KR100463831B1 - Apparatus and method for optimizing image quality by using human visual characteristics - Google Patents

Abstract

The present invention relates to an apparatus and method for extracting optimized image quality using human visual characteristics, wherein a red / green / blue (RGB) image signal input to a display device is L * C * h (brightness, saturation, Color: L *, C *, h) RGB to L * C * h conversion unit for converting to a device independent color space; L * C * that adjusts to an image having an optimal color by adjusting and converting the color of the viewer for each of the pre-divided areas with respect to values converted into the L * C * h space by the RGB to L * C * h converter. h control unit; An L * C * h to RGB converter for converting a value adjusted to an optimal color in the L * C * h color space by an L * C * h control unit into an RGB image signal; An RGB to YPbPr conversion unit for converting an RGB image signal input to the display device into an YPbPr (luminance component (Y) chrominance component (PbPr): YPBPr) signal; An image control and enhancement unit for adjusting the YPbPr signal converted by the RGB to YPbPr conversion unit to an image of a quality preferred by an observer; An YPbPr to RGB converter for converting the YPbPr image adjusted to the viewer's preferred quality by the image adjusting and improving unit into an RGB image signal; Extracts coefficients corresponding to the RGB image signal adjusted to the optimal color converted by the L * C * h to RGB converter, and is adjusted to the YPbPr image of the viewer's preferred quality by the YPbPr to RGB converter. It includes a coefficient extraction unit for extracting the coefficient corresponding to the RGB image signal. Therefore, by using the extracted coefficients to convert the image to the optimized image quality, it is possible to reflect human visual characteristics and preferences and color reproduction similar to the original test in the development of the display system. When applied, it has the effect of developing high-definition display devices that provide rich color and clear images to display users.

Description

Apparatus and method for extracting optimized image quality using human visual characteristics {APPARATUS AND METHOD FOR OPTIMIZING IMAGE QUALITY BY USING HUMAN VISUAL CHARACTERISTICS}

The present invention relates to an apparatus and method for extracting optimized image quality using human visual characteristics, and in particular, to developing a digital display system (eg, a cathode ray tube (CRT), a liquid crystal display (LCD), a plasma display panel (PDP), ...). The present invention relates to an apparatus and a method for extracting coefficients of image quality optimized for a color scientific position and an image processing position using visual characteristics of a human (hereinafter, observer).

Typically, general display system development adjusts image quality through simple adjustments and measurements such as saturation and brightness and contrast adjustment.

This measurement method is not only difficult to implement device independent color reproduction from a color scientific standpoint, but also has a problem of overlooking the preference for the image quality of users who will use the actual display device.

As described above, the display system development includes the "color image reproducing apparatus" disclosed in the registration number 1966-32166, the "Image Lightness Recalling Using Sigmoidal Contrast Enhancement Functions" published in 1999, and the 2000 publication. "Gamut Compression Algorithm Development on the Basis of Observer Experimental Data" and the like.

The above-mentioned "color image reproduction apparatus" has the purpose of visual matching and color reproduction of a color image on a monitor and a printer output, and is composed of a modeling and a system for color reproduction and matching of an environment-independent luminous match, and its effect is observed according to the observer's color adaptation. This reflects the condition so that the color image on the monitor and the printer output can be more visually matched.

In addition, "Image Lightness Recalling Using Sigmoidal Contrast Enhancement Functions" has the purpose of minimizing the reduction of the contrast of lightness due to the difference in color gamut between devices, and obtained by conducting experiments and experiments of contrast conversion experiments using sigmoidal functions Based on the derived data, it is possible to derive a contrast-preserving algorithm, which can reduce the reduction in contrast when mapping the gamut between devices having different effects.

In addition, "Gamut Compression Algorithm Development on the Basis of Observer Experimental Data" aims to develop a gamut compression algorithm that employs observers in consideration of the gamut difference between devices, and uses L * C * h color conversion for observers. It is composed of color gamut compression tendency collection and general algorithm development, and the effect is reproduced as closely as possible with the color represented by the large device in the device with small gamut width.

As described above, when looking at the technology disclosed in the preceding paper, it is not only difficult to implement color-independent color reproduction from a color scientific standpoint, but also the problem of overlooking the preference of the image quality of users who will actually use the display device is still a problem. Remained.

Accordingly, the present invention has been made to solve the above-described problems, the purpose of which is to extract the coefficient of the image quality in relation to the color scientific position and the image processing position using the visual characteristics of the human (hereinafter, observer), and extracted The present invention provides an apparatus and method for extracting optimized image quality using human visual characteristics to convert and process coefficients to reproduce optimal image quality in a display system.

In the present invention for achieving the above object, the optimized image quality extraction apparatus using the human visual characteristics is a red / green / blue (RGB) image signal input to the display device L * C * h (brightness, Saturation, color: L *, C *, h) RGB to L * C * h conversion unit for converting into a device independent color space; L * C * that adjusts to an image having an optimal color by adjusting and converting the color of the viewer for each of the pre-divided areas with respect to values converted into the L * C * h space by the RGB to L * C * h converter. h control unit; An L * C * h to RGB converter for converting a value adjusted to an optimal color in the L * C * h color space by an L * C * h control unit into an RGB image signal; An RGB to YPbPr conversion unit for converting an RGB image signal input to the display device into an YPbPr (luminance component (Y) chrominance component (PbPr): YPBPr) signal; An image control and enhancement unit for adjusting the YPbPr signal converted by the RGB to YPbPr conversion unit to an image of a quality preferred by an observer; An YPbPr to RGB converter for converting the YPbPr image adjusted to the viewer's preferred quality by the image adjusting and improving unit into an RGB image signal; Extracts coefficients corresponding to the RGB image signal adjusted to the optimal color converted by the L * C * h to RGB converter, and is adjusted to the YPbPr image of the viewer's preferred quality by the YPbPr to RGB converter. And a coefficient extractor for extracting coefficients corresponding to the RGB image signals.

In addition, according to the present invention for achieving the above object, the optimized image quality extraction method using the human visual characteristics related to the color scientific position, when the RGB image signal corresponding to the test image is provided, the conversion unit from RGB to L * C * h A first step of providing a L * C * h control unit with a value converted from the RGB image signal provided by the L * C * h device independent color space; The L * C * h control unit has an optimal color by adjusting and converting the color of the viewer for each of the pre-divided areas with respect to the values converted into the L * C * h space by the RGB to L * C * h converter. A second step of adjusting to an image and providing the image to a conversion unit from L * C * h to RGB; The third L * C * h to RGB converter converts a value adjusted to an optimal color in the L * C * h color space by the L * C * h control unit to an RGB image signal and provides the result to the coefficient extractor. step; And a fourth step of extracting a coefficient corresponding to an RGB image signal adjusted to an optimal color converted by the L * C * h to RGB converter by the coefficient extractor.

In addition, according to the present invention for achieving the above object, in the optimized image quality extraction method using the human visual characteristics related to the position of the image processing, when the RGB image signal corresponding to the test image is provided, RGB to YPbPr conversion unit provided in the RGB A first step of adjusting and converting an image signal into an element affecting image quality and providing the same to an image adjusting and improving unit; A second step of adjusting the YPbPr signal converted by the RGB to YPbPr conversion unit to an image of a quality preferred by the observer and providing the YPbPr to RGB conversion unit by the image adjustment and enhancement unit; A third step of converting a value adjusted to an YPbPr image of a quality preferred by an observer by the image adjusting and improving unit into an RGB image signal and providing the coefficient extracting unit to the RGB image signal; And a fourth step of extracting a coefficient corresponding to the RGB image signal adjusted to the YPbPr image of the viewer's preferred quality by the coefficient extraction unit from the YPbPr to RGB converter.

1 is a block diagram of an apparatus for extracting optimized image quality using human visual characteristics according to the present invention;

2 is a view showing in detail the internal configuration of the L * C * h control unit shown in Figure 1,

3 is a view showing in detail the internal configuration of the image control and enhancement shown in Figure 1,

4 is a flowchart illustrating a method of extracting optimized image quality using human visual characteristics related to color scientific positions according to the present invention;

5 is a flowchart illustrating a method of extracting optimized image quality using a human visual characteristic related to an image processing position according to the present invention.

<Description of the symbols for the main parts of the drawings>

10: RGB to L * C * h converter 20: L * C * h controller

21: color gamut selection unit 23: L * control unit

25: C * control unit 27: h control unit

30: L * C * h to RGB converter 40: RGB to YPbPr converter

50: image control and enhancement unit 51: luminance extraction unit

52: sharpness control unit 53: contrast control unit

54: noise control unit 55: crush control unit

56: luminance merging unit 60: YPbPr to RGB conversion unit

70: coefficient extraction unit

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a block diagram of an apparatus for extracting an optimized image quality using human visual characteristics according to the present invention, wherein L * C * h (red, green, blue) in red / green / blue (RGB) Saturation, color: L *, C *, h) conversion unit 10, L * C * h control unit 20, L * C * h to RGB conversion unit 30, RGB to YPbPr (Luminance component (Y) chrominance component (PbPr): conversion unit 40 to YPbPr), image adjustment and enhancement unit 50, YPbPr to RGB conversion unit 60, and coefficient extraction unit 70 Include.

RGB to L * C * h conversion unit 10 is a block for converting from RGB space to L * C * h space in accordance with the characteristics of the display device to be developed. The color space is converted to the L * C * h control unit 20 and provided.

The L * C * h control unit 20 is configured to adjust and convert the observer's color by pre-divided areas with respect to values converted into the L * C * h space by the RGB to L * C * h converter 10. As a block for adjusting to an image having an optimal color by means of, as shown in FIG. 2, the color gamut selecting unit 21, the L * adjusting unit 23, the C * adjusting unit 25, and the h adjusting unit The part 27 is provided.

The color gamut selection unit 21 is a block for selecting a specific area of each of the L * C * h images, and selects a specific area previously divided by a specific area selected by the viewer, that is, L *, C *, and h.

When the specific area is selected by the color gamut selection unit 21, the L * adjusting unit 23 is divided into three areas of high, middle, and low brightness by the observer in the selected area, and is adjusted by performing color conversion. The adjusted brightness value is provided to the conversion unit 30 from L * C * h to RGB.

When the specific area is selected by the color gamut selection unit 21, the C * control unit 25 is divided into three areas of high saturation, middle and low by the observer in the selected area, and is adjusted by performing color conversion. The adjusted saturation value is provided to the conversion unit 30 from L * C * h to RGB.

h When the specific area is selected by the color gamut selection unit 21, the control unit 27 divides the color into six areas by the observer in the selected area and performs the conversion according to the band, and adjusts the adjusted color value. Is provided to the conversion unit 30 from L * C * h to RGB.

The L * C * h to RGB converter 30 extracts coefficients by converting a value adjusted to an optimal color in the L * C * h color space by the L * C * h control unit 20 to an RGB image signal. It provides to the part 70.

The RGB to YPbPr converter 40 is a block for controlling and converting an element affecting the image quality, and converts an input RGB image signal into an YPbPr signal and provides the image control and enhancement unit 50.

The image adjusting and improving unit 50 is a block that is adjusted to an image of a preferred quality by the observer's conversion and adjustment. As shown in FIG. 3, the brightness extracting unit 51 and the sharpness adjusting unit 52 are shown. ), A contrast control unit 53, a noise control unit 54, a lump control unit 55, and a brightness merging unit 56.

The luminance extractor 51 extracts only the luminance component Y from the YPbPr image converted by the RGB to YPbPr converter 40, and then the sharpness adjuster 52, the contrast adjuster 53, and the noise adjuster. 54, the luminance component extracted according to the adjustment control of each crush adjustment unit 55 is used.

The sharpness control unit 52 enhances the sharpness according to the user's preference while emphasizing the boundary portion of the image by using the unsharp masking method of the luminance component extracted by the luminance extractor 51, and improves the sharpness of the improved YPbPr image. The sharpness adjustment value is provided to the brightness merging unit 56.

The contrast controller 53 has 256 gray levels and adjusts the luminance component extracted by the luminance extractor 51 to lower portions of 128 and higher portions of 128 based on 128 so that the entire YPbPr image is bright. The degree of darkness is adjusted, and the contrast control value of the adjusted YPbPr image is provided to the brightness merging unit 56.

The noise controller 54 changes the quality of the YPbPr image by adding or removing white noise from the image using the luminance component and the filter extracted by the luminance extractor 51, and changes the noise control value of the changed YPbPr image. The merge unit 56 is provided.

The crush control unit 55 smoothly adjusts the crush of the YPbPr image by using the luminance component extracted by the luminance extractor 51, and adjusts the crush control value of the adjusted YPbPr image by the luminance merging unit 56. To provide.

The luminance merger 56 controls the luminance component Y controlled by each of the sharpness controller 52, the contrast controller 53, the noise controller 54, and the crush controller 55. PbPr) and provide the merged YPbPr image to the conversion unit 60 from YPbPr to RGB.

The YPbPr to RGB converter 60 converts the adjusted value of the YPbPr image of the viewer's preferred quality by the image adjusting and improving unit 50 into an RGB image signal and provides the converted value to the coefficient extracting unit 70.

The coefficient extractor 70 extracts a coefficient corresponding to the RGB image signal adjusted to the optimal color converted by the L * C * h-to-RGB conversion unit 30, and furthermore, the YPbPr to RGB conversion unit ( 60) extracts the coefficients corresponding to the RGB image signal adjusted to the YPbPr image of the viewer's preferred quality.

With reference to the flowchart of FIG. 4, the optimized image quality extraction method using the human visual characteristic related to the color scientific standpoint which concerns on this invention with the above-mentioned structure is demonstrated in detail.

First, the observer converts the provided RGB image signal into an L * C * h device independent color space when a red / green / blue (RGB) image signal corresponding to the test image is provided. In other words, the color characteristics of the developing display device are used to convert from an RGB image signal to XYZ space, and then to XYZ to L * a * b * space, and then to L * C * h space. The converted value of the L * C * h space is provided to the color gamut selection unit 21 in the L * C * h control unit 20 (step 400).

The color gamut selecting unit 21 is a block selected by the observer. When the observer selects a specific region to be converted in each of the L * C * h images (step 401), the L * adjusting unit 23 is selected in the selected specific region. In step 402, it is determined whether the color is adjusted using the C * adjusting unit 25 or the h adjusting unit 27.

When the observer wants to adjust the brightness in the selected region in the determination step 402, the observer controls the L * control unit 23 to adjust the brightness, and the adjusted brightness value is changed from L * C * h to RGB. Provided to the conversion unit 30 (step 403).

When the observer wants to adjust the saturation in the selected region in the determination step 402, the observer controls the saturation by controlling the C * control unit 25, and adjusts the saturation value from L * C * h to RGB. Provided to the conversion unit 30 (step 404).

When the observer wants to adjust the color in a specific area selected in the determination step 402, the observer controls the h adjusting unit 27 to adjust the color and converts the adjusted color value from L * C * h to RGB. To the unit 30 (step 405).

The L * C * h to RGB converter 30 converts each value adjusted to the optimal color in the L * C * h color space by the L * C * h control unit 20 to an RGB image signal. In more detail, the L * C * h space value converted by the L * C * h control unit 20 is converted to L * a * b * space, and then converted to XYZ space, and then converted The value of the XYZ space is converted into an RGB image signal and provided to the coefficient extracting unit 70 (step 406).

The coefficient extractor 70 extracts a coefficient corresponding to the RGB image signal adjusted to the optimal color converted by the L * C * h to RGB converter 30 (step 407).

5 is a flowchart illustrating a method of extracting optimized image quality using a human visual characteristic related to an image processing position according to the present invention.

First, the observer selects a test image and then converts the provided RGB image signal into an YPbPr signal that is adjusted and converted into a factor that affects image quality when an RGB image signal corresponding to the test image is provided. By applying ITU-R BT.709 (YPbPr) or ITU-R Rec.601 (YCbCr), the RGB image signal is converted into a signal having luminance component (Y) and chrominance component (PbPr (CbCr) to adjust the image. The brightness extracting unit 51 in the enhancement unit 50 is provided (step 501).

The luminance extractor 51 extracts only the luminance component Y from the YPbPr image converted by the RGB to YPbPr converter 40, and then uses the extracted luminance component to adjust the sharpness controller 52 and the contrast controller. In step 53, it is determined whether a desired control unit is selected for each of the noise control unit 54 and the crush control unit 55 (step 502).

When the observer wants to adjust the sharpness controller 52 in the determination step 502, the sharpness is improved by using the extracted luminance component, and the sharpness control value of the enhanced YPbPr image is provided to the brightness merger 56. (Step 503).

If the observer wants to adjust the contrast control unit 53 in the determination step 502, the brightness and darkness of the entire YPbPr image is adjusted using the extracted luminance component, and the contrast control value of the adjusted YPbPr image is adjusted. Provided to the brightness merging unit 56 (step 504).

If the observer wants to adjust the noise control unit 54 in the determination step 502, the quality of the YPbPr image is changed by adding or removing additional noise using the extracted luminance component, and the noise of the changed YPbPr image. The adjustment value is provided to the brightness merging unit 56 (step 505).

If the observer wants to adjust the crush control unit 55 in the determination step 502, the crush of the YPbPr image is smoothly adjusted by using the extracted luminance component, and the crush control value of the adjusted YPbPr image is adjusted. To the luminance merging unit 56 (step 506).

The luminance merger 56 controls the luminance component Y controlled by each of the sharpness controller 52, the contrast controller 53, the noise controller 54, and the crush controller 55. PbPr) and the merged YPbPr image is provided to the conversion unit 60 from YPbPr to RGB (step 507).

The YPbPr to RGB converter 60 converts the adjusted values of the YPbPr image of the viewer's preferred quality by the image adjusting and improving unit 50 into RGB image signals and provides them to the coefficient extracting unit 70 (step). 508).

The coefficient extractor 70 extracts a coefficient corresponding to an RGB image signal adjusted by the YPbPr to RGB converter 60 to an YPbPr image of a preferred quality (step 509).

Therefore, by using coefficients corresponding to the RGB image signal adjusted to the optimal color extracted by the coefficient extraction unit 70 and coefficients corresponding to the RGB image signal adjusted to the YPbPr image of the viewer's preferred quality. The Y, Pb, Pr conversion and LCH color conversion are conversion based on the standard. First, the Y, Pb, Pr conversion is applied to the ITU-709 standard. By Y = 0.701G + 0.087B + 0.212RPb = (BY) /1.826Pr= (RY) /1.576, which is capable of inverse transformation without error. Next, since the LCH color conversion is also a color conversion to the standard color space, no color difference error due to the color conversion occurs.

Therefore, the present invention extracts the coefficient of the image quality in relation to the color scientific position and the image processing position using the visual characteristics of the human (hereinafter, the observer), converts the image quality into the optimized image quality using the extracted coefficient, and displays the system. The development process can reflect human visual characteristics and preferences, and color reproduction similar to the original test source. Also, when the extracted coefficients are applied to a display system, they provide rich colors and clear images to display users. There is an effect that enables the development of high-definition display device.

Claims (18)

In the optimized image quality extraction apparatus in a display device system, A red / green / blue (RGB) image signal input according to the display device characteristics is converted into an L * C * h (brightness * saturation * color: L * C * h) device independent color space. A conversion unit from RGB to L * C * h; L * C which adjusts to an image having an optimal color by adjusting and converting the color of the viewer for each segmented area with respect to the values converted into the L * C * h space by the RGB to L * C * h converter. h control; An L * C * h to RGB converter for converting a value adjusted to an optimal color in the L * C * h color space by the L * C * h adjusting unit into an RGB image signal; An RGB to YPbPr converter for converting an RGB image signal input according to the display device characteristic into an YPbPr (luminance component (Y) chrominance component (PbPr): YPPPr) signal; An image adjusting and improving unit for adjusting the YPbPr signal converted by the RGB to YPbPr conversion unit to an image having a preferred quality; An YPbPr to RGB converter for converting the YPbPr image adjusted to the quality preferred by the viewer by the image adjusting and improving unit into an RGB image signal; Extracting coefficients corresponding to the RGB image signal adjusted to the optimal color converted by the L * C * h to RGB conversion unit, the YPbPr to RGB conversion unit to the YPbPr image of the preferred quality And a coefficient extraction unit for extracting coefficients corresponding to the adjusted RGB image signals. The method of claim 1, wherein the L * C * h control unit, A color gamut selecting unit configured to select a color gamut by the observer among pre-divided areas with respect to the values converted into the L * C * h spaces; When changing the brightness among the areas selected by the color gamut selection unit, the brightness is adjusted by an observer in the selected area, and L which provides the adjusted brightness value to the L * C * h to RGB conversion unit. Control unit; When the chroma is to be changed among the areas selected by the color gamut selection unit, the chroma is controlled by an observer in the selected area, and C is provided to the conversion unit from the L * C * h to RGB conversion unit. Control unit; When the color of the area selected by the color area selection unit is to be changed, the color is adjusted by an observer in the selected area, and the h provides the adjusted color value to the L * C * h to RGB conversion unit. Optimized image quality extraction apparatus using human visual characteristics, characterized in that it further comprises a control unit. The method of claim 1, wherein the image adjusting and improving unit, A luminance extractor which extracts only luminance components from the YPbPr image converted by the RGB to YPbPr converter; A sharpness controller for improving sharpness using the luminance component extracted by the brightness extractor and providing a sharpness control value of the enhanced YPbPr image; A contrast controller configured to adjust a light and dark degree of the entire YPbPr image by using the luminance component extracted by the luminance extractor and to provide a contrast control value of the adjusted YPbPr image; A noise control unit for changing the quality of the YPbPr image by adding / removing additional noise using the luminance component extracted by the luminance extractor and providing a noise control value of the changed YPbPr image; A crush control unit for smoothly controlling crushing of the YPbPr image by using the luminance component extracted by the luminance extracting unit, and providing a crush control value of the adjusted YPbPr image; The luminance (Y) signal adjusted by each of the sharpness control unit, the contrast control unit, the noise control unit, and the crush control unit is merged with the signal of the color difference component (PbPr), and the merged YPbPr image from the YPbPr to RGB An optimized image quality extraction apparatus using human visual characteristics, characterized in that it further comprises a luminance merging unit provided to the conversion unit. The method of claim 1, wherein the RGB to L * C * h conversion unit, Optimized image quality using human visual characteristics, characterized in that the conversion to the XYZ space by using the color characteristics of the display device, and then to the L * a * b * space, and then to the L * C * h space Extractor. The method of claim 1, wherein the L * C * h to RGB conversion unit, The L * C * h space value is converted into L * a * b * space, and then converted into XYZ space, and then the human visual characteristic is converted into an RGB image signal. Optimized image quality extraction device. The method of claim 1, wherein the RGB to YPbPr conversion unit, The RGB image signal is converted into a signal having a luminance component (Y) and a chrominance component (PbPr) by applying ITU-R BT.709 (YPbPr) or ITU-R Rec. 601 (YCbCr). Optimized image quality extraction device using visual characteristics. The method of claim 1, wherein the YPbPr to RGB conversion unit, The signal having the luminance component (Y) and the color difference component (PbPr) is converted into the RGB image signal by applying the ITU-R BT.709 (YPbPr) or ITU-R Rec. 601 (YCbCr) regulation. An optimized image quality extraction device using human visual characteristics. The method of claim 1, Optimization using human visual characteristics, which is applied to the display system development process by converting to the image quality of the optimized image using coefficients corresponding to the RGB image signal adjusted to the optimal color extracted by the coefficient extraction unit Image quality extraction device. Red / green / blue (RGB) to L * C * h (brightness * saturation * color: L * C * h), L * C * h control unit, L * C In the optimized image quality extraction method related to the color scientific position in a display device system having a * h to RGB conversion unit and a coefficient extraction unit, When an RGB image signal corresponding to a test image is provided, a value obtained by converting the provided RGB image signal into an L * C * h device independent color space by the RGB to L * C * h converter is converted into the L * C. a first step provided to the * h control unit; Optimal color by the observer's color control and conversion for each area pre-divided with respect to the values converted into the L * C * h space by the RGB to L * C * h converter in the L * C * h control unit Adjusting to an image having a second value and providing the L * C * h to RGB converter; The L * C * h to RGB converter converts a value adjusted to an optimal color in the L * C * h color space by the L * C * h control unit to an RGB image signal and provides it to the coefficient extractor. A third step of doing; And a fourth step of extracting a coefficient corresponding to an RGB image signal adjusted to an optimal color converted by the L * C * h to RGB converter by the coefficient extractor. Optimized image quality extraction method. 10. The method of claim 9, wherein the second step of adjusting the image having the optimal color by the L * C * h control unit, Selecting a color gamut by the viewer from among pre-divided areas with respect to values converted into an L * C * h space by using the color gamut selection unit in the L * C * h adjusting unit; When the brightness of the area selected by the color gamut selection unit is to be converted, the brightness is controlled by an observer in the selected area by the L * control unit in the L * C * h control unit, and the adjusted brightness value is converted into L. Providing to a * C * h to RGB conversion unit; When the saturation of the area selected by the color gamut selection unit is to be converted, the saturation is adjusted by an observer in the selected area by the C * control unit in the L * C * h control unit, and the adjusted saturation value is converted into L. Providing to a * C * h to RGB conversion unit; When the color of the area selected by the color gamut selection unit is to be converted, a color is adjusted by an observer in the selected area in the h adjusting part in the L * C * h adjusting part, and the adjusted color value is converted into the L *. A method of extracting optimized image quality using human visual characteristics, the method further comprising providing the conversion unit from C * h to RGB. 10. The method of claim 9, wherein the first step converted by the RGB to L * C * h conversion unit, Optimized image quality using human visual characteristics, characterized in that the conversion to the XYZ space by using the color characteristics of the display device, and then to the L * a * b * space, and then to the L * C * h space Extraction method. 10. The method of claim 9, wherein the third step of converting the L * C * h to RGB converter comprises: The L * C * h space value is converted into L * a * b * space, and then converted into XYZ space, and then the human visual characteristic is converted into an RGB image signal. Optimized image quality extraction method. The method of claim 9, wherein the fourth step extracted by the coefficient extracting unit comprises: Optimization using human visual characteristics, which is applied to the display system development process by converting to the image quality of the optimized image using coefficients corresponding to the RGB image signal adjusted to the optimal color extracted by the coefficient extraction unit Image quality extraction method. A red / green / blue (RGB) to YPbPr (luminance component (Y) chrominance component (PbPr): YPbPr) conversion unit, image adjustment and enhancement unit, YPbPr to RGB conversion unit, A method for extracting optimized image quality related to an image processing position in a display device system including a coefficient extractor, When an RGB image signal corresponding to a test image is provided, the RGB to YPbPr converter adjusts and converts the provided RGB image signal into a factor affecting image quality and provides the image control and enhancement unit. step; A second step of adjusting, by the image adjusting and improving unit, the YPbPr signal converted by the RGB to YPbPr conversion unit to an image having a preferred quality and providing the YPbPr to RGB conversion unit; A third step of converting, from the YPbPr to RGB converter, a value adjusted by the image adjusting and improving unit into an YPbPr image of a quality preferred by the observer to an RGB image signal, and providing the converted value to an RGB image signal; And a fourth step of extracting a coefficient corresponding to an RGB image signal adjusted to an YPbPr image of a preferred quality by the YPbPr to RGB converter by the coefficient extractor. Optimized image quality extraction method. The method of claim 14, wherein the adjusting of the image to the viewer's preferred quality by the image adjusting and improving unit comprises: Extracting only luminance components from the YPbPr image converted by the RGB to YPbPr conversion unit using the image adjustment and enhancement unit luminance extractor; Improving sharpness using the luminance component extracted by the brightness extracting unit using the sharpness adjusting unit in the image adjusting and improving unit, and providing a sharpness adjusting value of the improved YPbPr image; Adjusting the light and dark degree of the entire YPbPr image by using the luminance component extracted by the luminance extracting unit using the image adjusting and enhancement part contrast adjusting unit, and providing a contrast control value of the adjusted YPbPr image. ; The quality control of the YPbPr image is changed by adding / removing additional noise using the luminance component extracted by the luminance extractor using the image adjusting and improving unit noise control unit to provide a noise control value of the changed YPbPr image. Making; Using the luminance component extracted by the luminance extracting unit to adjust the crushing of the YPbPr image smoothly by using the crushing control unit in the image adjusting and improving unit, and providing a crushing control value of the adjusted YPbPr image. ; Merging the luminance (Y) signal adjusted by each of the sharpness control unit, the contrast control unit, the noise control unit, and the crush control unit by using the brightness control unit in the image control and enhancement unit, and merges the signal of the color difference component (PbPr) And providing the merged YPbPr image to the YPbPr to RGB converting unit. 15. The method of claim 14, wherein the first step of converting the RGB to YPbPr unit comprises: The RGB image signal is converted into a signal having a luminance component (Y) and a chrominance component (PbPr) by applying ITU-R BT.709 (YPbPr) or ITU-R Rec. 601 (YCbCr). An optimized image quality extraction method using visual characteristics. 15. The method of claim 14, wherein the third step is performed by the YPbPr to RGB conversion unit; The signal having the luminance component (Y) and the color difference component (PbPr) is converted into the RGB image signal by applying the ITU-R BT.709 (YPbPr) or ITU-R Rec. 601 (YCbCr) regulation. An optimized image quality extraction method using human visual characteristics. 15. The method of claim 14, wherein the fourth step extracted by the coefficient extraction unit, A human characterized in that it is applied to the display system development process by converting the image quality of the optimized image using the coefficient corresponding to the RGB image signal adjusted to the YPbPr image of the observer extracted by the coefficient extractor An optimized image quality extraction method using visual characteristics.