JP3845927B2 - Image processing apparatus and image processing method - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an image processing apparatus and an image processing method for performing image processing on image data according to an instruction such as image quality adjustment, and in particular, when an image processing operator performs, an image is processed according to characteristics of a target processed image. An image that can be easily adjusted to the image quality intended by the operator by classifying into multiple areas, performing image processing using different image processing parameters for each area, and executing image processing suitable for each area The present invention relates to a processing apparatus and an image processing method.
[0002]
[Prior art]
In recent years, various image processing apparatuses for editing, processing, and analyzing image data have been developed. There are various forms of image processing. Basically, the target image is displayed on the image display device, the area to be subjected to image processing is specified, and image representation such as contrast, sharpness, and edge is displayed. It is common to obtain a desired image by designating an image processing operator to change the image, further setting the processing parameters in some cases, and executing image processing. There is also an image processing apparatus that allows a rough processing result to be displayed and checked in advance by executing a preview process before processing the entire image. Actually, a desired image processing result is obtained by variously combining these single image processes. An example of such an image processing apparatus implemented by software is “Photoshop”.
[0003]
These general image processing apparatuses have a large number of image processing operators that bring about changes in image quality and image quality such as “density inversion”, “image rotation”, “sheepness adjustment”, “edge enhancement”, etc. The image processing is performed using these many image processing operators, and further, a desired image can be obtained by performing more subtle adjustments while setting predetermined image processing parameters set for each operator. It has gained. Therefore, in these image processing processes, the process of repeated trial and error by the operator actually occupies most of image editing, processing, and analysis work. That is, the operator sets a predetermined operator and parameters, executes image processing based on the set parameters, checks the processing result, and if the desired result cannot be obtained, Set different operators and parameters. Image processing is executed by repeating such processing. Much of research related to conventional image processing is performed for the purpose of a) increasing the types of image processing operators, b) increasing the speed of each image processing, and the like. On the other hand, research on the reduction of the operator's process as described above is also conducted.
[0004]
For example, a color image forming apparatus described in Japanese Patent Application Laid-Open No. 7-203230 is an example of a result of research aimed at simplifying an image processing process and realizing an image processing apparatus that can be processed more intuitively by an operator. . In this color image forming apparatus, a correspondence relationship between a combination of a plurality of color adjustment parameters and a color parameter in which a change in the image due to the processing is defined in a sensory language is stored, and this is referred to as a sensory word “color”. It is defined as “psychological parameter”, and image processing by an instruction using this “color psychological parameter” is enabled. By using these “color psychological parameters”, it is not necessary to use image processing parameters that were simply numerical or abstract expressions that were difficult to understand during color adjustment, etc. Image processing is possible. In this way, a system has been provided in which the user trial and error process for parameter setting is reduced and image processing is facilitated.
[0005]
However, these conventional image processing apparatuses generally apply the same image processing parameters to the entire target image when an instruction from the image processing operator is given. Usually, there are various different image characteristics in different areas in the image. When the same image processing parameters are applied to the entire image, the operator pays attention and the intended processing result is obtained in the part intended to be corrected. However, at the same time, there is a high possibility that a new image area will appear that results in a processing result different from the operator's intention. As a result, the entire image is different from the result intended by the operator, and there is a problem that an image processing result that is satisfactory for the operator cannot be obtained.
[0006]
[Problems to be solved by the invention]
Some conventional image processing apparatuses change an image processing parameter as an option for a predetermined image processing operator and set it so that a finer adjustment can be made to the image processing in the operator. At the time of setting, the image processing parameter group is uniquely determined, and the image processing is executed in all regions based on the image processing parameter group. As a result, the image processing of the entire image is executed with a set of uniquely defined image processing parameters, and the parameters that were appropriate in a specific area in the image are not appropriate in other areas. When the entire image is viewed, the result desired by the user is not obtained, and the image quality may not be improved.
[0007]
One method for solving such a problem is a method of dividing an image into a plurality of regions. By setting an appropriate image processing parameter group for each divided region, the entire uniform image processing is avoided. However, the conventional region dividing method is generally divided into a uniform image or divided while the user views the image. Therefore, none of the processing speed and the processing result yields a satisfactory result for the operator. In particular, in the case of using a method in which the user manually sets the area, it is required to display the predetermined image data on the display device, and to accurately set the area while visually checking it. It is possible that the part where the user visually sets the area does not match the area having the same image characteristics, and performing accurate area division on the image and performing appropriate image processing for each divided area It was difficult.
[0008]
The present invention has been made to solve the above problems. An object of the present invention is to perform image analysis when performing an image processing operator on various image data having different characteristics, and appropriately change image processing parameters in the same image according to the image analysis result. An object of the present invention is to provide an image processing apparatus and an image processing method capable of performing appropriate image processing.
[0009]
[Means for Solving the Problems]
An image processing apparatus according to the present invention includes an image input unit for inputting image data, an image data storage unit for storing the input image data, an image processing operator instruction unit for instructing an image processing method for the image, and an image Analyzing the target image data based on the processing operator, analyzing the analysis result by the image data analyzing unit, and performing image processing based on the parameter value of the image processing parameter and the parameter value Image processing parameter / region determining means for determining an image processing area to be executed, and image processing means for performing image processing on image data based on the image processing parameter determined as an image processing operator and image processing application area information When an image processing operator's instruction to change the image quality is given For each image processing operators, it analyzes the image data to be processed, and performs image processing using a suitable plurality of image processing parameters corresponding to the characteristics of the image.
[0010]
Further, in the image processing apparatus of the present invention, the image data analysis executed by the image data analysis means is required for determining the image processing parameters used when the operator instructed by the image processing operator instruction means is executed. It is characterized by image data.
[0011]
Further, the image processing parameter / region determining unit in the image processing apparatus of the present invention classifies the image data into a plurality of regions according to the image analysis result by the image data analyzing unit, and each of the classified regions has the image processing parameter. And image processing is executed based on the image processing parameter set for each classified area.
[0012]
Further, the image processing parameter / region determining means in the image processing apparatus of the present invention performs image analysis processing corresponding to the instructing operator on the image data for each operator instructed by the image processing operator instructing means, By analyzing the image analysis result corresponding to the operator, an image processing mode for each classified region is determined, an image processing parameter corresponding to the determined image processing mode is selected, and image processing for each classified region is performed. It is characterized by performing.
[0013]
Further, the image processing parameter / region determination means in the image processing apparatus of the present invention performs an analysis process on the image data for each operator instructed by the image processing operator instruction means, analyzes the result, and sets in advance. Each image processing mode application area is classified based on the threshold value, and an image processing parameter to be applied is determined for each classified image processing mode application area.
[0014]
In the image processing apparatus of the present invention, when the image processing operator performs edge enhancement processing, the image data analysis means executes edge strength analysis of the image, and the image processing parameter / region determination means sets the strength of edge enhancement processing. Filter coefficients for setting the image processing parameters as image processing parameters. When the image processing operator is color tone correction processing, the image data analysis unit executes color tone analysis of the image, and the image processing parameter / region determination unit sets the strength of color tone correction based on the result of the color tone analysis. Determine the parameters to be used. Further, when the image processing operator performs image reduction processing, the image data analysis means extracts an image area including pixels with high edge strength by the image data analysis, and the image processing parameter / area determination means In an image area including high pixels, a parameter for executing image reduction is set by weighting pixels having high edge strength in order to preserve edges, and average value reduction is executed in other image areas. Set the parameter to.
[0015]
The image processing method of the present invention includes an image input means for inputting image data, an image data storage means for storing the input image data, and an image processing operator instruction means for instructing an image processing technique for the image. In the image processing apparatus having image processing means for performing image processing, the step of executing analysis of the target image data in accordance with the image processing operator instructed by the image processing operator instruction means, and analyzing the result of the image data analysis Determining the parameter value of the image processing parameter and the image processing area for executing the image processing based on the parameter value, and instructing the image data based on the determined image processing parameter and the image processing application area information. Executing image processing by an image processing operator. The image processing method.
[0016]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, the present invention will be specifically described based on examples with reference to the drawings. FIG. 1 is a block diagram showing the overall configuration of an image processing apparatus according to an embodiment of the present invention. 1 includes an image input unit 1, an image data storage unit 2, an image processing operator instruction unit 3, an image data analysis processing unit 4, an image processing parameter / region determination processing unit 5, and an image processing unit 6. It is configured. These components are connected by a predetermined bus so that data can be transferred between them.
[0017]
The image input unit 1 inputs image information output from various devices such as a scanner, digital video, and digital camera as digital data. The image data storage unit 2 stores image information input to the image input unit 1 as digital data. The image data stored as necessary is stored in an image processing operator instruction unit 3 and an image data analysis processing unit 4. And output to the image processing unit 6. The image processing operator instruction unit 3 instructs an image processing operator such as image analysis, image quality adjustment, and format conversion. When the image processing operator is instructed, the image data analysis processing unit 4 determines whether or not the image data should be analyzed according to the content of the instruction, and performs various image analysis if necessary and outputs an analysis result. The image processing parameter / region determination processing unit 5 performs analysis using the types of image processing parameters accompanying the image processing operator and the results obtained by the image data analysis processing unit, and classifies the image data into a plurality of image application regions. At the same time, an image processing parameter group to be applied in each region is determined. The image processing unit 6 performs image processing on the image data based on the input image processing operator, image processing parameters, and image processing parameter application area information.
[0018]
Next, the operation of an embodiment of the image processing apparatus of the present invention will be specifically described with reference to the drawings. FIG. 2 is a flowchart for explaining how image processing parameters are determined and image processing is performed when an image processing operator is instructed. First, when there is an instruction of an image processing operator such as image analysis, image quality adjustment, and format conversion in step 201, in step 202, whether or not the image processing operator includes an image processing parameter, and includes an image processing parameter. Determines whether the image processing parameter is an image processing parameter that needs to be changed depending on the image data. If image analysis is not required, the determination is no and the process immediately proceeds to the image processing step of step 206. For example, in the case of an image processing operator such as “density inversion”, since there is no image processing parameter, the process immediately proceeds to the image processing step. In the case of an image processing parameter in which the rotation angle and rotation method are uniquely determined as in image rotation, the process immediately proceeds to the image processing step. In such a case, image analysis is not performed. On the other hand, in the case of an image processing operator such as edge enhancement described later, image analysis is performed. If it is determined in step 202 that image analysis needs to be performed (YES), in step 203, necessary image analysis is performed for each image processing operator. In step 204, the images are classified according to the characteristics, and the image analysis result and the image processing parameters are analyzed and combined. In step 205, an image processing parameter group and an image processing area are determined and output. Finally, in step 206, the designated image processing operator is executed using the image processing parameters.
[0019]
Furthermore, when the operation of the parameter determination processing unit is specifically described, a case where edge enhancement is selected as an image processing operator will be described as an example. Usually, when an image processing operator selects edge enhancement as an image processing operator, first, the image data accumulated through the image input unit is displayed on a CRT or the like, and an area where edge enhancement is to be executed is set as necessary. An image processing operator for edge enhancement is selected. When instructing the image processing operator, an image processing parameter is also designated together with the image processing operator through an interface as shown in FIG. 3, for example. This embodiment shows a case where “edge enhancement” is selected as one of the operators. For selection of “edge enhancement”, “strong”, “normal”, “weak”, etc. are prepared as processing parameters. In some cases, a finer value may be set. “Strong”, “ordinary”, and “weak” are sensory terms and are not physical quantities, but in conventional image processing apparatuses, in actual processing, for example, as shown in FIG. Individual physical parameters (filter coefficients in this example) corresponding to “weak” are respectively substituted, and image processing is executed using fixed filter coefficients A, B, and C corresponding to the individual physical parameters. The terms “strong”, “ordinary”, and “weak” are only generally classified according to their characteristics, and a fixed filter coefficient is assigned to each of them.
[0020]
The actual image has various different characteristics such as a region where the edge is strongly visible and a region where the edge is blurred in the same image. For example, when processing with an edge strength of “strong” is performed on such an image, the edge is emphasized more strongly in an image area where the edge originally appears clearly. It may become saturated. An improvement effect by edge enhancement can be seen in the region where the edge is supposed to be emphasized. On the other hand, in a region where the density distribution is smooth, the noise component is excessively emphasized, so that although the density is smooth, the feeling of roughness becomes strong. When processing is performed on the same image with the same image processing parameters in this way, the difference in the state of the image obtained as a processing result is emphasized, and therefore a satisfactory processing result is not always obtained. This problem cannot be solved even if the image processing parameters are changed. Therefore, in the present invention, the degree of edge strength of the image to be processed is analyzed, and based on the value, the processing area to be classified and the image processing operator at that time are determined. Find out how to decide.
[0021]
An example of the image processing parameter / region determination method of the present invention will be described with reference to FIGS. When “edge enhancement” is selected as the image processing operator, first, the image data analysis processing unit performs analysis processing necessary for determining image processing parameters for edge enhancement. In this embodiment, as the analysis process, the edge strength of the entire image data is obtained. FIG. 5 is an edge intensity histogram as an analysis result. When the edge intensity histogram of the entire image shown in FIG. 5 is obtained, the edge intensity histogram is then divided by a plurality of predetermined threshold values TH1, TH2, and TH3. For each edge intensity range divided by these threshold values, pixels having edge intensity belonging to each intensity range are classified, and an application parameter is determined for each of the classified pixels. Details of the classification of image processing obtained by the result of the analysis processing are shown in FIG. As shown in FIG. 6, a plurality of threshold values (edge strength analysis results) TH11-TH33 for classifying the respective image processing parameters and regions, and edge enhancement application parameters (filter coefficients in this embodiment) for each of them. By associating the filters A1-A4, B1-B4, and C1-C4, the classification of the area in which each process is executed and the respective image processing parameters are determined. In the present embodiment, the edge strength is classified into four in each of the strong, medium, and weak image processing parameters, and image processing parameters (filter coefficients) for edge enhancement processing are set for each. These results are output as image processing parameters and image processing application area information. That is, the image areas to be processed are classified based on the edge intensity histogram, and image processing parameters to be applied to the respective image areas to be processed are determined.
[0022]
Another embodiment of the image processing parameter / region determination method will be described with reference to FIGS. For example, when “edge enhancement” is selected as the image processing operator, first, the image data analysis processing unit performs analysis processing necessary for setting image processing parameters for edge enhancement. In this embodiment, as analysis processing, the edge strength of the entire image data is obtained, and an edge strength histogram as shown in FIG. 5 is derived. Further, based on the derived edge intensity histogram, a median value, maximum value, minimum value, standard deviation, and the like of the edge intensity are obtained.
[0023]
First, classification of regions is performed by classifying the edge intensity histogram in FIG. 5 with a plurality of threshold values TH1, TH2, and TH3, as described above. Although these threshold values are used for classification, these threshold values may be fixed for each parameter. Further, as shown in FIG. 7, the edge average Es and the edge variance obtained from the image analysis result are shown. A value obtained by a function having various results such as Eσ, median, maximum, minimum, and standard deviation as parameters may be used. For example, as in the threshold value determination column in FIG. 7, TH1 = ω1 (Es, Eσ, α, β...) Is used as a determination function for the threshold value TH1. The characteristics of edge enhancement in each region when the processing regions are classified from the edge strength histograms in edge enhancement “strong”, “normal”, and “weak” are as shown in FIG. This is a function consisting of parameters such as edge average Es, edge variance Eσ, median value, maximum value, minimum value, standard deviation, and so on. Calculate and output the obtained result as an image processing parameter. For example, in FIG. 7, when “strong” is designated for edge enhancement, filter coefficients are determined by the functions f1, f2, and f3 for the filters A1, A2, and A3. When “normal” is designated in edge enhancement, the same processing is performed for the filters B1, B2, and B3 by the functions g1, g2, and g3. When “weak” is designated in edge enhancement, the filters C1, C2, and C3 are processed. The filter coefficients are determined by the functions h1, h2, and h3. The image processing parameter group and the image processing application area information obtained by the above operation are output to the image processing unit. The image processing unit executes image processing based on the instructed operator by changing the setting of the parameter to be applied to each classified region according to these parameters and processing region information. With the above processing, it is possible to realize a mechanism in which appropriate processing is executed for various characteristic regions in the same image whose processing results are sensuously received in response to an image processing operator instruction.
[0024]
Although only edge enhancement has been described in the present embodiment, the above method is executed by various image processing operators, for example, various operators such as “sheepness”, “contrast”, “color tone correction”, “image reduction”, and the like. It is also possible to set different processing parameters in the region.
[0025]
A case where the present invention is applied to a process of executing “color tone correction” will be described. For example, when it is desired to increase redness, first, the color tone analysis of the entire image is executed. That is, it is classified into two types, a reddish area and a non-red area. Or you may classify | categorize into three types, the area | region which does not have redness, the area | region which does not exist, and the area | region which exists in the middle. Next, if you want to further increase the redness of the reddish area, perform a process to increase redness by color correction in the reddish image area, and do not increase the redness in the other image areas. Correct the color tone. As a result of this correction, only the reddish image region portion becomes an image in which redness is further enhanced, and tone correction without influence of the redness increasing process is executed in the other image regions. Further, it is also possible to change the color correction of the other image area part without changing the color tone of the red part, that is, the reverse correction.
[0026]
Next, processing for image reduction will be described. When the image reduction operator executes, first, an edge strength histogram of the entire image is obtained by image analysis, and is classified into a region having a high edge strength and a region having no edge strength. When performing image reduction, a simple average value reduction is executed for a portion that does not include a pixel with high edge strength. On the other hand, when a region having a high edge strength is included, a pixel value having a high edge strength is weighted to perform image reduction processing in order to preserve the edge. In other words, different processing parameters are assigned to an image region having a high edge strength obtained by image analysis in order to execute a different processing from a region that does not include other portions having a high edge strength. Further, it is possible to classify the region into a region having a high edge strength, a region having a low edge strength, and an intermediate region, and assigning different parameters to each region, so that more delicate processing can be executed.
[0027]
According to the method of the present invention, parameter setting for various image processing operators, which has been complicated and difficult in the past, can be executed with settings that are easier for the operator to use than sensory processing. In the present embodiment, the case where there is one image processing parameter for the image processing operator has been described. However, depending on the image processing operator, it is possible to set two or more image processing parameters and execute the operator. It may be necessary. Even in this case, the correlation between the analysis result of the image data and each image processing parameter group is executed using a threshold value set for each image processing parameter, and appropriate multiple processing parameters are classified for each classified region. By classifying image areas by image analysis, it is possible to set optimum image processing parameters for each image area.
[0028]
【The invention's effect】
As described above, according to the image processing apparatus and the image processing method of the present invention, when an image processing operator is executed, image analysis is performed, and an appropriate image processing parameter is determined for each region based on the result. Can do. Therefore, the determination process using trial and error of the image processing parameter that has been conventionally performed is simplified, and appropriate parameter allocation to the image processing area at the time of image processing operator execution can be easily and accurately performed. It is possible to efficiently and easily obtain a desired image.
[Brief description of the drawings]
FIG. 1 is a block diagram showing the overall configuration of an image processing apparatus according to the present invention.
FIG. 2 is a flowchart illustrating the operation of the present invention.
FIG. 3 is a diagram illustrating an example in which an image processing operator is instructed by taking edge enhancement processing as an example in the present invention;
FIG. 4 is a diagram for explaining a connection between an image processing operator's instruction and an image processing parameter that is a conventional method using edge enhancement processing as an example;
FIG. 5 is a diagram illustrating a relationship between an edge strength histogram and a region classification.
FIG. 6 is a diagram for explaining the relationship between region classification and image processing parameters in image processing operator / region determination processing;
FIG. 7 is a diagram for explaining a region classification based on an image analysis result and an image processing parameter setting method.
[Explanation of symbols]
1 Image input section
2 Image storage unit
3 Image processing operator instruction section
4 Image data analysis processor
5 Image processing parameter / region determination processing unit
6 Image processing section

Claims (7)

Based on an image input means for inputting image data, an image data storage means for storing the input image data, an image processing technique instruction means for instructing an image processing technique for the image, and an instructed image processing technique Image data analysis means for performing analysis of target image data, and analyzing the analysis result of the image data analysis means , classifying the image data into one or a plurality of image processing areas, and for each image processing area an image processing adjustment indicators and area determination means for determining a value of the adjustment indicator of processing techniques, for each of the image processing area, the image processing by the value of the adjustment measure of the image processing area image processing technique which has been determined for An image processing apparatus comprising image processing means for performing image processing by a technique . Image data analysis performed by the image data analysis means and the target image data that is required to determine the value of the adjustment indicator which is used during the execution of the image processing method instructed by the image processing method instruction unit The image processing apparatus according to claim 1, wherein: The image processing adjustment index / region determining means performs an analysis process on the image data for each image processing method instructed by the image processing operator instruction means, analyzes the result, and sets a predetermined threshold. based on the value, classified into each image processing area, the image processing apparatus according to claim 1, wherein determining the image processing indicator to be applied to each said classified image processing area. The image processing method is edge enhancement processing, the image data analysis means executes edge strength analysis of an image, and the image processing adjustment index / region determination means has a filter coefficient for setting the strength of edge enhancement processing The image processing apparatus according to claim 1, wherein: is set as an adjustment index . The image processing method is a color tone correction process, the image data analysis unit executes a color tone analysis of the image, and the image processing adjustment index / region determination unit sets the strength of the color tone correction based on the result of the color tone analysis. The image processing apparatus according to claim 1, wherein an adjustment index to be determined is determined. The image processing method is an image reduction process, the image data analysis unit extracts an image region including a pixel having a high edge strength by the image data analysis, and the image processing adjustment index / region determination unit In an image area including high pixels, an adjustment index for performing image reduction is set by weighting pixels having high edge strength in order to preserve edges, and average value reduction is executed in other image areas. The image processing apparatus according to claim 1, wherein an adjustment index is set as described above. Image input means for inputting image data, image data storage means for storing the input image data, image processing technique instruction means for instructing an image processing technique for the image, and image processing means for performing image processing an image processing method in an image processing apparatus and a step of performing an analysis of the image data according to the image processing method instructed by the image processing technique instruction means, analyze the results of the image data analysis, the image data 1 or into a plurality of image processing regions, and away step to determine the adjustment indication of the image processing techniques per the image processing region, for each of the image processing region, are determined for the image processing region And a step of performing image processing by the image processing method according to a value of an adjustment index of the image processing method.

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