WO2019127667A1 - 侦测图像中高频成分的方法及装置 - Google Patents

侦测图像中高频成分的方法及装置 Download PDF

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Publication number
WO2019127667A1
WO2019127667A1 PCT/CN2018/072507 CN2018072507W WO2019127667A1 WO 2019127667 A1 WO2019127667 A1 WO 2019127667A1 CN 2018072507 W CN2018072507 W CN 2018072507W WO 2019127667 A1 WO2019127667 A1 WO 2019127667A1
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Prior art keywords
image pixel
value
difference
grayscale
primary color
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PCT/CN2018/072507
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English (en)
French (fr)
Inventor
关晓亮
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深圳市华星光电技术有限公司
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Priority to JP2020529280A priority Critical patent/JP6951578B2/ja
Priority to KR1020207021433A priority patent/KR102350818B1/ko
Priority to US15/749,013 priority patent/US10553165B2/en
Priority to EP18893749.4A priority patent/EP3734580A4/en
Publication of WO2019127667A1 publication Critical patent/WO2019127667A1/zh

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    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G3/00—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes
    • G09G3/006—Electronic inspection or testing of displays and display drivers, e.g. of LED or LCD displays
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G3/00—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes
    • G09G3/20—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix no fixed position being assigned to or needed to be assigned to the individual characters or partial characters
    • G09G3/34—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix no fixed position being assigned to or needed to be assigned to the individual characters or partial characters by control of light from an independent source
    • G09G3/36—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix no fixed position being assigned to or needed to be assigned to the individual characters or partial characters by control of light from an independent source using liquid crystals
    • G09G3/3607—Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix no fixed position being assigned to or needed to be assigned to the individual characters or partial characters by control of light from an independent source using liquid crystals for displaying colours or for displaying grey scales with a specific pixel layout, e.g. using sub-pixels
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G06T2207/30121—CRT, LCD or plasma display
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G2320/00—Control of display operating conditions
    • G09G2320/02—Improving the quality of display appearance
    • G09G2320/0242—Compensation of deficiencies in the appearance of colours
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G2320/00—Control of display operating conditions
    • G09G2320/02—Improving the quality of display appearance
    • G09G2320/028—Improving the quality of display appearance by changing the viewing angle properties, e.g. widening the viewing angle, adapting the viewing angle to the view direction
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G2320/00—Control of display operating conditions
    • G09G2320/06—Adjustment of display parameters
    • G09G2320/0666—Adjustment of display parameters for control of colour parameters, e.g. colour temperature
    • G—PHYSICS
    • G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
    • G09G—ARRANGEMENTS OR CIRCUITS FOR CONTROL OF INDICATING DEVICES USING STATIC MEANS TO PRESENT VARIABLE INFORMATION
    • G09G2360/00—Aspects of the architecture of display systems
    • G09G2360/16—Calculation or use of calculated indices related to luminance levels in display data

Definitions

  • the present invention relates to the field of display technologies, and in particular, to a method and apparatus for detecting high frequency components in an image.
  • LCD Liquid crystal display
  • PDAs personal digital assistants
  • digital cameras computer screens or laptop screens, etc.
  • liquid crystal displays which include a liquid crystal display panel and a backlight module.
  • the working principle of the liquid crystal display panel is to fill liquid crystal molecules between a Thin Film Transistor Array Substrate (TFT Array Substrate) and a Color Filter (CF) substrate, and apply driving on the two substrates.
  • TFT Array Substrate Thin Film Transistor Array Substrate
  • CF Color Filter
  • the liquid crystal panel Since the liquid crystal molecules have optical anisotropy characteristics, the liquid crystal panel has a color shift problem at a large viewing angle.
  • the prior art proposes a color shift compensation algorithm implemented by preprocessing the input data signal, and the specific implementation steps of the color shift compensation algorithm include:
  • the original grayscale values of the respective primary color components of each image pixel respectively generate a first display grayscale value and a second display grayscale value, and respectively control the same color on the liquid crystal panel by using the first display grayscale value and the second display grayscale value respectively Display brightness of two sub-pixels, wherein the first display gray scale value is greater than the second display gray scale value, such that driving voltages applied to the two sub-pixels are different, such that liquid crystal molecules of the two sub-pixels are deflected into different angles, thereby Viewing the picture from different angles can obtain better viewing effect and achieve the purpose of reducing the color shift.
  • an image is generally composed of a plurality of image pixels, each of which includes three primary color components of red, green, and blue, and provides a display for each primary color component of each image pixel when driving an image display.
  • the required grayscale value is used to control the brightness of the primary color component, thereby causing the primary color component to display a corresponding color, thereby effecting display of the image.
  • each primary color component controls two sub-pixels of the same color and adjacent, that is, the red component correspondingly controls two adjacent red sub-pixels, and the green component correspondingly controls two adjacent green sub-pixels.
  • the blue component correspondingly controls two adjacent blue sub-pixels, so that the first display gray scale and the second display gray scale generated by the original gray scale value of the red component respectively control the display brightness of the corresponding two red sub-pixels
  • the first display gray scale and the second display gray scale generated by the original gray scale value of the green component respectively control the display brightness of the corresponding two green sub-pixels, and the first display generated by the original gray scale value of the blue component
  • the gray scale and the second display gray scale respectively control the display brightness of the corresponding two blue sub-pixels.
  • the display brightness of each image pixel is a mixture of the display brightness of its corresponding primary color component, and the display brightness of each primary color component is a mixture of the display brightness of its corresponding two sub-pixels, generally, in order to be displayed by the first gray scale and
  • the display brightness of the two sub-pixels of the second display gray scale control can be kept consistent with the display brightness of the two sub-pixels controlled by the original gray scale value, and the display brightness corresponding to the first display gray scale value is usually set.
  • the sum of the display brightness corresponding to the gray scale value is equal to twice the display brightness corresponding to the original gray scale value.
  • a high frequency component In addition, in image processing, where the brightness or gradation of the image is intensely changed is called a high frequency component, and vice versa is a low frequency component.
  • detection of a high frequency component in the image is limited to the detected image.
  • the pixel and its adjacent image pixels have a small detection range.
  • the high-frequency component is processed by the color shift compensation algorithm, and a graininess occurs, resulting in a decrease in display quality.
  • the object of the present invention is to provide a method for detecting high frequency components in an image, which can optimize the detection process of high frequency components in the image, improve display defects caused by the use of the color shift compensation algorithm, and improve display quality.
  • the present invention provides a method of detecting high frequency components in an image, comprising the following steps:
  • the image pixel located in the first layer surrounds the image pixel to be detected, and the image pixel located in the second layer surrounds an image pixel located in the first layer;
  • Step S2 calculating a first grayscale difference value, where the first grayscale difference value is a difference between an original grayscale value of the image pixel to be detected and an original grayscale value of each image pixel located in the first layer.
  • Step S3 Calculating a second grayscale difference value, where the second grayscale difference is a difference between an original grayscale value of the image pixel to be detected and an original grayscale value of each image pixel located in the second layer.
  • the method further includes:
  • Each of the image pixels in the step S1 includes a first primary color component, a second primary color component, and a third primary color component;
  • the original grayscale value of each image pixel includes: an original grayscale value of the first primary color component, an original grayscale value of the second primary color component, and an original grayscale value of the third primary color component;
  • the difference between the original grayscale value of the image pixel to be detected and the original grayscale value of the image pixel located in the first layer is: the original grayscale value of the first primary color component in the image pixel to be detected and the first a difference between original grayscale values of the first primary color component of the image pixels of one layer, an original grayscale value of the second primary color component of the image pixel to be detected, and a second primary color component of the image pixel located in the first layer.
  • the difference between the original grayscale value and the difference between the original grayscale value of the third primary color component in the image pixel to be detected and the original grayscale value of the third primary color component in the image pixel of the first layer one of;
  • the difference between the original grayscale value of the image pixel to be detected and the original grayscale value of the image pixel located in the second layer is: the original grayscale value of the first primary color component in the image pixel to be detected and the first a difference between original grayscale values of the first primary color component of the image pixels of the second layer, an original grayscale value of the second primary color component of the image pixel to be detected, and a second primary color component of the image pixel located in the second layer.
  • the difference between the original grayscale value and the difference between the original grayscale value of the third primary color component in the image pixel to be detected and the original grayscale value of the third primary color component in the image pixel of the second layer one of.
  • the acquiring unit is configured to obtain an original grayscale value of an image pixel in a to-be-processed image, where the image pixel includes: an image pixel to be detected, an image pixel located in the first layer, and an image pixel located in the second layer; An image pixel located in the first layer surrounds the image pixel to be detected, and the image pixel located in the second layer surrounds an image pixel located in the first layer;
  • the first calculating unit is configured to calculate a first grayscale difference value and a second grayscale difference value, where the first grayscale difference value is an original grayscale value of the image pixel to be detected and located at the first layer The maximum value of the difference of the original grayscale values of the respective image pixels; the second grayscale difference is the original grayscale value of the image pixel to be detected and the original grayscale of each image pixel located in the second layer The maximum value of the difference in values;
  • the second calculating unit is configured to calculate a target grayscale difference value according to the target grayscale difference algorithm, the first grayscale difference value, and the second grayscale difference value;
  • the determining unit is configured to compare the target grayscale difference with the preset grayscale threshold. If the target grayscale difference is greater than the grayscale threshold, determine that the image pixel to be detected is a high frequency image pixel, otherwise It is determined that the image pixel to be detected is a low frequency image pixel.
  • the device for detecting a high frequency component in an image further includes: an adjusting unit connected to the determining unit;
  • the adjusting unit is configured to adjust an actual grayscale value of the high frequency image pixel according to a preset adjustment algorithm and a target grayscale difference, and reduce an actual grayscale value and an original grayscale value of the high frequency image pixel.
  • the difference between the actual grayscale values and the original grayscale values of the high frequency image pixels is obtained by color shift compensation to obtain grayscale values.
  • Each image pixel includes a first primary color component, a second primary color component, and a third primary color component arranged in sequence;
  • the original grayscale value of each image pixel includes: an original grayscale value of the first primary color component, an original grayscale value of the second primary color component, and an original grayscale value of the third primary color component;
  • the difference between the original grayscale value of the image pixel to be detected and the original grayscale value of the image pixel located in the first layer is: the original grayscale value of the first primary color component in the image pixel to be detected and the first a difference between original grayscale values of the first primary color component of the image pixels of one layer, an original grayscale value of the second primary color component of the image pixel to be detected, and a second primary color component of the image pixel located in the first layer.
  • the difference between the original grayscale value and the difference between the original grayscale value of the third primary color component in the image pixel to be detected and the original grayscale value of the third primary color component in the image pixel of the first layer one of;
  • the difference between the original grayscale value of the image pixel to be detected and the original grayscale value of the image pixel located in the second layer is: the original grayscale value of the first primary color component in the image pixel to be detected and the first a difference between original grayscale values of the first primary color component of the image pixels of the second layer, an original grayscale value of the second primary color component of the image pixel to be detected, and a second primary color component of the image pixel located in the second layer.
  • the difference between the original grayscale value and the difference between the original grayscale value of the third primary color component in the image pixel to be detected and the original grayscale value of the third primary color component in the image pixel of the second layer one of.
  • Gray scale value L is the actual grayscale value of the high frequency image pixel before the adjustment algorithm is adjusted, C is a preset adjustment coefficient, and the adjustment coefficient ranges from 0 to 1, and the adjustment coefficient follows The target gray scale difference increases and decreases.
  • the invention also provides a method for detecting high frequency components in an image, comprising the following steps:
  • Step S1 Obtain an original grayscale value of an image pixel in the image to be processed, where the image pixel includes: an image pixel to be detected, an image pixel located in the first layer, and an image pixel located in the second layer;
  • the image pixel located in the first layer surrounds the image pixel to be detected, and the image pixel located in the second layer surrounds an image pixel located in the first layer;
  • Step S2 calculating a first grayscale difference value, where the first grayscale difference value is a difference between an original grayscale value of the image pixel to be detected and an original grayscale value of each image pixel located in the first layer.
  • Step S3 Calculating a second grayscale difference value, where the second grayscale difference is a difference between an original grayscale value of the image pixel to be detected and an original grayscale value of each image pixel located in the second layer.
  • Step S4 calculating a target grayscale difference according to the target grayscale difference algorithm, the first grayscale difference value, and the second grayscale difference value;
  • Step S5 Comparing the target grayscale difference with the preset grayscale threshold. If the target grayscale difference is greater than the grayscale threshold, determining that the image pixel to be detected is a high frequency image pixel, otherwise determining the to The detected image pixels are low frequency image pixels;
  • the method further includes: when the image pixel to be detected is a high frequency image pixel, the method further includes:
  • Step S6 Adjust an actual grayscale value of the high frequency image pixel according to a preset adjustment algorithm and a target grayscale difference, and reduce an absolute difference between an actual grayscale value of the high frequency image pixel and an original grayscale value. value;
  • the actual grayscale value is obtained by color shift compensation after obtaining the grayscale value of the original grayscale value of the high frequency image pixel;
  • the original grayscale value of each image pixel includes: an original grayscale value of the first primary color component, an original grayscale value of the second primary color component, and an original grayscale value of the third primary color component;
  • the difference between the original grayscale value of the image pixel to be detected and the original grayscale value of the image pixel located in the first layer is: the original grayscale value of the first primary color component in the image pixel to be detected and the first a difference between original grayscale values of the first primary color component of the image pixels of one layer, an original grayscale value of the second primary color component of the image pixel to be detected, and a second primary color component of the image pixel located in the first layer.
  • the difference between the original grayscale value and the difference between the original grayscale value of the third primary color component in the image pixel to be detected and the original grayscale value of the third primary color component in the image pixel of the first layer one of;
  • the difference between the original grayscale value of the image pixel to be detected and the original grayscale value of the image pixel located in the second layer is: the original grayscale value of the first primary color component in the image pixel to be detected and the first a difference between original grayscale values of the first primary color component of the image pixels of the second layer, an original grayscale value of the second primary color component of the image pixel to be detected, and a second primary color component of the image pixel located in the second layer
  • the difference between the original grayscale value and the difference between the original grayscale value of the third primary color component in the image pixel to be detected and the original grayscale value of the third primary color component in the image pixel of the second layer one of;
  • the present invention provides a method of detecting high frequency components in an image, using the difference between the original grayscale value of the image pixel to be detected and the original grayscale value of each image pixel located in the first layer.
  • the maximum value is used as the first grayscale difference value
  • the maximum value of the difference between the original grayscale value of the image pixel to be detected and the original grayscale value of each image pixel located in the second layer is used as the second grayscale difference value
  • the detection process of high-frequency components in the image improves the display failure caused by the color shift compensation algorithm and
  • FIG. 1 is a schematic diagram of steps S1 to S3 of a method for detecting high frequency components in an image according to the present invention
  • the present invention provides a method for detecting high frequency components in an image, comprising the following steps:
  • Step S1 Obtain an original grayscale value of an image pixel in the image to be processed, the image pixel includes: an image pixel 100 to be detected, an image pixel 200 located in the first layer, and an image pixel 300 located in the second layer;
  • each image to be processed is composed of a plurality of image pixels, each of the image pixels includes a first primary color component, a second primary color component, and a third primary color component, and the original grayscale value of the image pixel includes: a first primary color The original grayscale value of the component, the second primary color component, and the third primary color component, by providing a grayscale value required for each primary color component of each image pixel to control the brightness of the primary color component, thereby causing the primary color The component displays the corresponding color, thereby realizing the display of the image.
  • the first primary color component, the second primary color component, and the third primary color component are a red component, a green component, and a blue component, respectively.
  • each image pixel may further comprise a fourth primary color component, the fourth primary color component presenting a white color.
  • the image pixel 100 to be detected, the image pixel 200 located in the first layer, and the image pixel 300 located in the second layer are arranged in 5 rows and 5 columns, wherein The image pixel 100 is located at the center, that is, the third row and the third column.
  • the image pixel 200 located in the first layer surrounds the image pixel 100 to be detected, and is located in the second row, the second column, the second row, the third column, and the second column.
  • Row 4, 3, 2, 3, 4, 4, 2, 4, 3, and 4, and the remaining 16 image pixels are For the image pixels 300 located in the second layer, it is apparent that the image pixels 300 located in the second layer are surrounded by the image pixels 200 located in the first layer.
  • the image pixel 100 to be detected when the image pixel 100 to be detected is located at an edge or a corner of the image, the image pixel 100 to be detected, the image pixel 200 located in the first layer, and the image pixel 300 located in the second layer
  • the image pixels 100 to be detected, the image pixels 200 located in the first layer, and the image pixels 100 to be detected are located in the fifth row and the fifth column, for example, when the image pixel 100 to be detected is located at the left edge of the image to be processed.
  • the image pixels 300 located in the second layer can be arranged in only 5 rows and 3 columns, wherein the image pixels 100 to be detected are located in the third row and the first column, and the image pixels 200 located in the first layer are located in the second row and the first column.
  • Step S2 Calculating a first grayscale difference value, where the first grayscale difference is a difference between an original grayscale value of the image pixel 100 to be detected and an original grayscale value of each image pixel 200 located in the first layer. The maximum value of the value.
  • F2 Max(
  • F4 Max(
  • F5 Max(
  • F6 Max(
  • F7 Max(
  • F8 Max(
  • R0, G0, and B0 respectively represent original grayscale values of the first primary color component, the second primary color component, and the third primary color component in the image pixel 100 to be detected
  • R1 to R8 respectively represent 8 located in the first layer
  • the original grayscale value of the first primary color component of the image pixel 200, G1 to G8 respectively represent the original grayscale values of the second primary color components of the image pixels 200 located in the first layer
  • B1 to B8 respectively represent 8 in the first
  • the original grayscale value of the third primary color component of the image pixel 200 of the layer, F1 to F8 respectively represent the difference between the original grayscale value of the image pixel 200 located in the first layer and the image pixel 100 to be detected, FA1 Is the first grayscale difference.
  • Step S3 calculating a second grayscale difference value, where the second grayscale difference value is a difference between a grayscale value of the image pixel 100 to be detected and a grayscale value of each image pixel 300 located in the second layer.
  • the difference between the grayscale value of the image pixel 100 to be detected and the original grayscale value of the image pixel 300 located in the second layer is: the original grayscale value of the first primary color component in the image pixel 100 to be detected and a difference between original grayscale values of the first primary color component in the image pixel 300 of the second layer, an original grayscale value of the second primary color component in the image pixel 100 to be detected, and the image pixel located in the second layer
  • the difference between the original grayscale values of the second primary color component in 300 and the original grayscale value of the third primary color component in the image pixel to be detected and the original grayscale of the third primary color component in the image pixel 300 of the second layer The largest of the differences between the order values.
  • the image pixel 100 to be detected, the image pixel 200 located in the first layer, and the image pixel 300 located in the second layer are arranged in 5 rows and 5 columns.
  • the calculation process in the step S3 is as follows. :
  • F9 Max(
  • F10 Max(
  • F11 Max(
  • F12 Max(
  • F13 Max(
  • F14 Max(
  • F15 Max(
  • F16 Max(
  • F18 Max(
  • F20 Max(
  • F21 Max(
  • F23 Max(
  • FA2 Max(F9, F10, F11, F12, F13, F14, F15, F16, F17, F18, F19, F20, F21, F22, F23, F24);
  • R0, G0, and B0 respectively represent original grayscale values of the first primary color component, the second primary color component, and the third primary color component in the image pixel 100 to be detected
  • R9 to R24 respectively represent 16 located in the second layer.
  • the original grayscale values of the first primary color component of the image pixel 300, G9 to G24 represent the original grayscale values of the second primary color components of the 16 image pixels 300 of the second layer, respectively
  • B9 to B24 represent 16 in the second
  • the original grayscale value of the third primary color component of the image pixel 300 of the layer, F9 to F24 respectively represent the difference between the original grayscale value of the image pixel 300 located in the second layer and the image pixel 100 to be detected, FA2 Is the second grayscale difference.
  • Step S4 calculating a target grayscale difference according to the target grayscale difference algorithm, the first grayscale difference value, and the second grayscale difference value;
  • the step value, a is a preset first weight value, and b is a preset second weight value.
  • Step S5 Comparing the target grayscale difference with the preset grayscale threshold. If the target grayscale difference is greater than the grayscale threshold, determining that the image pixel 100 to be detected is a high frequency image pixel, otherwise determining the The image pixels 100 to be detected are low frequency image pixels.
  • each of the primary color components in each image pixel controls display of one sub-pixel in the display panel, that is, one image pixel includes three sub-pixels. Each sub-pixel corresponds to a primary color component.
  • each of the primary color components in each image pixel controls display of two sub-pixels in the display panel, that is, one image pixel includes six sub-pixels, and each of the two pixels The sub-pixels correspond to a primary color component.
  • the method for detecting high-frequency components in the image according to the present invention further includes:
  • Step S6 Adjust an actual grayscale value of the high frequency image pixel according to a preset adjustment algorithm and a target grayscale difference, and reduce a difference between an actual grayscale value of the high frequency image pixel and an original grayscale value. ;
  • the actual grayscale value is a grayscale value obtained by color shift compensation after the original grayscale value of the high frequency image pixel.
  • the color shift compensation process is: first acquiring original gray scale values of respective primary color components in the high frequency image pixels, and converting the original gray scales into first display gray scale values and second according to the color cast compensation algorithm. Displaying a grayscale value, wherein the first display grayscale value and the second display grayscale value of each primary color component respectively control display brightness of the two subpixels corresponding to the primary color component, so that the two subpixels realize bright and dark display to achieve color shift compensation the goal of.
  • the present invention further provides an apparatus for detecting high frequency components in an image, comprising: an obtaining unit 10, a first calculating unit 20 connected to the acquiring unit 10, and a first computing unit 20 connected thereto.
  • the second calculation unit 30 and the determination unit 40 connected to the second calculation unit 30.
  • the acquiring unit 10 is configured to obtain an original grayscale value of an image pixel in a to-be-processed image, where the image pixel includes: an image pixel 100 to be detected, an image pixel 200 located in the first layer, and an image pixel located in the second layer. 300.
  • the image pixel 200 located in the first layer surrounds the image pixel 100 to be detected, and the image pixel 300 located in the second layer surrounds the image pixel 200 located in the first layer.
  • each image to be processed is composed of a plurality of image pixels, each of the image pixels includes a first primary color component, a second primary color component, and a third primary color component, and the original grayscale value of the image pixel includes the first primary color component.
  • an original gray scale value of the second primary color component and the third primary color component by providing a gray scale value required for each primary color component of each image pixel to control the brightness of the primary color component, thereby making the primary color component The corresponding color is displayed, thereby realizing the display of the image.
  • the first primary color component, the second primary color component, and the third primary color component are a red component, a green component, and a blue component, respectively.
  • each image pixel may further comprise a fourth primary color component, which may be a white component.
  • the image pixel 100 to be detected when the image pixel 100 to be detected is located at an edge or a corner of the image, the image pixel 100 to be detected, the image pixel 200 located in the first layer, and the image pixel 300 located in the second layer
  • the image pixels 100 to be detected, the image pixels 200 located in the first layer, and the image pixels 100 to be detected are located in the fifth row and the fifth column, for example, when the image pixel 100 to be detected is located at the left edge of the image to be processed.
  • the image pixels 300 located in the second layer can be arranged in only 5 rows and 3 columns, wherein the image pixels 100 to be detected are located in the third row and the first column, and the image pixels 200 located in the first layer are located in the second row and the first column.
  • the second row, the second column, the third row, the second column, the fourth row, the first column, the fourth row, the second column, a total of five, and the remaining nine image pixels are the second layer image pixels 300, and when the The detected image pixel 100 is located at the right edge, the upper edge or the lower edge when it is located at the left edge of the image to be processed, and will not be described herein.
  • the image pixel 100 to be detected is located at the lower left corner of the image to be processed, the image pixel 100 to be detected, the image pixel 200 located in the first layer, and the image pixel 300 located in the second layer can only be arranged in 3 rows.
  • the image pixel 100 to be detected is located in the first row and the first column
  • the image pixel 200 located in the first layer is located in the second row, the first column, the second row, the second column, and the first row and the second column.
  • the remaining 6 image pixels are the image pixels 300 of the second layer.
  • the first calculating unit 20 is configured to calculate a first grayscale difference value and a second grayscale difference value, where the first grayscale difference value is an original grayscale value of the image pixel 100 to be detected and located at the first a maximum value of a difference of original grayscale values of each image pixel 200 of one layer; the second grayscale difference value is an original grayscale value of the image pixel 100 to be detected and each image pixel located in the second layer The maximum value of the difference between the original grayscale values of 300.
  • the difference between the original grayscale value of the image pixel 100 to be detected and the original grayscale value of the image pixel 200 in the first layer is: the original grayscale of the first primary color component in the image pixel 100 to be detected. a difference between a value and an original grayscale value of the first primary color component in the image pixel 200 of the first layer, an original grayscale value of a second primary color component in the image pixel 100 to be detected, and the first grayscale value
  • the difference between the original grayscale values of the second primary color component in the image pixel 200 and the original grayscale value of the third primary color component in the image pixel to be detected and the third primary color component in the image pixel 200 of the first layer The largest of the differences between the original grayscale values.
  • the image computing unit 100 to be detected, the image pixel 200 located in the first layer, and the image pixel 300 located in the second layer are arranged in 5 rows and 5 columns, and the calculation of the first computing unit 20 is taken as an example.
  • the process includes:
  • F1 Max(
  • F3 Max(
  • F4 Max(
  • F5 Max(
  • F7 Max(
  • R0, G0, and B0 respectively represent original grayscale values of the first primary color component, the second primary color component, and the third primary color component in the image pixel 100 to be detected
  • R1 to R8 respectively represent 8 located in the first layer
  • the original grayscale value of the first primary color component of the image pixel 200, G1 to G8 respectively represent the original grayscale values of the second primary color components of the image pixels 200 located in the first layer
  • B1 to B8 respectively represent 8 in the first
  • the original grayscale value of the third primary color component of the image pixel 200 of the layer, F1 to F8 respectively represent the difference between the original grayscale value of the image pixel 200 located in the first layer and the image pixel 100 to be detected, FA1 Is the first grayscale difference.
  • the image computing unit 100 to be detected, the image pixel 200 located in the first layer, and the image pixel 300 located in the second layer are arranged in 5 rows and 5 columns, and the calculation of the first computing unit 20 is taken as an example.
  • the process also includes:
  • F9 Max(
  • F17 Max(
  • F21 Max(
  • FA2 Max(F9, F10, F11, F12, F13, F14, F15, F16, F17, F18, F19, F20, F21, F22, F23, F24)
  • R0, G0, and B0 respectively represent original grayscale values of the first primary color component, the second primary color component, and the third primary color component in the image pixel 100 to be detected
  • R9 to R24 respectively represent 16 located in the second layer.
  • the original grayscale values of the first primary color component of the image pixel 300, G9 to G24 represent the original grayscale values of the second primary color components of the 16 image pixels 300 of the second layer, respectively
  • B9 to B24 represent 16 in the second
  • the original grayscale value of the third primary color component of the image pixel 300 of the layer, F9 to F24 respectively represent the difference between the original grayscale value of the image pixel 300 located in the second layer and the image pixel 100 to be detected, FA2 Is the second grayscale difference.
  • the determining unit 40 is configured to compare the target grayscale difference with the preset grayscale threshold. If the target grayscale difference is greater than the grayscale threshold, determine that the image pixel 100 to be detected is a high frequency image pixel. Otherwise, it is determined that the image pixel to be detected is a low frequency image pixel.
  • the adjusting unit 50 is configured to adjust an actual grayscale value of the high frequency image pixel according to a preset adjustment algorithm and a target grayscale difference, and reduce an actual grayscale value and an original grayscale value of the high frequency image pixel.
  • the difference between the actual grayscale values and the original grayscale values of the high frequency image pixels is obtained by color shift compensation to obtain grayscale values.
  • the color shift compensation process is: first acquiring original gray scale values of respective primary color components in the high frequency image pixels, and converting the original gray scales into first display gray scale values and second according to the color cast compensation algorithm. Displaying a grayscale value, wherein the first display grayscale value and the second display grayscale value of each primary color component respectively control display brightness of the two subpixels corresponding to the primary color component, so that the two subpixels realize bright and dark display to achieve color shift compensation the goal of.

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Abstract

本发明提供了一种侦测图像中高频成分的方法及装置。该方法利用待检测的图像像素的原始灰阶值与位于第一层的各个图像像素的原始灰阶值的差值的最大值作为第一灰阶差值，利用待检测的图像像素的原始灰阶值与位于第二层的各个图像像素的原始灰阶值的差值的最大值作为第二灰阶差值，再根据目标灰阶差值算法、第一灰阶差值及第二灰阶差值计算得出目标灰阶差值，再将目标灰阶差值与预设的灰阶阈值进行比较判断所述待检测的图像像素是否为高频图像像素，最后对高频图像像素实际灰阶值进行调整，减小高频图像像素的实际灰阶值与原始灰阶值的之间的差值，能够优化图像中高频成分的侦测过程，改善因采用色偏补偿算法造成显示不良，提升显示品质。

Description

侦测图像中高频成分的方法及装置 技术领域
本发明涉及显示技术领域，尤其涉及一种侦测图像中高频成分的方法及装置。
背景技术
液晶显示器(Liquid Crystal Display，LCD)具有机身薄、省电、无辐射等众多优点，得到了广泛的应用。如：液晶电视、移动电话、个人数字助理(PDA)、数字相机、计算机屏幕或笔记本电脑屏幕等，在平板显示领域中占主导地位。
现有市场上的液晶显示器大部分为背光型液晶显示器，其包括液晶显示面板及背光模组(backlight module)。液晶显示面板的工作原理是在薄膜晶体管阵列基板(Thin Film Transistor Array Substrate，TFT Array Substrate)与彩色滤光片(Color Filter，CF)基板之间灌入液晶分子，并在两片基板上施加驱动电压来控制液晶分子的旋转方向，以将背光模组的光线折射出来产生画面。
由于液晶分子有光学的各向异性特性，因此液晶面板存在有大视角下的色偏问题。为了解决液晶面板大视角下的色偏现象，现有技术提出了一种通过对输入的数据信号进行预处理实现的色偏补偿算法，该色偏补偿算法的具体实施步骤包括：待显示图像的各图像像素的各基色分量的原始灰阶值分别产生第一显示灰阶值和第二显示灰阶值，利用第一显示灰阶值和第二显示灰阶值分别控制液晶面板上相同颜色的两个子像素的显示亮度，其中第一显示灰阶值大于第二显示灰阶值，从而使得施加至两个子像素的驱动电压不相同，使得两个子像素的液晶分子偏转成不同的角度，从而在不同的角度观看画面都可获得较好的观看效果，达到降低色偏的目的。其中，一幅图像通常由多个图像像素构成，每个图像像素包括红、绿、蓝三种基色分量，在驱动一幅图像显示时，通过对每个图像像素的每个基色分量提供一个显示所需的灰阶值，以控制该基色分量的亮度，进而使得该基色分量显示相应的颜色，由此实现图像的显示。在一个图像像素中，每一个基色分量控制两个相同颜色且相邻的子像素，也即红色分量对应控制两个相邻的红色子像素，绿色分量对应控制两个相邻的绿色子像素，蓝色分量对应控制两个相邻的蓝色子像素，从而由红色分量的原始灰阶值产生的 第一显示灰阶和第二显示灰阶分别控制其对应的两个红色子像素的显示亮度，由绿色分量的原始灰阶值产生的第一显示灰阶和第二显示灰阶分别控制其对应的两个绿色子像素的显示亮度，由蓝色分量的原始灰阶值产生的第一显示灰阶和第二显示灰阶分别控制其对应的两个蓝色子像素的显示亮度。每个图像像素的显示亮度为其对应的基色分量的显示亮度的混合，每个基色分量的显示亮度为其对应的两个子像素的显示亮度的混合，一般地，为了由第一显示灰阶和第二显示灰阶控制的两个子像素的显示亮度的混合后还能保持与由原始灰阶值控制的两个子像素的显示亮度一致，通常会设置第一显示灰阶值对应的显示亮度和第二显示灰阶值对应的显示亮度之和等于原始灰阶值对应的显示亮度的二倍。
此外，在图像处理中，图像中亮度或灰度变化激烈的地方称为高频成分，反之则为低频成分，现有技术中对于图像中的高频成分的侦测局限于被侦测的图像像素及与其相邻的图像像素，侦测范围较小，这种情况下，高频成分经过上述色偏补偿算法处理后会出现颗粒感，导致显示品质降低。
发明内容
本发明的目的在于提供一种侦测图像中高频成分的方法，能够优化图像中高频成分的侦测过程，改善因采用色偏补偿算法造成显示不良，提升显示品质。
本发明的目的还在于提供一种侦测图像中高频成分的装置，能够优化图像中高频成分的侦测过程，改善因采用色偏补偿算法造成显示不良，提升显示品质。
为实现上述目的，本发明提供了一种侦测图像中高频成分的方法，包括如下步骤：
步骤S1、获取待处理图像中图像像素的原始灰阶值，所述图像像素包括：待检测的图像像素、位于第一层的图像像素及位于第二层的图像像素；
所述位于第一层的图像像素包围所述待检测的图像像素，所述位于第二层的图像像素包围位于第一层的图像像素；
步骤S2、计算第一灰阶差值，所述第一灰阶差值为所述待检测的图像像素的原始灰阶值与位于第一层的各个图像像素的原始灰阶值的差值的最大值；
步骤S3、计算第二灰阶差值，所述第二灰阶差值为所述待检测的图像像素的原始灰阶值与位于第二层的各个图像像素的原始灰阶值的差值的最大值；
步骤S4、根据目标灰阶差值算法、第一灰阶差值及第二灰阶差值计算得出目标灰阶差值；
步骤S5、将目标灰阶差值与预设的灰阶阈值进行比较，若目标灰阶差值大于灰阶阈值，则判定所述待检测的图像像素为高频图像像素，否则判定所述待检测的图像像素为低频图像像素。
在所述待检测的图像像素为高频图像像素时，所述方法还包括：
步骤S6、根据预设的调整算法及目标灰阶差值调整所述高频图像像素的实际灰阶值，减小高频图像像素的实际灰阶值与原始灰阶值的之间的绝对差值；
所述实际灰阶值为所述高频图像像素的原始灰阶值经过色偏补偿后得到灰阶值。
所述步骤S4中目标灰阶差值算法为：F＝a×FA1+b×FA2，其中，F为目标灰阶差值，FA1为第一灰阶差值，FA2为第二灰阶差值，a为预设的第一权重值，b为预设的第二权重值。
所述步骤S1中每一个图像像素均包括第一基色分量、第二基色分量及第三基色分量；
每一个图像像素的原始灰阶值均包括：第一基色分量的原始灰阶值、第二基色分量的原始灰阶值及第三基色分量的原始灰阶值；
所述待检测的图像像素的原始灰阶值与一位于第一层的图像像素的原始灰阶值的差值为：待检测的图像像素中第一基色分量的原始灰阶值与该位于第一层的图像像素中第一基色分量的原始灰阶值之间差值、待检测的图像像素中第二基色分量的原始灰阶值与该位于第一层的图像像素中第二基色分量的原始灰阶值之间差值以及待检测的图像像素中第三基色分量的原始灰阶值与该位于第一层的图像像素中第三基色分量的原始灰阶值之间的差值中最大的一个；
所述待检测的图像像素的原始灰阶值与一位于第二层的图像像素的原始灰阶值的差值为：待检测的图像像素中第一基色分量的原始灰阶值与该位于第二层的图像像素中第一基色分量的原始灰阶值之间差值、待检测的图像像素中第二基色分量的原始灰阶值与该位于第二层的图像像素中第二基色分量的原始灰阶值之间差值以及待检测的图像像素中第三基色分量的原始灰阶值与该位于第二层的图像像素中第三基色分量的原始灰阶值之间的差值中最大的一个。
所述步骤S6中预设的调整算法为：L’＝(L-L0)×C+L0，其中L’为经过调整算法调整后实际灰阶值，L0为高频图像像素的原始灰阶值，L 为在所述调整算法调整前的高频图像像素的实际灰阶值，C为预设的调整系数，所述调整系数的取值范围为0～1，所述调整系数随着目标灰阶差值的增大而减小。
本发明还提供一种侦测图像中高频成分的装置，包括：获取单元、与所述获取单元相连的第一计算单元、与所述第一计算单元相连的第二计算单元以及与所述第二计算单元相连的判断单元；
所述获取单元，用于获取待处理画面中图像像素的原始灰阶值，所述图像像素包括：待检测的图像像素、位于第一层的图像像素及位于第二层的图像像素；所述位于第一层的图像像素包围所述待检测的图像像素，所述位于第二层的图像像素包围位于第一层的图像像素；
所述第一计算单元，用于计算第一灰阶差值及第二灰阶差值，所述第一灰阶差值为所述待检测的图像像素的原始灰阶值与位于第一层的各个图像像素的原始灰阶值的差值的最大值；所述第二灰阶差值为所述待检测的图像像素的原始灰阶值与位于第二层的各个图像像素的原始灰阶值的差值的最大值；
所述第二计算单元，用于根据目标灰阶差值算法、第一灰阶差值及第二灰阶差值计算得出目标灰阶差值；
所述判断单元，用于将目标灰阶差值与预设的灰阶阈值进行比较，若目标灰阶差值大于灰阶阈值，则判定所述待检测的图像像素为高频图像像素，否则判定所述待检测的图像像素为低频图像像素。
所述侦测图像中高频成分的装置还包括：与所述判断单元相连的调整单元；
所述调整单元，用于根据预设的调整算法及目标灰阶差值调整所述高频图像像素的实际灰阶值，减小高频图像像素的实际灰阶值与原始灰阶值的之间的差值；所述实际灰阶值为所述高频图像像素的原始灰阶值经过色偏补偿后得到灰阶值。
所述目标灰阶差值算法为：F＝a×FA1+b×FA2，其中，F为目标灰阶差值，FA1为第一灰阶差值，FA2为第二灰阶差值，a为预设的第一权重值，b为预设的第二权重值。
每一个图像像素均包括依次排列的第一基色分量、第二基色分量及第三基色分量；
每一个图像像素的原始灰阶值均包括：第一基色分量的原始灰阶值、第二基色分量的原始灰阶值及第三基色分量的原始灰阶值；
所述待检测的图像像素的原始灰阶值与一位于第一层的图像像素的原 始灰阶值的差值为：待检测的图像像素中第一基色分量的原始灰阶值与该位于第一层的图像像素中第一基色分量的原始灰阶值之间差值、待检测的图像像素中第二基色分量的原始灰阶值与该位于第一层的图像像素中第二基色分量的原始灰阶值之间差值以及待检测的图像像素中第三基色分量的原始灰阶值与该位于第一层的图像像素中第三基色分量的原始灰阶值之间的差值中最大的一个；
所述待检测的图像像素的原始灰阶值与一位于第二层的图像像素的原始灰阶值的差值为：待检测的图像像素中第一基色分量的原始灰阶值与该位于第二层的图像像素中第一基色分量的原始灰阶值之间差值、待检测的图像像素中第二基色分量的原始灰阶值与该位于第二层的图像像素中第二基色分量的原始灰阶值之间差值以及待检测的图像像素中第三基色分量的原始灰阶值与该位于第二层的图像像素中第三基色分量的原始灰阶值之间的差值中最大的一个。
所述预设的调整算法为：L’＝(L-L0)×C+L0，其中L’为经过调整算法调整后的高频图像像素的实际灰阶值，L0为高频图像像素的原始灰阶值，L为在所述调整算法调整前的高频图像像素的实际灰阶值，C为预设的调整系数，所述调整系数的取值范围为0～1，所述调整系数随着目标灰阶差值的增大而减小。
本发明还提供一种侦测图像中高频成分的方法，包括如下步骤：
步骤S1、获取待处理图像中图像像素的原始灰阶值，所述图像像素包括：待检测的图像像素、位于第一层的图像像素及位于第二层的图像像素；
所述位于第一层的图像像素包围所述待检测的图像像素，所述位于第二层的图像像素包围位于第一层的图像像素；
步骤S2、计算第一灰阶差值，所述第一灰阶差值为所述待检测的图像像素的原始灰阶值与位于第一层的各个图像像素的原始灰阶值的差值的最大值；
步骤S3、计算第二灰阶差值，所述第二灰阶差值为所述待检测的图像像素的原始灰阶值与位于第二层的各个图像像素的原始灰阶值的差值的最大值；
步骤S4、根据目标灰阶差值算法、第一灰阶差值及第二灰阶差值计算得出目标灰阶差值；
步骤S5、将目标灰阶差值与预设的灰阶阈值进行比较，若目标灰阶差值大于灰阶阈值，则判定所述待检测的图像像素为高频图像像素，否则判定所述待检测的图像像素为低频图像像素；
其中，在所述待检测的图像像素为高频图像像素时，所述方法还包括：
步骤S6、根据预设的调整算法及目标灰阶差值调整所述高频图像像素的实际灰阶值，减小高频图像像素的实际灰阶值与原始灰阶值的之间的绝对差值；
所述实际灰阶值为所述高频图像像素的原始灰阶值经过色偏补偿后得到灰阶值；
其中，所述步骤S4中目标灰阶差值算法为：F＝a×FA1+b×FA2，其中，F为目标灰阶差值，FA1为第一灰阶差值，FA2为第二灰阶差值，a为预设的第一权重值，b为预设的第二权重值；
其中，所述步骤S1中每一个图像像素均包括第一基色分量、第二基色分量及第三基色分量；
每一个图像像素的原始灰阶值均包括：第一基色分量的原始灰阶值、第二基色分量的原始灰阶值及第三基色分量的原始灰阶值；
所述待检测的图像像素的原始灰阶值与一位于第一层的图像像素的原始灰阶值的差值为：待检测的图像像素中第一基色分量的原始灰阶值与该位于第一层的图像像素中第一基色分量的原始灰阶值之间差值、待检测的图像像素中第二基色分量的原始灰阶值与该位于第一层的图像像素中第二基色分量的原始灰阶值之间差值以及待检测的图像像素中第三基色分量的原始灰阶值与该位于第一层的图像像素中第三基色分量的原始灰阶值之间的差值中最大的一个；
所述待检测的图像像素的原始灰阶值与一位于第二层的图像像素的原始灰阶值的差值为：待检测的图像像素中第一基色分量的原始灰阶值与该位于第二层的图像像素中第一基色分量的原始灰阶值之间差值、待检测的图像像素中第二基色分量的原始灰阶值与该位于第二层的图像像素中第二基色分量的原始灰阶值之间差值以及待检测的图像像素中第三基色分量的原始灰阶值与该位于第二层的图像像素中第三基色分量的原始灰阶值之间的差值中最大的一个；
其中，所述步骤S6中预设的调整算法为：L’＝(L-L0)×C+L0，其中L’为经过调整算法调整后实际灰阶值，L0为高频图像像素的原始灰阶值，L为在所述调整算法调整前的高频图像像素的实际灰阶值，C为预设的调整系数，所述调整系数的取值范围为0～1，所述调整系数随着目标灰阶差值的增大而减小。
本发明的有益效果：本发明提供了一种侦测图像中高频成分的方法，利用待检测的图像像素的原始灰阶值与位于第一层的各个图像像素的原始 灰阶值的差值的最大值作为第一灰阶差值，利用待检测的图像像素的原始灰阶值与位于第二层的各个图像像素的原始灰阶值的差值的最大值作为第二灰阶差值，再根据目标灰阶差值算法、第一灰阶差值及第二灰阶差值计算得出目标灰阶差值，再将目标灰阶差值与预设的灰阶阈值进行比较判断所述待检测的图像像素是否为高频图像像素，最后对高频图像像素的实际灰阶值进行调整，减小高频图像像素的实际灰阶值与原始灰阶值的之间的差值，能够优化图像中高频成分的侦测过程，改善因采用色偏补偿算法造成显示不良，提升显示品质。本发明还提供一种侦测图像中高频成分的装置，能够优化图像中高频成分的侦测过程，改善因采用色偏补偿算法造成显示不良，提升显示品质。
附图说明
为了能更进一步了解本发明的特征以及技术内容，请参阅以下有关本发明的详细说明与附图，然而附图仅提供参考与说明用，并非用来对本发明加以限制。
附图中，
图1为本发明的侦测图像中高频成分的方法的步骤S1至步骤S3的示意图；
图2为本发明的侦测图像中高频成分的方法的流程图；
图3为本发明的侦测图像中高频成分的装置的示意图。
具体实施方式
为更进一步阐述本发明所采取的技术手段及其效果，以下结合本发明的优选实施例及其附图进行详细描述。
请参阅图2，并结合图1，本发明提供一种侦测图像中高频成分的方法，包括如下步骤：
步骤S1、获取待处理图像中图像像素的原始灰阶值，所述图像像素包括：待检测的图像像素100、位于第一层的图像像素200及位于第二层的图像像素300；
所述位于第一层的图像像素200包围所述待检测的图像像素100，所述位于第二层的图像像素300包围位于第一层的图像像素200。
具体地，每一个待处理图像由多个图像像素组成，每一个图像像素均包括第一基色分量、第二基色分量及第三基色分量，所述图像像素的原始灰阶值包括：第一基色分量、第二基色分量及第三基色分量的原始灰阶值， 通过对每个图像像素的每个基色分量提供一个显示所需的灰阶值，以控制该基色分量的亮度，进而使得该基色分量显示相应的颜色，由此实现图像的显示。优选地，所述第一基色分量、第二基色分量及第三基色分量分别为红色分量、绿色分量及蓝色分量。
可以理解的是，在本发明的其他实施例中，每一个图像像素还可以包括第四基色分量，所述第四基色分量呈现白色。
进一步地，如图1所示，一般情况下，所述待检测的图像像素100、位于第一层的图像像素200及位于第二层的图像像素300排列成5行5列，其中，待检测的图像像素100位于中央即第3行第3列，位于第一层的图像像素200包围所述待检测的图像像素100，分别位于第2行第2列、第2行第3列、第2行第4列、第3行第2列、第3行第4列、第4行第2列、第4行第3列及第4行第4列共8个，剩余的16个图像像素即为位于第二层的图像像素300，显然，该些位于第二层的图像像素300是包围位于第一层的图像像素200的。
可以理解的是，当所述待检测的图像像素100位于所述图像的边缘或角落时，所述待检测的图像像素100、位于第一层的图像像素200及位于第二层的图像像素300的将不足以排列成5行5列，例如当所述待检测的图像像素100位于所述待处理图像的左边缘时，所述待检测的图像像素100、位于第一层的图像像素200及位于第二层的图像像素300仅能排列成5行3列，其中，待检测的图像像素100的位于第3行第1列，位于第一层的图像像素200位于第2行第1列、第2行第2列、第3行第2列，第4行第1列、第4行第2列共5个，剩余的9个图像像素为第二层图像像素300，而当所述待检测的图像像素100位于右边缘、上边缘或下边缘时与其位于所述待处理图像的左侧边缘时类似，此处不再赘述。当所述待检测的图像像素100位于所述待处理图像的左下角时，待检测的图像像素100、位于第一层的图像像素200及位于第二层的图像像素300仅能排列成3行3列，其中，待检测的图像像素100位于第1行第1列，位于第一层的图像像素200位于第2行第1列、第2行第2列及第1行第2列共3个，剩余的6个图像像素为第二层的图像像素300。而当所述待检测的图像像素100位于左上角、右上角和右下角时与其位于所述待处理图像的左下角时类似，此处不再赘述。
步骤S2、计算第一灰阶差值，所述第一灰阶差值为所述待检测的图像像素100的原始灰阶值与位于第一层的各个图像像素200的原始灰阶值的差值的最大值。
其中，所述待检测的图像像素100的原始灰阶值与一位于第一层的图像像素200的原始灰阶值的差值为：待检测的图像像素100中第一基色分量的原始灰阶值与该位于第一层的图像像素200中第一基色分量的原始灰阶值之间差值、待检测的图像像素100中第二基色分量的原始灰阶值与该位于第一层的图像像素200中第二基色分量的原始灰阶值之间差值以及待检测的图像像素中第三基色分量的原始灰阶值与该位于第一层的图像像素200中第三基色分量的原始灰阶值之间的差值中最大的一个。应当理解的是，上述各个差值均为绝对差值，不存在负值。
举例来说，以所述待检测的图像像素100、位于第一层的图像像素200及位于第二层的图像像素300的排列成5行5列为例，所述步骤S2中的计算过程如下：
F1＝Max(|R1-R0|,|B1-B0|,|G1-G0|)；
F2＝Max(|R2-R0|,|B2-B0|,|G2-G0|)；
F3＝Max(|R3-R0|,|B3-B0|,|G3-G0|)；
F4＝Max(|R4-R0|,|B4-B0|,|G4-G0|)；
F5＝Max(|R5-R0|,|B5-B0|,|G5-G0|)；
F6＝Max(|R6-R0|,|B6-B0|,|G6-G0|)；
F7＝Max(|R7-R0|,|B7-B0|,|G7-G0|)；
F8＝Max(|R8-R0|,|B8-B0|,|G8-G0|)；
FA1＝Max(F1,F2,F3,F4,F5,F6,F7,F8)；
其中，R0、G0、B0分别代表所述待检测的图像像素100中第一基色分量、第二基色分量及第三基色分量的原始灰阶值，R1至R8分别代表8个位于第一层的图像像素200的第一基色分量的原始灰阶值，G1至G8分别代表8个位于第一层的图像像素200的第二基色分量的原始灰阶值，B1至B8分别代表8个位于第一层的图像像素200的第三基色分量的原始灰阶值，F1至F8分别代表8个位于第一层的图像像素200与所述待检测的图像像素100的原始灰阶值的差值，FA1为第一灰阶差值。
步骤S3、计算第二灰阶差值，所述第二灰阶差值为所述待检测的图像像素100的灰阶值与位于第二层的各个图像像素300的灰阶值的差值的最大值；
其中，所述待检测的图像像素100的灰阶值与一位于第二层的图像像素300的原始灰阶值差值为：待检测的图像像素100中第一基色分量的原始灰阶值与该位于第二层的图像像素300中第一基色分量的原始灰阶值之间的差值、待检测的图像像素100中第二基色分量的原始灰阶值与该位于 第二层的图像像素300中第二基色分量的原始灰阶值之间的差值以及待检测的图像像素中第三基色分量的原始灰阶值与该位于第二层的图像像素300中第三基色分量的原始灰阶值之间的差值中最大的一个。
举例来说，以所述待检测的图像像素100、位于第一层的图像像素200及位于第二层的图像像素300的排列成5行5列为例，所述步骤S3中的计算过程如下：
F9＝Max(|R9-R0|,|B9-B0|,|G9-G0|)；
F10＝Max(|R10-R0|,|B10-B0|,|G10-G0|)；
F11＝Max(|R11-R0|,|B11-B0|,|G11-G0|)；
F12＝Max(|R12-R0|,|B12-B0|,|G12-G0|)；
F13＝Max(|R13-R0|,|B13-B0|,|G13-G0|)；
F14＝Max(|R14-R0|,|B14-B0|,|G14-G0|)；
F15＝Max(|R15-R0|,|B15-B0|,|G15-G0|)；
F16＝Max(|R16-R0|,|B16-B0|,|G16-G0|)；
F17＝Max(|R17-R0|,|B17-B0|,|G17-G0|)；
F18＝Max(|R18-R0|,|B18-B0|,|G18-G0|)；
F19＝Max(|R19-R0|,|B19-B0|,|G19-G0|)；
F20＝Max(|R20-R0|,|B20-B0|,|G20-G0|)；
F21＝Max(|R21-R0|,|B21-B0|,|G21-G0|)；
F22＝Max(|R22-R0|,|B22-B0|,|G22-G0|)；
F23＝Max(|R23-R0|,|B23-B0|,|G23-G0|)；
F24＝Max(|R24-R0|,|B24-B0|,|G24-G0|)；
FA2＝Max(F9,F10,F11,F12,F13,F14,F15,F16,F17,F18,F19,F20,F21,F22,F23,F24)；
其中，R0、G0、B0分别代表所述待检测的图像像素100中第一基色分量、第二基色分量及第三基色分量的原始灰阶值，R9至R24分别代表16个位于第二层的图像像素300的第一基色分量的原始灰阶值，G9至G24分别代表16个位于第二层的图像像素300的第二基色分量的原始灰阶值，B9至B24分别代表16个位于第二层的图像像素300的第三基色分量的原始灰阶值，F9至F24分别代表16个位于第二层的图像像素300与所述待检测的图像像素100的原始灰阶值的差值，FA2为第二灰阶差值。
步骤S4、根据目标灰阶差值算法、第一灰阶差值及第二灰阶差值计算得出目标灰阶差值；
具体地，所述步骤S4中目标灰阶差值算法为：F＝a×FA1+b×FA2，其 中，F为目标灰阶差值，FA1为第一灰阶差值，FA2为第二灰阶差值，a为预设的第一权重值，b为预设的第二权重值，通过调节a和b的具体大小，能够改变目标灰阶差值。
步骤S5、将目标灰阶差值与预设的灰阶阈值进行比较，若目标灰阶差值大于灰阶阈值，则判定所述待检测的图像像素100为高频图像像素，否则判定所述待检测的图像像素100为低频图像像素。
具体地，在未采用色偏补偿算法进行色偏补偿的显示面板中，每一个图像像素中的每一个基色分量控制显示面板中的一个子像素实现显示，也即一个图像像素包括三个子像素，每一个子像素对应一种基色分量。
而在采用色偏补偿算法进行色偏补偿的显示面板中，每一个图像像素中的每一个基色分量控制显示面板中的两个个子像素实现显示，也即一个图像像素包括六个子像素，每两个子像素对应一种基色分量。
此时，在所述待检测的图像像素100为高频图像像素时，为了减少色偏补偿所带来的颗粒感，本发明所述侦测图像中高频成分的方法还包括：
步骤S6、根据预设的调整算法及目标灰阶差值调整所述高频图像像素的实际灰阶值，减小高频图像像素的实际灰阶值与原始灰阶值的之间的差值；
所述实际灰阶值为所述高频图像像素的原始灰阶值经过色偏补偿后得到灰阶值。
具体地，所述色偏补偿的过程为：先获取高频图像像素中各个基色分量的原始灰阶值，并将根据色偏补偿算法将原始灰阶转换为第一显示灰阶值和第二显示灰阶值，各个基色分量的第一显示灰阶值和第二显示灰阶值分别控制该基色分量对应的两个子像素的显示亮度，使得两个子像素实现亮暗显示，以达到色偏补偿的目的。所述第一显示灰阶值和第二显示灰阶值即为所述实际灰阶值，所述减小高频图像像素的实际灰阶值与原始灰阶值的之间的差值，即为减少高频图像像素中各个基色分量对应的两个子像素之间的亮暗差异，从而减少因色偏补偿所带来的颗粒感。
具体地，所述步骤S6中预设的调整算法为：L’＝(L-L0)×C+L0，其中L’为经过调整算法调整后的高频图像像素的实际灰阶值，L0为高频图像像素的原始灰阶值，L为在所述调整算法调整前的高频图像像素的实际灰阶值，C为预设的调整系数，所述调整系数的取值范围为0～1，所述调整系数随着目标灰阶差值的增大而减小，也就是说当所述目标灰阶差值越大时，所述高频图像像素经过色偏补偿处理后亮暗显示的幅度越小，从而能够减小因色偏补偿带来的显示不良。
请参阅图3，本发明还提供一种侦测图像中高频成分的装置，包括：获取单元10、与所述获取单元10相连的第一计算单元20、与所述第一计算单元20相连的第二计算单元30以及与所述第二计算单元30相连的判断单元40。
所述获取单元10，用于获取待处理画面中图像像素的原始灰阶值，所述图像像素包括：待检测的图像像素100、位于第一层的图像像素200及位于第二层的图像像素300；所述位于第一层的图像像素200包围所述待检测的图像像素100，所述位于第二层的图像像素300包围位于第一层的图像像素200。
具体地，每一个待处理图像由多个图像像素组成，每一个图像像素均包括第一基色分量、第二基色分量及第三基色分量，所述图像像素的原始灰阶值包括第一基色分量、第二基色分量及第三基色分量的原始灰阶值，通过对每个图像像素的每个基色分量提供一个显示所需的灰阶值，以控制该基色分量的亮度，进而使得该基色分量显示相应的颜色，由此实现图像的显示。优选地，所述第一基色分量、第二基色分量及第三基色分量分别为红色分量、绿色分量及蓝色分量。
可以理解的是，在本发明的其他实施例中，每一个图像像素还可以包括第四基色分量，所述第四基色分量可以为白色分量。
如图1所示，一般情况下，所述待检测的图像像素100、位于第一层的图像像素200及位于第二层的图像像素300排列成5行5列，其中，待检测的图像像素100位于中央即第3行第3列，位于第一层的图像像素200包围所述待检测的图像像素100，分别位于第2行第2列、第2行第3列、第2行第4列、第3行第2列、第3行第4列、第4行第2列、第4行第3列及第4行第4列共8个，剩余的16个图像像素即为位于第二层的图像像素300，显然，该些位于第二层的图像像素300是包围位于第一层的图像像素200的。
可以理解的是，当所述待检测的图像像素100位于所述图像的边缘或角落时，所述待检测的图像像素100、位于第一层的图像像素200及位于第二层的图像像素300的将不足以排列成5行5列，例如当所述待检测的图像像素100位于所述待处理图像的左边缘时，所述待检测的图像像素100、位于第一层的图像像素200及位于第二层的图像像素300仅能排列成5行3列，其中，待检测的图像像素100的位于第3行第1列，位于第一层的图像像素200位于第2行第1列、第2行第2列、第3行第2列，第4行第1列、第4行第2列共5个，剩余的9个图像像素为第二层图像像素300，而 当所述待检测的图像像素100位于右边缘、上边缘或下边缘时与其位于所述待处理图像的左侧边缘时类似，此处不再赘述。当所述待检测的图像像素100位于所述待处理图像的左下角时，待检测的图像像素100、位于第一层的图像像素200及位于第二层的图像像素300仅能排列成3行3列，其中，待检测的图像像素100位于第1行第1列，位于第一层的图像像素200位于第2行第1列、第2行第2列及第1行第2列共3个，剩余的6个图像像素为第二层的图像像素300。而当所述待检测的图像像素100位于左上角、右上角和右下角时与其位于所述待处理图像的左下角时类似，此处不再赘述。
所述第一计算单元20，用于计算第一灰阶差值及第二灰阶差值，所述第一灰阶差值为所述待检测的图像像素100的原始灰阶值与位于第一层的各个图像像素200的原始灰阶值的差值的最大值；所述第二灰阶差值为所述待检测的图像像素100的原始灰阶值与位于第二层的各个图像像素300的原始灰阶值的差值的最大值。
其中，所述待检测的图像像素100的原始灰阶值与一位于第一层的图像像素200的原始灰阶值的差值为：待检测的图像像素100中第一基色分量的原始灰阶值与该位于第一层的图像像素200中第一基色分量的原始灰阶值之间的差值、待检测的图像像素100中第二基色分量的原始灰阶值与该位于第一层的图像像素200中第二基色分量的原始灰阶值之间的差值以及待检测的图像像素中第三基色分量的原始灰阶值与该位于第一层的图像像素200中第三基色分量的原始灰阶值之间的差值中最大的一个。
举例来说，以所述待检测的图像像素100、位于第一层的图像像素200及位于第二层的图像像素300的排列成5行5列为例，所述第一计算单元20的计算过程包括：
F1＝Max(|R1-R0|,|B1-B0|,|G1-G0|)
F2＝Max(|R2-R0|,|B2-B0|,|G2-G0|)
F3＝Max(|R3-R0|,|B3-B0|,|G3-G0|)
F4＝Max(|R4-R0|,|B4-B0|,|G4-G0|)
F5＝Max(|R5-R0|,|B5-B0|,|G5-G0|)
F6＝Max(|R6-R0|,|B6-B0|,|G6-G0|)
F7＝Max(|R7-R0|,|B7-B0|,|G7-G0|)
F8＝Max(|R8-R0|,|B8-B0|,|G8-G0|)
FA1＝Max(F1,F2,F3,F4,F5,F6,F7,F8)
其中，R0、G0、B0分别代表所述待检测的图像像素100中第一基色分 量、第二基色分量及第三基色分量的原始灰阶值，R1至R8分别代表8个位于第一层的图像像素200的第一基色分量的原始灰阶值，G1至G8分别代表8个位于第一层的图像像素200的第二基色分量的原始灰阶值，B1至B8分别代表8个位于第一层的图像像素200的第三基色分量的原始灰阶值，F1至F8分别代表8个位于第一层的图像像素200与所述待检测的图像像素100的原始灰阶值的差值，FA1为第一灰阶差值。
其中，所述待检测的图像像素100的原始灰阶值与一位于第二层的图像像素300的原始灰阶值的差值为：待检测的图像像素100中第一基色分量的原始灰阶值与该位于第二层的各个图像像素300中第一基色分量的原始灰阶值之间差值、待检测的图像像素100中第二基色分量的原始灰阶值与该位于第二层的各个图像像素300中第二基色分量的原始灰阶值之间的差值以及待检测的图像像素中第三基色分量100的原始灰阶值与该位于第二层的各个图像像素300中第三基色分量的原始灰阶值之间的差值中最大的一个。
举例来说，以所述待检测的图像像素100、位于第一层的图像像素200及位于第二层的图像像素300的排列成5行5列为例，所述第一计算单元20的计算过程还包括：
F9＝Max(|R9-R0|,|B9-B0|,|G9-G0|)
F10＝Max(|R10-R0|,|B10-B0|,|G10-G0|)
F11＝Max(|R11-R0|,|B11-B0|,|G11-G0|)
F12＝Max(|R12-R0|,|B12-B0|,|G12-G0|)
F13＝Max(|R13-R0|,|B13-B0|,|G13-G0|)
F14＝Max(|R14-R0|,|B14-B0|,|G14-G0|)
F15＝Max(|R15-R0|,|B15-B0|,|G15-G0|)
F16＝Max(|R16-R0|,|B16-B0|,|G16-G0|)
F17＝Max(|R17-R0|,|B17-B0|,|G17-G0|)
F18＝Max(|R18-R0|,|B18-B0|,|G18-G0|)
F19＝Max(|R19-R0|,|B19-B0|,|G19-G0|)
F20＝Max(|R20-R0|,|B20-B0|,|G20-G0|)
F21＝Max(|R21-R0|,|B21-B0|,|G21-G0|)
F22＝Max(|R22-R0|,|B22-B0|,|G22-G0|)
F23＝Max(|R23-R0|,|B23-B0|,|G23-G0|)
F24＝Max(|R24-R0|,|B24-B0|,|G24-G0|)
FA2＝Max(F9,F10,F11,F12,F13,F14,F15,F16,F17,F18, F19,F20,F21,F22,F23,F24)
其中，R0、G0、B0分别代表所述待检测的图像像素100中第一基色分量、第二基色分量及第三基色分量的原始灰阶值，R9至R24分别代表16个位于第二层的图像像素300的第一基色分量的原始灰阶值，G9至G24分别代表16个位于第二层的图像像素300的第二基色分量的原始灰阶值，B9至B24分别代表16个位于第二层的图像像素300的第三基色分量的原始灰阶值，F9至F24分别代表16个位于第二层的图像像素300与所述待检测的图像像素100的原始灰阶值的差值，FA2为第二灰阶差值。
所述第二计算单元30，用于根据目标灰阶差值算法、第一灰阶差值及第二灰阶差值计算得出目标灰阶差值。
具体地，所述目标灰阶差值算法为：F＝a×FA1+b×FA2，其中，F为目标灰阶差值，FA1为第一灰阶差值，FA2为第二灰阶差值，a为预设的第一权重值，b为预设的第二权重值，通过调节a和b的具体大小，能够改变目标灰阶差值。
所述判断单元40，用于将目标灰阶差值与预设的灰阶阈值进行比较，若目标灰阶差值大于灰阶阈值，则判定所述待检测的图像像素100为高频图像像素，否则判定所述待检测的图像像素为低频图像像素。
具体地，所述侦测图像中高频成分的装置还包括：与所述判断单元40相连的调整单元50；
所述调整单元50，用于根据预设的调整算法及目标灰阶差值调整所述高频图像像素的实际灰阶值，减小高频图像像素的实际灰阶值与原始灰阶值的之间的差值；所述实际灰阶值为所述高频图像像素的原始灰阶值经过色偏补偿后得到灰阶值。
具体地，所述色偏补偿的过程为：先获取高频图像像素中各个基色分量的原始灰阶值，并将根据色偏补偿算法将原始灰阶转换为第一显示灰阶值和第二显示灰阶值，各个基色分量的第一显示灰阶值和第二显示灰阶值分别控制该基色分量对应的两个子像素的显示亮度，使得两个子像素实现亮暗显示，以达到色偏补偿的目的。所述第一显示灰阶值和第二显示灰阶值即为所述实际灰阶值，所述减小高频图像像素的实际灰阶值与原始灰阶值的之间的差值，即为减少高频图像像素中各个基色分量对应的两个子像素之间的亮暗差异，从而减少因色偏补偿所带来的颗粒感。
具体地，所述步骤S6中预设的调整算法为：L’＝(L-L0)×C+L0，其中L’为经过调整算法调整后的高频图像像素的实际灰阶值，L0为高频图像像素的原始灰阶值，L为在所述调整算法调整前的高频图像像素的实际 灰阶值，C为预设的调整系数，所述调整系数的取值范围为0～1，所述调整系数随着目标灰阶差值的增大而减小，也就是说当所述目标灰阶差值越大时，所述高频图像像素经过色偏补偿处理后亮暗显示的幅度越小，从而能够减小因色偏补偿带来的显示不良。
综上所述，本发明提供了一种侦测图像中高频成分的方法，利用待检测的图像像素的原始灰阶值与位于第一层的各个图像像素的原始灰阶值的差值的最大值作为第一灰阶差值，利用待检测的图像像素的原始灰阶值与位于第二层的各个图像像素的原始灰阶值的差值的最大值作为第二灰阶差值，再根据目标灰阶差值算法、第一灰阶差值及第二灰阶差值计算得出目标灰阶差值，再将目标灰阶差值与预设的灰阶阈值进行比较判断所述待检测的图像像素是否为高频图像像素，最后对高频图像像素的实际灰阶值进行调整，减小高频图像像素的实际灰阶值与原始灰阶值的之间的差值，能够优化图像中高频成分的侦测过程，改善因采用色偏补偿算法造成显示不良，提升显示品质。本发明还提供一种侦测图像中高频成分的装置，能够优化图像中高频成分的侦测过程，改善因采用色偏补偿算法造成显示不良，提升显示品质。
以上所述，对于本领域的普通技术人员来说，可以根据本发明的技术方案和技术构思作出其他各种相应的改变和变形，而所有这些改变和变形都应属于本发明权利要求的保护范围。

Claims (11)

  1. 一种侦测图像中高频成分的方法，包括如下步骤：
    步骤S1、获取待处理图像中图像像素的原始灰阶值，所述图像像素包括：待检测的图像像素、位于第一层的图像像素及位于第二层的图像像素；
    所述位于第一层的图像像素包围所述待检测的图像像素，所述位于第二层的图像像素包围位于第一层的图像像素；
    步骤S2、计算第一灰阶差值，所述第一灰阶差值为所述待检测的图像像素的原始灰阶值与位于第一层的各个图像像素的原始灰阶值的差值的最大值；
    步骤S3、计算第二灰阶差值，所述第二灰阶差值为所述待检测的图像像素的原始灰阶值与位于第二层的各个图像像素的原始灰阶值的差值的最大值；
    步骤S4、根据目标灰阶差值算法、第一灰阶差值及第二灰阶差值计算得出目标灰阶差值；
    步骤S5、将目标灰阶差值与预设的灰阶阈值进行比较，若目标灰阶差值大于灰阶阈值，则判定所述待检测的图像像素为高频图像像素，否则判定所述待检测的图像像素为低频图像像素。
  2. 如权利要求1所述侦测图像中高频成分的方法，其中，在所述待检测的图像像素为高频图像像素时，所述方法还包括：
    步骤S6、根据预设的调整算法及目标灰阶差值调整所述高频图像像素的实际灰阶值，减小高频图像像素的实际灰阶值与原始灰阶值的之间的绝对差值；
    所述实际灰阶值为所述高频图像像素的原始灰阶值经过色偏补偿后得到灰阶值。
  3. 如权利要求1所述的侦测图像中高频成分的方法，其中，所述步骤S4中目标灰阶差值算法为：F＝a×FA1+b×FA2，其中，F为目标灰阶差值，FA1为第一灰阶差值，FA2为第二灰阶差值，a为预设的第一权重值，b为预设的第二权重值。
  4. 如权利要求1所述的侦测图像中高频成分的方法，其中，所述步骤S1中每一个图像像素均包括第一基色分量、第二基色分量及第三基色分量；
    每一个图像像素的原始灰阶值均包括：第一基色分量的原始灰阶值、第二基色分量的原始灰阶值及第三基色分量的原始灰阶值；
    所述待检测的图像像素的原始灰阶值与一位于第一层的图像像素的原始灰阶值的差值为：待检测的图像像素中第一基色分量的原始灰阶值与该位于第一层的图像像素中第一基色分量的原始灰阶值之间差值、待检测的图像像素中第二基色分量的原始灰阶值与该位于第一层的图像像素中第二基色分量的原始灰阶值之间差值以及待检测的图像像素中第三基色分量的原始灰阶值与该位于第一层的图像像素中第三基色分量的原始灰阶值之间的差值中最大的一个；
    所述待检测的图像像素的原始灰阶值与一位于第二层的图像像素的原始灰阶值的差值为：待检测的图像像素中第一基色分量的原始灰阶值与该位于第二层的图像像素中第一基色分量的原始灰阶值之间差值、待检测的图像像素中第二基色分量的原始灰阶值与该位于第二层的图像像素中第二基色分量的原始灰阶值之间差值以及待检测的图像像素中第三基色分量的原始灰阶值与该位于第二层的图像像素中第三基色分量的原始灰阶值之间的差值中最大的一个。
  5. 如权利要求2所述的侦测图像中高频成分的方法，其中，所述步骤S6中预设的调整算法为：L’＝(L-L0)×C+L0，其中L’为经过调整算法调整后实际灰阶值，L0为高频图像像素的原始灰阶值，L为在所述调整算法调整前的高频图像像素的实际灰阶值，C为预设的调整系数，所述调整系数的取值范围为0～1，所述调整系数随着目标灰阶差值的增大而减小。
  6. 一种侦测图像中高频成分的装置，包括：获取单元、与所述获取单元相连的第一计算单元、与所述第一计算单元相连的第二计算单元以及与所述第二计算单元相连的判断单元；
    所述获取单元，用于获取待处理画面中图像像素的原始灰阶值，所述图像像素包括：待检测的图像像素、位于第一层的图像像素及位于第二层的图像像素；所述位于第一层的图像像素包围所述待检测的图像像素，所述位于第二层的图像像素包围位于第一层的图像像素；
    所述第一计算单元，用于计算第一灰阶差值及第二灰阶差值，所述第一灰阶差值为所述待检测的图像像素的原始灰阶值与位于第一层的各个图像像素的原始灰阶值的差值的最大值；所述第二灰阶差值为所述待检测的图像像素的原始灰阶值与位于第二层的各个图像像素的原始灰阶值的差值的最大值；
    所述第二计算单元，用于根据目标灰阶差值算法、第一灰阶差值及第二灰阶差值计算得出目标灰阶差值；
    所述判断单元，用于将目标灰阶差值与预设的灰阶阈值进行比较，若 目标灰阶差值大于灰阶阈值，则判定所述待检测的图像像素为高频图像像素，否则判定所述待检测的图像像素为低频图像像素。
  7. 如权利要求6所述的侦测图像中高频成分的装置，还包括：与所述判断单元相连的调整单元；
    所述调整单元，用于根据预设的调整算法及目标灰阶差值调整所述高频图像像素的实际灰阶值，减小高频图像像素的实际灰阶值与原始灰阶值的之间的差值；所述实际灰阶值为所述高频图像像素的原始灰阶值经过色偏补偿后得到灰阶值。
  8. 如权利要求6所述的侦测图像中高频成分的装置，其中，所述目标灰阶差值算法为：F＝a×FA1+b×FA2，其中，F为目标灰阶差值，FA1为第一灰阶差值，FA2为第二灰阶差值，a为预设的第一权重值，b为预设的第二权重值。
  9. 如权利要求6所述的侦测图像中高频成分的装置，其中，每一个图像像素均包括依次排列的第一基色分量、第二基色分量及第三基色分量；
    所述待检测的图像像素的原始灰阶值与一位于第一层的图像像素的原始灰阶值的差值为：待检测的图像像素中第一基色分量的原始灰阶值与该位于第一层的图像像素中第一基色分量的原始灰阶值之间差值、待检测的图像像素中第二基色分量的原始灰阶值与该位于第一层的图像像素中第二基色分量的原始灰阶值之间差值以及待检测的图像像素中第三基色分量的原始灰阶值与该位于第一层的图像像素中第三基色分量的原始灰阶值之间的差值中最大的一个；
    所述待检测的图像像素的原始灰阶值与一位于第二层的图像像素的原始灰阶值的差值为：待检测的图像像素中第一基色分量的原始灰阶值与该位于第二层的图像像素中第一基色分量的原始灰阶值之间差值、待检测的图像像素中第二基色分量的原始灰阶值与该位于第二层的图像像素中第二基色分量的原始灰阶值之间差值以及待检测的图像像素中第三基色分量的原始灰阶值与该位于第二层的图像像素中第三基色分量的原始灰阶值之间的差值中最大的一个。
  10. 如权利要求6所述的侦测图像中高频成分的装置，其中，所述预设的调整算法为：L’＝(L-L0)×C+L0，其中L’为经过调整算法调整后的高频图像像素的实际灰阶值，L0为高频图像像素的原始灰阶值，L为在所述调整算法调整前的高频图像像素的实际灰阶值，C为预设的调整系数，所述调整系数的取值范围为0～1，所述调整系数随着目标灰阶差值的增大而减小。
  11. 一种侦测图像中高频成分的方法，包括如下步骤：
    步骤S1、获取待处理图像中图像像素的原始灰阶值，所述图像像素包括：待检测的图像像素、位于第一层的图像像素及位于第二层的图像像素；
    所述位于第一层的图像像素包围所述待检测的图像像素，所述位于第二层的图像像素包围位于第一层的图像像素；
    步骤S2、计算第一灰阶差值，所述第一灰阶差值为所述待检测的图像像素的原始灰阶值与位于第一层的各个图像像素的原始灰阶值的差值的最大值；
    步骤S3、计算第二灰阶差值，所述第二灰阶差值为所述待检测的图像像素的原始灰阶值与位于第二层的各个图像像素的原始灰阶值的差值的最大值；
    步骤S4、根据目标灰阶差值算法、第一灰阶差值及第二灰阶差值计算得出目标灰阶差值；
    步骤S5、将目标灰阶差值与预设的灰阶阈值进行比较，若目标灰阶差值大于灰阶阈值，则判定所述待检测的图像像素为高频图像像素，否则判定所述待检测的图像像素为低频图像像素；
    其中，在所述待检测的图像像素为高频图像像素时，所述方法还包括：
    步骤S6、根据预设的调整算法及目标灰阶差值调整所述高频图像像素的实际灰阶值，减小高频图像像素的实际灰阶值与原始灰阶值的之间的绝对差值；
    所述实际灰阶值为所述高频图像像素的原始灰阶值经过色偏补偿后得到灰阶值；
    其中，所述步骤S4中目标灰阶差值算法为：F＝a×FA1+b×FA2，其中，F为目标灰阶差值，FA1为第一灰阶差值，FA2为第二灰阶差值，a为预设的第一权重值，b为预设的第二权重值；
    其中，所述步骤S1中每一个图像像素均包括第一基色分量、第二基色分量及第三基色分量；
    每一个图像像素的原始灰阶值均包括：第一基色分量的原始灰阶值、第二基色分量的原始灰阶值及第三基色分量的原始灰阶值；
    所述待检测的图像像素的原始灰阶值与一位于第一层的图像像素的原始灰阶值的差值为：待检测的图像像素中第一基色分量的原始灰阶值与该位于第一层的图像像素中第一基色分量的原始灰阶值之间差值、待检测的图像像素中第二基色分量的原始灰阶值与该位于第一层的图像像素中第二基色分量的原始灰阶值之间差值以及待检测的图像像素中第三基色分量的 原始灰阶值与该位于第一层的图像像素中第三基色分量的原始灰阶值之间的差值中最大的一个；
    所述待检测的图像像素的原始灰阶值与一位于第二层的图像像素的原始灰阶值的差值为：待检测的图像像素中第一基色分量的原始灰阶值与该位于第二层的图像像素中第一基色分量的原始灰阶值之间差值、待检测的图像像素中第二基色分量的原始灰阶值与该位于第二层的图像像素中第二基色分量的原始灰阶值之间差值以及待检测的图像像素中第三基色分量的原始灰阶值与该位于第二层的图像像素中第三基色分量的原始灰阶值之间的差值中最大的一个；
    其中，所述步骤S6中预设的调整算法为：L’＝(L-L0)×C+L0，其中L’为经过调整算法调整后实际灰阶值，L0为高频图像像素的原始灰阶值，L为在所述调整算法调整前的高频图像像素的实际灰阶值，C为预设的调整系数，所述调整系数的取值范围为0～1，所述调整系数随着目标灰阶差值的增大而减小。
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