JP4558370B2 - Image processing apparatus and method, program, and recording medium - Google Patents

Description

  The present invention relates to an image processing apparatus, an image processing method, a program, and a recording medium, and in particular, detects sharp edges of pixel values corresponding to the contours of objects in an image, amplifies components other than edges, and The present invention relates to an image processing apparatus, an image processing method, a program, and a recording medium that improve the contrast of the recording medium.

  There exists an image processing apparatus using a non-linear filter (non-linear smoother) that smooths pixel values other than the edge in a state where an edge having a sharp change in pixel value corresponding to the contour of an object in the image is stored. (For example, refer to Patent Document 1).

  FIG. 1 shows a configuration of an example of a conventional image processing apparatus using this nonlinear filter. It is assumed that image data S1, which is digital data, is input to this image processing apparatus in units of frames. The image data S1 is a pixel value (image data of a frame image) of each pixel constituting the frame. In this image processing apparatus, it is assumed that the luminance signal in the image data is processed.

  In this image processing apparatus, the nonlinear filter 1 extracts a structure component ST1 corresponding to the contour of an object in a frame image from the input image data S1, and outputs the structure component ST1 to the structure correction unit 2 and the subtraction unit 3. The structure correction unit 2 corrects the contrast of the structure component ST1 input from the nonlinear filter 1 based on a preset conversion curve, and outputs the corrected structure component ST2 obtained as a result to the addition unit 5.

  The subtractor 3 subtracts the structure component ST1 extracted by the nonlinear filter 1 from the input image data S1, thereby generating a texture component (amplitude component) TX1 constituting the details of the frame image, and an amplifier 4 Output to. The amplification unit 4 amplifies the texture component TX1 input from the subtraction unit 3 with a predetermined amplification gain, and outputs the amplified structure component ST2 obtained as a result to the addition unit 5. The adding unit 5 generates the image data S2 by adding the corrected structure component ST2 and the amplified structure component ST2.

  FIG. 2 shows the structure correction procedure by this image processing apparatus by the change of the amplitude characteristic of the image data. The vertical and horizontal axes of the graph shown in FIG. 2 indicate the level of the luminance signal in the image data, and the amplitude between the white level that is 100% white and the black level that is 100% black. Takes a value. Note that 100% of the brightness level of white is determined to be 100IRE in a unit representing a relative ratio of image signals called IRE (Institute of Radio Engineers). According to the NTSC (National Television System Committee) standard adopted for Japanese television broadcasting, the white level is 100IRE and the black level is 0IRE.

  That is, the input image data S1 is input to the nonlinear filter 1 and the subtracting unit 3, and the structure component ST1 is extracted by the nonlinear filter 1. Further, the subtracting unit 3 subtracts the structure component ST1 from the image data S1 to generate the texture component TX1.

  The structure component ST1 is corrected to the structure component ST2 by the structure correction unit 2 based on a preset conversion curve. In the example of FIG. 2, correction is performed so that the low frequency side (black side) of luminance is increased and the high frequency side (white side) is decreased.

  On the other hand, the texture component TX1 is amplified by the amplification unit 4 with a predetermined amplification gain, and is added to the corrected structure component ST2 by the addition unit 5. This addition result is the image data S2.

  In the image data S2, the contrast of the structure component is corrected in the structure correction unit 2 and the texture component is amplified in the amplification unit 4, so that the contrast of the entire frame image is improved and the details in the frame image are reduced. It is expected to be emphasized.

JP 2003-348377 A

  However, in the conventional image processing apparatus described above, a single conversion curve is used when performing contrast correction on the texture component ST1 regardless of the image characteristics of the input data S1, so depending on the image characteristics of the image data S1. There has been a problem that a sufficient effect may not be obtained in terms of contrast correction.

  The present invention has been made in view of such circumstances, and enables contrast correction according to the image characteristics of an image to be processed.

The image processing apparatus of the present invention, by smoothing the pixel values of the non-sharp edge change of the pixel values in the image data, and smoothing means for generating a structure component which constitutes the outline of the image of the image data, Subtracting means for subtracting the generated structure component from the image data to generate a texture component constituting the details of the image of the image data, detecting means for detecting a histogram of luminance of the image data as image characteristics of the image data, and detection Using a luminance histogram as an image characteristic, generating means for generating a conversion curve formed by connecting line segments having higher slopes corresponding to higher frequency bands , and a structure component based on the generated conversion curve And a correction means for correcting the correction and an addition means for adding the corrected structure component and texture component.

The image processing apparatus of the present invention may further include an amplifying means for amplifying that were generated texture component, wherein the addition means, so that adds the auxiliary Tadashisa the structure component, and amplified texture component Can be.

The image processing method of the present invention, by smoothing the pixel values of the non-sharp edge change of the pixel values in the image data, a smoothing step of generating a structure component which constitutes the outline of the image of the image data, A subtracting step for subtracting the generated structure component from the image data to generate a texture component constituting the details of the image of the image data, a detecting step for detecting a histogram of luminance of the image data as an image characteristic of the image data, and detection Using the luminance histogram as the image characteristics, a generation step for generating a conversion curve formed by connecting line segments having higher slopes corresponding to higher frequency bands , and a structure component based on the generated conversion curve And a correction step for correcting the correction and an addition step for adding the corrected structure component and texture component

Recording medium program of the present invention, by smoothing the pixel values of the non-sharp edge change of the pixel values in the image data, a smoothing step of generating a structure component which constitutes the outline of the image of the image data A subtracting step for subtracting the generated structure component from the image data to generate a texture component constituting the details of the image of the image data; a detecting step for detecting a histogram of luminance of the image data as an image characteristic of the image data; using the histogram of the luminance of the detected image characteristics, a generation step of generating a conversion curve frequency is linked inclination is large segments corresponding higher band, based on the generated conversion curve, structure Correction step for correcting the component, and addition step for adding the corrected structure component and texture component To execute a process including the computer.

Program of the present invention, by smoothing the pixel values of the non-sharp edge change of the pixel values in the image data, a smoothing step of generating a structure component which constitutes the outline of the image of the image data is generated A subtracting step for subtracting the obtained structural component from the image data to generate a texture component constituting the details of the image of the image data, a detecting step for detecting a histogram of luminance of the image data as an image characteristic of the image data, and Using a luminance histogram as an image characteristic, a generation step for generating a conversion curve formed by connecting line segments with larger slopes corresponding to higher frequency bands , and correcting the structure component based on the generated conversion curve And a correction step that adds the corrected structure component and the texture component. Cause the computer to execute.

  In the image processing apparatus and method, and the program of the present invention, a structure component and a texture component of image data are generated. Further, the image characteristic of the image data is detected, a conversion curve is generated corresponding to the detected image characteristic, and the structure component is corrected based on the generated conversion curve. Further, the corrected structure component and texture component are added.

  According to the present invention, it is possible to perform contrast correction according to the image characteristics of an image to be processed.

  Embodiments of the present invention will be described below. Correspondences between constituent elements described in the claims and specific examples in the embodiments of the present invention are exemplified as follows. This description is to confirm that specific examples supporting the invention described in the claims are described in the embodiments of the invention. Therefore, even if there are specific examples that are described in the embodiment of the invention but are not described here as corresponding to the configuration requirements, the specific examples are not included in the configuration. It does not mean that it does not correspond to a requirement. On the contrary, even if a specific example is described here as corresponding to a configuration requirement, this means that the specific example does not correspond to a configuration requirement other than the configuration requirement. not.

  Further, this description does not mean that all the inventions corresponding to the specific examples described in the embodiments of the invention are described in the claims. In other words, this description is an invention corresponding to the specific example described in the embodiment of the invention, and the existence of an invention not described in the claims of this application, that is, in the future, a divisional application will be made. It does not deny the existence of an invention that is added by correction.

The image processing apparatus according to claim 1 (for example, the image processing apparatus 20 in FIG. 3)
Wherein the image change of the pixel values in the data to smooth the pixel values of the non-sharp edges, the smoothing means for generating a structure component which constitutes the outline of the image of the image data (e.g., non-linear filter of FIG. 3 23)
Subtracting means (for example, a subtracting unit 25 in FIG. 3) that subtracts the generated structure component from the image data and generates a texture component that constitutes image details of the image data;
Detecting means (for example, the image characteristic detecting unit 21 in FIG. 3) for detecting a histogram of luminance of the image data as image characteristics of the image data;
Using the detected luminance histogram as the image characteristic, generating means (for example, a correction curve generating unit shown in FIG. 3) that generates a conversion curve formed by connecting line segments having higher slopes corresponding to higher frequency bands . 22)
Correction means (for example, the structure correction unit 24 in FIG. 3) for correcting the structure component based on the generated conversion curve;
Adding means for adding the corrected structure component and the texture component (for example, the adding unit 27 in FIG. 3).

An image processing apparatus according to claim 2 is provided.
Amplifying means for amplifying that were generated the texture component (e.g., the amplifying unit 26 of FIG. 3) further comprises,
It said adding means, be summed and complement Tadashisa the said structure component, and said texture component is amplified.

The image processing method according to claim 3,
By smoothing the pixel value other than the sharp edge change of the pixel values in the image data, the smoothing step of generating a structure component which constitutes the outline of the image of the image data (e.g., step S3 of FIG. 7 )When,
Subtracting the generated structure component from the image data to generate a texture component that constitutes image details of the image data (for example, step S5 in FIG. 7);
A detection step (for example, step S1 in FIG. 7) for detecting a histogram of luminance of the image data as an image characteristic of the image data;
A generation step (for example, step S2 in FIG. 7) that uses a detected luminance histogram as the image characteristic to generate a conversion curve formed by connecting line segments having a larger slope corresponding to a higher frequency band . ,
A correction step (for example, step S4 in FIG. 7) for correcting the structure component based on the generated conversion curve;
An adding step (for example, step S7 in FIG. 7) for adding the corrected structure component and the texture component.

  Note that the correspondence between the configuration requirements described in the claims of the program of the present invention and the program recorded on the recording medium of the present invention and the specific example in the embodiment of the present invention is the image processing of the present invention described above. Since it is the same as that of the method, its description is omitted.

  Hereinafter, specific embodiments to which the present invention is applied will be described in detail with reference to the drawings.

  FIG. 3 shows a configuration example of an image processing apparatus according to an embodiment of the present invention. It is assumed that image data S1 that is digital data is input to the image processing apparatus 20 in units of frames. The image data S1 is a pixel value (image data of a frame image) of each pixel constituting the frame. The image processing apparatus 20 performs processing on the luminance signal in the image data.

  In the image processing device 20, the image characteristic detection unit 21 detects the histogram by dividing the luminance of the input image data S 1 into a plurality of bands, and outputs a detection signal CN 1 indicating the detection result to the correction curve generation unit 22. To do. The correction curve generation unit 22 generates a correction curve by connecting the same number of line segments as the number of bands of the histogram based on the detection signal CN1 from the image characteristic detection unit 21. At this time, the slope of the corresponding line segment is increased as the frequency is higher.

  4 to 6 show examples of detected luminance histograms (FIGS. 4A to 6A) and correction curves (FIGS. 4B to 6B) generated based on the histograms. 4B to 6B, the horizontal axis represents the luminance before correction, and the vertical axis represents the luminance after correction.

  As in the example shown in FIG. 4A, when the frequency of the luminance intermediate band is high, the generated correction curve has a large slope of the line segment corresponding to the intermediate band, as in the example shown in FIG. 4B. S-shaped curve. Further, when the luminance frequency increases as the frequency increases as in the example illustrated in FIG. 5A, the generated correction curve has a slope that increases as the frequency increases as illustrated in FIG. 5B. As a whole, it becomes a downwardly convex curve. Further, when the luminance frequency decreases as the frequency increases as in the example illustrated in FIG. 6A, the generated correction curve decreases in inclination as the frequency increases as illustrated in FIG. 6B. As a whole, the curve is convex upward.

  Returning to FIG. The non-linear filter 23 extracts the structure component ST1 corresponding to the contour of the object in the frame image from the input image data S1 and outputs it to the structure correction unit 24 and the subtraction unit 25. The structure correction unit 24 corrects the contrast of the structure component ST1 input from the nonlinear filter 23 based on the conversion curve generated by the correction curve generation unit 22, and adds the corrected structure component ST2 obtained as a result to the addition unit 27. Output to. The subtractor 25 subtracts the structure component ST1 extracted by the nonlinear filter 23 from the input image data S1, thereby extracting the texture component (amplitude component) TX1 constituting the details of the frame image and amplifying unit 26. Output to.

Amplification unit 26, a texture component TX1 which is inputted from the subtraction unit 25 to a predetermined amplification gain, and outputs the texture component TX 2 amplification already obtained as a result to the adder 27. The adding unit 27 generates the image data S2 by adding the corrected structure component ST2 and the amplified texture component TX2 .

  Next, contrast correction processing by the image processing apparatus 20 will be described with reference to the flowchart of FIG. This contrast correction process is started, for example, when image data S1 in units of frames is input to the image processing apparatus 20. This contrast correction process is performed in units of frames.

  In step S <b> 1, the image characteristic detection unit 21 detects the histogram by dividing the luminance of the input image data S <b> 1 into a plurality of bands, and outputs a detection signal CN <b> 1 indicating the detection result to the correction curve generation unit 22. In step S <b> 2, the correction curve generation unit 22 generates a correction curve formed by connecting line segments having larger slopes corresponding to higher frequency bands based on the detection signal CN <b> 1 from the image characteristic detection unit 21.

  In step S <b> 3, the nonlinear filter 23 extracts the structure component ST <b> 1 corresponding to the contour of the object in the frame image from the input image data S <b> 1 and outputs the structure component ST <b> 1 to the structure correction unit 24 and the subtraction unit 25. In step S4, the structure correction unit 24 corrects the contrast of the structure component ST1 input from the nonlinear filter 23 based on the conversion curve generated by the correction curve generation unit 22, and the corrected structure component ST2 obtained as a result thereof. Is output to the adder 27.

In step S5, the subtraction unit 25 extracts the texture component (amplitude component) TX1 constituting the details of the frame image by subtracting the structure component ST1 extracted by the nonlinear filter 23 from the input image data S1. And output to the amplifying unit 26. In step S <b> 6, the amplification unit 26 amplifies the texture component TX < b> 1 input from the subtraction unit 25 with a predetermined amplification gain, and outputs the amplified texture component TX 2 obtained as a result to the addition unit 27. In step S7, the addition unit 27 generates the image data S2 by adding the corrected structure component ST2 and the amplified texture component TX2 . This is the end of the description of the contrast correction process.

  In the image data S2 generated by the contrast correction process, the contrast component of the structure component is corrected by using a correction curve that is applied to the image characteristics (specifically, the luminance histogram) of the image data S1. Therefore, the contrast correction works more effectively.

  In the image characteristic detection unit 21, instead of (or in addition to) the luminance histogram of the input image data S1, for example, at least one of the average value, the maximum value, or the minimum value of the luminance of the input image data S1 is obtained. Detection may be performed, and the correction curve generation unit 22 may generate a correction curve based on the detection result.

  By the way, the series of processes described above can be executed by hardware, but can also be executed by software. When a series of processing is executed by software, a program constituting the software may execute various functions by installing a computer incorporated in dedicated hardware or various programs. For example, a general-purpose personal computer configured as shown in FIG. 8 is installed from the recording medium.

  The personal computer 50 includes a CPU (Central Processing Unit) 51. An input / output interface 55 is connected to the CPU 51 via the bus 54. A ROM (Read Only Memory) 52 and a RAM (Random Access Memory) 53 are connected to the bus 54.

  The input / output interface 55 includes a keyboard for inputting operation commands by a user, an input unit 56 including an input device such as a mouse, an output unit 57 including a display for displaying image data, and a hard disk for storing programs and various data. A storage unit 58 made up of a drive and the like, and a communication unit 59 made up of a LAN (Local Area Network) adapter and the like, which executes communication processing via a network represented by the Internet, are connected. Also, a magnetic disk (including a flexible disk), an optical disk (including a CD-ROM (Compact Disc-Read Only Memory), a DVD (Digital Versatile Disc)), a magneto-optical disk (including an MD (Mini Disc)), or a semiconductor A drive 60 for reading / writing data from / to a recording medium 61 such as a memory is connected.

  A program for causing the personal computer 50 to execute the above-described series of processing is supplied to the personal computer 50 while being stored in the recording medium 61, read by the drive 60, and installed in a hard disk drive built in the storage unit 58. Has been. The program installed in the storage unit 58 is loaded from the storage unit 58 to the RAM 53 and executed by a command of the CPU 51 corresponding to a command from the user input to the input unit 56.

  In this specification, the steps executed based on the program are executed in parallel or individually even if they are not necessarily processed in time series, as well as processes executed in time series according to the described order. It also includes processing.

  The program may be processed by a single computer, or may be processed in a distributed manner by a plurality of computers. Furthermore, the program may be transferred to a remote computer and executed.

  In the present specification, the step of describing the program recorded in the recording medium is not limited to the processing performed in time series according to the described order, but is not necessarily performed in time series, either in parallel or individually. The process to be executed is also included.

It is a block diagram which shows an example of a structure of the conventional image processing apparatus using a nonlinear filter. It is a figure which shows the outline | summary of the process by the image processing apparatus of FIG. It is a block diagram which shows the structural example of the image processing apparatus to which this invention is applied. It is a figure which shows the example of the histogram of a brightness | luminance, and the conversion curve corresponding to it. It is a figure which shows the example of the histogram of a brightness | luminance, and the conversion curve corresponding to it. It is a figure which shows the example of the histogram of a brightness | luminance, and the conversion curve corresponding to it. 4 is a flowchart for explaining contrast correction processing by the image processing apparatus in FIG. 3. It is a block diagram which shows the structural example of the general purpose computer to which this invention is applied.

Explanation of symbols

  21 image characteristic detection unit, 22 correction curve generation unit, 23 nonlinear filter, 24 structure correction unit, 25 subtraction unit, 26 amplification unit, 27 addition unit

Claims (5)

In an image processing apparatus that processes image data,
Smoothing means for smoothing pixel values other than edges where the change in pixel value in the image data is steep, thereby generating a structure component that constitutes the contour of the image of the image data;
Subtracting means for subtracting the generated structure component from the image data and generating a texture component that constitutes image details of the image data;
Detecting means for detecting a luminance histogram of the image data as an image characteristic of the image data;
A generation unit that generates a conversion curve formed by connecting line segments having a larger slope corresponding to a higher frequency band using a histogram of luminance as the detected image characteristic;
Correction means for correcting the structure component based on the generated conversion curve;
An image processing apparatus comprising: an adding unit that adds the corrected structure component and the texture component. Amplifying means for amplifying the generated texture component;
The image processing apparatus according to claim 1, wherein the adding unit adds the corrected structure component and the amplified texture component. In an image processing method for processing image data,
The change in the pixel values in the image data to smooth the pixel values of the non-sharp edges, the smoothing step of generating a structure component which constitutes the outline of the image of the image data,
A subtracting step of subtracting the generated structure component from the image data to generate a texture component that constitutes image details of the image data;
A detection step of detecting a luminance histogram of the image data as an image characteristic of the image data;
Using a luminance histogram as the detected image characteristic, a generation step for generating a conversion curve formed by connecting line segments having a larger slope corresponding to a higher frequency band ; and
A correction step of correcting the structure component based on the generated conversion curve;
An image processing method comprising: an adding step of adding the corrected structure component and the texture component. A program for processing image data,
The change in the pixel values in the image data to smooth the pixel values of the non-sharp edges, the smoothing step of generating a structure component which constitutes the outline of the image of the image data,
A subtracting step of subtracting the generated structure component from the image data to generate a texture component that constitutes image details of the image data;
A detection step of detecting a luminance histogram of the image data as an image characteristic of the image data;
Using a luminance histogram as the detected image characteristic, a generation step for generating a conversion curve formed by connecting line segments having a larger slope corresponding to a higher frequency band ; and
A correction step of correcting the structure component based on the generated conversion curve;
A program that causes a computer to execute a process including an adding step of adding the corrected structure component and the texture component. A program for processing image data,
The change in the pixel values in the image data to smooth the pixel values of the non-sharp edges, the smoothing step of generating a structure component which constitutes the outline of the image of the image data,
A subtracting step of subtracting the generated structure component from the image data to generate a texture component that constitutes image details of the image data;
A detection step of detecting a luminance histogram of the image data as an image characteristic of the image data;
Using a luminance histogram as the detected image characteristic, a generation step for generating a conversion curve formed by connecting line segments having a larger slope corresponding to a higher frequency band ; and
A correction step of correcting the structure component based on the generated conversion curve;
A computer-readable recording medium storing a program for causing a computer to execute a process including an adding step of adding the corrected structure component and the texture component.

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