frame has been assigned. A file is created (step S38), the contents stored in the FIFO buffer 82 are cleared (step S39), the resulting frame image data of the frame is stored in a newly created moving image file (step S40), and the process returns to step S30. In step S38, the storage contents corresponding to the number of the most recent afterimage frames specified in the text field G26 in FIG. 4 are left, and the totaled result of the remaining frames is cleared from the FIFO buffer 82. For example, as shown in FIG. 8B, if “3” is designated as the Mth frame and the number of afterimage frames, as shown in FIG. 8B, in step S38, the (M−1) th frame to the The counting result of the remaining frames is cleared from the FIFO buffer 82, leaving the counting result of the frame (M-3).

  By the way, as a result grouping process executed by the result grouping execution means 66, a series of image processing results may be distributed and stored in any of a plurality of groups provided in advance. Simply, the frame number and the group to be assigned to may be stored in association with each other.

  Thereafter, as shown in FIG. 5, the module execution means 63 determines from the table T1 whether there is an image processing module to be executed next (step S17). If there is, the module execution means 63 repeats from step S9. 63 determines whether or not there is a next input frame image (step S18), and if so, repeats the processing from step S8, and if not, ends the simulation (end).

As described above, the result grouping execution unit 66 performs the given operation result on the current frame processed image data obtained by performing the image processing on the frame image of the frame, and the frame stored in the FIFO buffer 82. Grouping can be performed on the current frame processed image data using a given calculation result on the past frame processed image data for one or more past frame images.
When the result grouping execution means 66 distributes the current frame processed image data to a group different from the group to which the past frame processed image data stored in the FIFO buffer 82 is allocated, at least a part of the FIFO buffer 82 Clear the stored contents of. As a result, it is possible to perform a simulation in consideration of the influence of the afterimage of the eyes.

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

FIG. 9A to FIG. 9E show examples of parameter files. 9A to 9E 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.
10 (A) to 10 (C) are explanatory diagrams of the parameters of FIGS. 9 (A) to 9 (E). FIG. 10A shows an explanatory diagram of the parameters in FIG. 9A, FIG. 10B shows an explanatory diagram of the parameters in FIG. 9D, and FIG. 10C shows the parameters in FIG. The explanatory view of the parameter of E) is represented.
FIG. 11 is an explanatory diagram of an operation example of this embodiment.

  In each of FIGS. 9A to 9E, the correction amount y for the pixel value x of the R component is set discretely, 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. 10A to 10C perform different color conversion processes based on the reference lines P1 to P3 where the pixel values before and after correction are equal.

In the present embodiment, for example, for each frame image of a plurality of frame images IMGin _{1 to} IMGin ₆ ... Constituting a moving image, the execution order of one or a plurality of image processes including the color conversion process is changed. A plurality of result frame images can be obtained by setting a plurality of types of parameters for each image processing. Then, as shown in FIG. 11, difference information with the corresponding input frame image for each result frame image is calculated and digitized, and the calculation results are grouped, for example, result frame images IMGO _{1 to} IMGO having different image processing results. _By grouping ₆ ... Into different groups, qualitative and quantitative evaluation of the effect of visual image processing results can be facilitated.

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.

  Note that image quality degradation due to image processing is not only locally caused, but also color irregularities that occur on the entire screen of the frame image, jaggies and block noise that occur when converting from high resolution to low resolution, and blur on the entire screen. These image quality degradations can be evaluated by visual comparison.

In addition, since the operator can freely set the combination of image processing modules on the screen G1, the 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, a comparative evaluation with the input frame image data VIDEO is performed on a computer by executing a known evaluation software. It is also possible to do this. 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 varying the gamma curve over the entire frame image screen has been described as an example, but the present invention is not limited to this. Absent. 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 frame image screen is adopted, and the target image for correcting the color unevenness of the optical system is set as the input frame image. Then, a combination of parameters such that the maximum value of ΔEuv between the sampling pixels of the result frame image becomes small 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, and an edge value of each pixel of the result frame image is obtained for the input frame image of the gradation image, and the maximum value is A combination of parameters that can be reduced may be obtained, and a combination of image processing modules that can reduce the occurrence of pseudo contours during contrast enhancement or edge enhancement may be found.

  In the present embodiment, the result grouping condition setting process includes the original input frame image data and a result frame obtained by performing image processing by the image processing module on the input frame image data as shown in FIG. An example of a calculation method for calculating difference information with image data, 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 for grouping the difference information will be described. However, the present invention is not limited to this. For example, a calculation method for calculating the difference information between the original input frame image data and the result frame 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 information At least one of the grouping range designation methods may be set in the result grouping condition setting process.

  Further, in the present embodiment, as a calculation method for calculating difference information, a difference in brightness 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 frame image data The difference between the edge values based on the image and the frame image data after image processing has been described as an example, but the present invention is not limited to this. As a calculation method for calculating the difference information, for example, a difference in brightness between pixels for which difference information is calculated, a difference in saturation and hue between pixels, a color difference between pixels, and input frame image data and a frame after image processing It suffices to include at least one of edge value differences based on image data.

In this embodiment, when the current frame processed image data is allocated to a group different from the group to which the past frame processed image data stored in the FIFO buffer 82 is allocated, The grouping may be executed on the current frame processed image data using the calculation result for the past frame processed image data for at least one frame stored in the FIFO buffer 82.
Furthermore, in the present embodiment, the description has been given assuming that the FIFO buffer 82 is built in the writing unit 8, but the present invention is not limited to this, and the FIFO buffer 82 is provided outside the writing unit 8. It may be done.
Furthermore, in this embodiment, the FIFO buffer 82 is used to refer to the specified calculation results of a plurality of past frames, and grouping is performed based on the specified calculation results of the frames. However, the present invention is not limited to this. It is not something. For example, the grouping may be performed based on the specified calculation result of the frame by referring to only the specified calculation result of the immediately preceding frame. In this case, a scene change can be extracted, or an unintended image change after image processing can be extracted. Note that grouping based on the specified calculation result of the frame by referring only to the specified calculation result of the immediately preceding frame is performed by using the FIFO buffer 82 to specify the specified calculation of the frame by referring to the specified calculation results of a plurality of past frames. Instead of grouping based on the result, or using the above-described FIFO buffer 82, it may be performed simultaneously with grouping based on the specified calculation result of the frame by referring to the specified calculation result of a plurality of past frames.

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 frame images after a series of image processing, qualitative and quantitative evaluation of visual effects can be facilitated, and verification of the result frame 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 frame images and grouping the image processing results, it is possible to easily grasp the effect of changing the parameters applied to each image processing.
In addition, depending on the video, processing for effects due to continuous frames that cannot be detected by the eyes, such as blinking pixels or changing colors for each frame, may be performed according to the characteristics of the display. . In this embodiment, since the FIFO buffer 82 is used to refer to the aggregate value of the processing results of the past frames, it is possible to suppress the influence of each frame that cannot be recognized by the eyes, or to be continuously captured by the eyes such as afterimages. Frame effects can be simulated.

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, 82 ... FIFO buffer,
B1, B2, G24 to G26 ... text field, G1 ... screen,
G2 ... check box, G3, G27, G28 ... button, G4 ... rectangle,
G5, G6 ... execution procedure change button, G7 ... execution button, G8 ... read button,
G9 ... Result grouping condition setting button, G10 ... Write button,
G20 ... Result grouping condition setting screen, G21, G22, G23 ... Radio buttons,
P1 to P3 ... reference line, T1 ... table, VIDEO ... input frame image data

Claims (12)

A simulation apparatus for an image processing circuit for simulating the operation of an image processing circuit that performs image processing on a moving image composed of a plurality of frame images,
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 each frame image;
A result grouping execution unit that executes grouping on the image data on which the image processing by the image processing module executed by the module execution unit is performed;
Storage means for storing a given calculation result for image data after past frame processing in which the image processing is performed on each frame image of one or a plurality of frames before the frame,
The result grouping execution means includes:
A given computation result for the current frame processed image data obtained by performing the image processing on the frame image of the frame, and the computation result for the past frame processed image data stored in the storage unit. A simulation apparatus for an image processing circuit, wherein the grouping is performed on the image data after the current frame processing. In claim 1,
The result grouping execution means includes:
When the image data after the current frame processing is distributed to a group different from the group to which the image data after the past frame processing stored in the storage means is allocated, at least a part of the storage contents of the storage means is cleared. A characteristic image processing circuit simulation apparatus. In claim 1,
The result grouping execution means includes:
When the current frame processed image data is distributed to a group different from the group to which the past frame processed image data stored in the storage means is distributed, the calculation result for the current frame processed image data and the storage A grouping is performed on the image data after the current frame processing using the calculation result for the image data after the past frame processing for at least one frame stored in the means. Simulation device. In any one of Claims 1 thru | or 3,
The result grouping execution means includes:
An image processing circuit that performs the grouping based on difference information between input frame image data and processed image data obtained by performing image processing on the input frame image data by the image processing module. Simulation device. In any one of Claims 1 thru | or 4,
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 frame image based on the grouping condition set by the result grouping condition setting means. In any one of Claims 1 thru | or 5,
The simulation apparatus for an image processing circuit, wherein the number of frames of the calculation result for the image data after past frame processing stored in the storage means can be set. In any one of Claims 1 thru | or 6.
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 frame 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 7,
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
An image processing circuit comprising: sequentially executing the image processing modules selected by the module selection unit according to an execution procedure set by the module execution procedure setting unit; and performing image processing of image data of an input frame image. Simulation device. In claim 7 or 8,
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 that performs image processing on a moving image composed of a plurality of frame images,
A module execution step of executing an image processing module having a function corresponding to the image processing circuit and performing the image processing on each frame image;
A result grouping execution step of performing grouping on image data of each frame image subjected to the image processing by the image processing module executed in the module execution step;
The result grouping execution step includes:
A given computation result for the current frame processed image data obtained by performing the image processing on the frame image of the frame, and the computation result for the past frame processed image data stored in the storage unit. And a method of performing a grouping on the image data after the current frame processing. An image processing circuit design method comprising:
After carrying out the image processing circuit simulation method according to claim 10 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.   An image processing circuit simulation program for causing a computer to execute the image processing circuit simulation method according to claim 10.