WO2016179946A1 - 一种判别图像亮度背景的方法、装置和显示装置 - Google Patents

一种判别图像亮度背景的方法、装置和显示装置 Download PDF

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WO2016179946A1
WO2016179946A1 PCT/CN2015/091064 CN2015091064W WO2016179946A1 WO 2016179946 A1 WO2016179946 A1 WO 2016179946A1 CN 2015091064 W CN2015091064 W CN 2015091064W WO 2016179946 A1 WO2016179946 A1 WO 2016179946A1
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Prior art keywords
pixels
image
discriminating
pixel
sub
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PCT/CN2015/091064
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English (en)
French (fr)
Inventor
刘鹏
董学
郭仁炜
陈忠君
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京东方科技集团股份有限公司
北京京东方光电科技有限公司
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Priority to EP15891648.6A priority Critical patent/EP3296957B1/en
Priority to US15/122,634 priority patent/US10062312B2/en
Publication of WO2016179946A1 publication Critical patent/WO2016179946A1/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
    • G09G3/20—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
    • 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
    • G09G3/2003—Display 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
    • 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
    • G09G3/2007—Display of intermediate tones
    • G09G3/2074—Display of intermediate tones using sub-pixels
    • 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
    • G09G2320/029—Improving the quality of display appearance by monitoring one or more pixels in the display panel, e.g. by monitoring a fixed reference pixel
    • G09G2320/0295—Improving the quality of display appearance by monitoring one or more pixels in the display panel, e.g. by monitoring a fixed reference pixel by monitoring each display pixel
    • 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 image display, and in particular to a method for discriminating an image brightness background, an apparatus for discriminating an image brightness background, and a display device thereof.
  • high-brightness backgrounds such as the white background of text pages
  • low-brightness backgrounds such as the night mode of text pages
  • the present invention provides a method for discriminating an image brightness background, an apparatus for discriminating an image brightness background, and a display device thereof, which are capable of solving or at least alleviating at least some of the defects existing in the prior art.
  • a method for discriminating an image brightness background may include the steps of: receiving image information to be discriminated, the image information including grayscale values of respective sub-pixels in each pixel;
  • the gray scale values of the specific sub-pixels in the s ⁇ mth row and the t ⁇ nth column centered on the pixel of the t-th column of the sth row constitute an array, and the array is arranged in order, where s,m , t, n is a natural number; if the grayscale values of the larger N specific sub-pixels in the array are greater than the grayscale value of the given value, and the variance is less than or equal to a certain threshold, then the s ⁇ m row and the tth are determined.
  • the specific sub-pixels in the ⁇ n column are high-brightness background regions, otherwise it is determined that the specific sub-pixels in the s ⁇ mth row and the t ⁇ nth column are non-high-brightness background
  • the grayscale value of different given values the number of larger N specific sub-pixels larger than the grayscale value of the given value, and the variance of different specific thresholds are used. Differentiating the severity of the brightness background can be made.
  • the entire image area is discriminated as a high-luminance area, a low-luminance area, and a transition area between the high-luminance area and the low-luminance area, respectively.
  • the regions of different luminance backgrounds are subjected to corresponding refinement processing.
  • the present invention is directed to a high resolution algorithm design based on high brightness background discrimination.
  • the present invention discriminates between two common backgrounds (high-brightness backgrounds and non-high-brightness backgrounds) to distinguish between high-brightness backgrounds and non-high-brightness backgrounds.
  • the present invention can change the high brightness by adjusting parameters such as a grayscale value of a given value, a setting of a larger number of N specific sub-pixels greater than a grayscale value of the given value, and/or a specific threshold of variance.
  • the severity of the background discrimination By changing the severity, you can change the range of the determined high-brightness area.
  • the invention can also be processed by different algorithms for different regions.
  • the variance is less than or equal to 50. Alternatively, the variance is less than or equal to 40.
  • the more the number N of specific sub-pixels larger than the grayscale value of a given value the more severe the discrimination condition.
  • the larger the gray scale value of a given value the more stringent the discrimination condition.
  • the smaller the variance the more stringent the discrimination conditions.
  • the grayscale value of the given value is greater than 180.
  • the grayscale value of a given value is greater than 200.
  • an array of grayscale values of specific sub-pixels in the s ⁇ mth row and the t ⁇ nth column pixel centered on the pixel in the tth column of the sth row represents odd rows ⁇ odd columns Gray scale values.
  • the odd-numbered rows/odd-numbered grayscale values are grayscale values of specific sub-pixels within 3 rows ⁇ 5 columns or 5 rows ⁇ 7 columns.
  • the arrays are arranged in descending order.
  • the array is arranged in ascending order.
  • the grayscale value array of a particular sub-pixel determined to be a non-high luminance background region is low pass filtered.
  • the specific sub-pixel is a red sub-pixel, a green sub-pixel, or a blue sub-pixel.
  • an apparatus for discriminating an image brightness background is provided.
  • the method may include: a receiving unit, configured to receive image information to be discriminated, the image information includes grayscale values of each sub-pixel in each pixel; and a storage unit configured to use the sth row and the tth column of the image information
  • the grayscale value of the specific sub-pixel in the t ⁇ nth column of the s ⁇ m line of the center constitutes an array, and the array is arranged in order, where s, m, t, n are self a determining unit, if the grayscale values of the larger N specific sub-pixels in the array are greater than the grayscale value of the given value, and the variance is less than or equal to a certain threshold, determining the s ⁇ m row and the t ⁇
  • the specific sub-pixels in the n columns are high-brightness background regions, otherwise it is determined that the specific sub-pixels in the s ⁇ mth row and the t ⁇ nth column are non-high-brightness background regions.
  • the apparatus for discriminating the luminance background of the image of the present invention By means of the apparatus for discriminating the luminance background of the image of the present invention, the grayscale value of different given values, the number of larger N specific sub-pixels larger than the grayscale value of the given value, and the variance of different specific thresholds are used. Differentiating the severity of the brightness background can be made. For example, the entire image area is discriminated as a high-luminance area, a low-luminance area, and a transition area between the high-luminance area and the low-luminance area, respectively. After the high-luminance region, the low-luminance region, and the transition region are discriminated, the regions of different luminance backgrounds are subjected to corresponding refinement processing. In other words, the present invention is directed to a high resolution algorithm design based on high brightness background discrimination.
  • the present invention discriminates between two common backgrounds (high-brightness backgrounds and non-high-brightness backgrounds) to distinguish between high-brightness backgrounds and non-high-brightness backgrounds.
  • the present invention can change the high brightness by adjusting parameters such as a grayscale value of a given value, a setting of a larger number of N specific sub-pixels greater than a grayscale value of the given value, and/or a specific threshold of variance.
  • the severity of the background discrimination By changing the severity, you can change the range of the determined high-brightness area.
  • the invention can also be processed by different algorithms for different regions.
  • the variance is less than or equal to 50. Alternatively, the variance is less than or equal to 40. In another embodiment of the present invention, the more the number N of specific sub-pixels larger than the grayscale value of a given value, the more severe the discrimination condition. Alternatively, the larger the gray scale value of a given value, the more stringent the discrimination condition. Alternatively, the smaller the variance, the more stringent the discrimination conditions.
  • a display apparatus comprising the above-described method of discriminating an image luminance background and/or the above-described apparatus for discriminating an image luminance background.
  • the grayscale value of different given values, the number of larger N specific sub-pixels larger than the grayscale value of the given value, and the variance of different specific thresholds can be used for the luminance background. Different degrees of severity are judged. For example, the entire image area is discriminated as a high-luminance area, a low-luminance area, and a transition area between the high-luminance area and the low-luminance area, respectively. After the high-luminance region, the low-luminance region, and the transition region are discriminated, the regions of different luminance backgrounds are subjected to corresponding refinement processing. In other words, the present invention is directed to a high resolution algorithm design based on high brightness background discrimination.
  • the present invention discriminates between two common backgrounds (high-brightness backgrounds and non-high-brightness backgrounds) to distinguish between high-brightness backgrounds and non-high-brightness backgrounds.
  • the invention can be adjusted by adjusting parameters such as a given value
  • the setting of the grayscale value, the number of larger N specific sub-pixels larger than the grayscale value of the given value, and/or the specific threshold of the variance change the severity of the high-brightness background discrimination. By changing the severity, you can change the range of the determined high-brightness area.
  • the invention can also be processed by different algorithms for different regions.
  • 1A and 1B show two arrangement modes of respective sub-pixels.
  • 2A is an example of inputting red sub-pixels of three rows ⁇ 5 columns centering on the sth row and the tth column in the case of FIG. 1A.
  • 2B is an example of the input of the red sub-pixels of the 3 rows ⁇ 5 columns centering on the s-th row and the t-th column in the case of FIG. 1B.
  • FIG. 3 is a flow chart of high brightness background discrimination in accordance with one embodiment of the present invention.
  • Fig. 5 shows an example of loose high brightness discrimination and severe high brightness discrimination according to an embodiment of the present invention.
  • the method 30 for discriminating the brightness background of the image shown in FIG. 3 may include the following steps:
  • the grayscale value may be a grayscale value of a red subpixel in each pixel, represented by arrays r_01, r_02, r_03, ..., r_n.
  • the grayscale value may be a grayscale value of a green subpixel in each pixel, represented by arrays g_01, g_02, g_03, ..., g_n.
  • the grayscale value may be a grayscale value of the blue subpixel in each pixel, represented by the arrays b_01, b_02, b_03, ..., b_n.
  • a red sub-pixel is taken as an example for explanation.
  • red sub-pixels mentioned in the following embodiments are only schematic, and can also be used for green sub-pixels, blue sub-pixels or sub-pixels of other colors. Perform the appropriate processing. That is, the specific sub-pixels mentioned in the following various embodiments may be red sub-pixels, green sub-pixels, blue sub-pixels, or sub-pixels of other colors.
  • step S34 the grayscale values of the specific sub-pixels (for example, red sub-pixels) in the s ⁇ mth row and the t ⁇ nth column of the image in the sth row and the tth column of the pixel in the image information are formed into an array, and This array is arranged in order, where s, m, t, n are natural numbers.
  • the sub-pixel arrangement shown in FIG. 1 can be employed.
  • the sub-pixels of this arrangement can make full use of the spatial arrangement of the three colors of red, green and blue, which is advantageous for achieving higher resolution.
  • Each of the sub-pixels for example, the red sub-pixel R, the green sub-pixel G, and the blue sub-pixel B has an aspect ratio of 2:3.
  • three sub-pixels constitute two pixels, and one repeating group includes four pixels. That is, the so-called delta pixel arrangement in the art.
  • the sub-pixels of the first row are in accordance with R, G, B; R, G, B; Arranged in order.
  • the sub-pixels of the second row are arranged in the order of B, R, G; B, R, G; ..., and the second row is arranged with respect to the position of the first row staggered by 1/2 red sub-pixels R, Or, the blue sub-pixel B at the beginning of the second line is arranged with respect to the red sub-pixel R at the beginning of the first line, and the size of the half-blue sub-pixel B or the half-red sub-pixel R is indented.
  • the third row repeats the arrangement of the first row, and the fourth row repeats the arrangement of the second row, which is sequentially performed.
  • the display screen obtained according to this arrangement only needs to input s rows and t/2 columns, that is, it can be obtained with s rows and t columns.
  • the same resolution saves the layout of the data lines.
  • FIG. 1A is merely one embodiment for implementing the present invention.
  • the arrangement manner of each sub-pixel in the image of the present invention may also adopt the size of the red sub-pixel R, the green sub-pixel G and the blue sub-pixel B in the usual sense, that is, the aspect ratio is 1:1, for example, as shown in FIG. 1B.
  • the aspect ratio is 2:3.
  • the arrangement of each sub-pixel in the image of the present invention may also be arranged in the usual sense of the red sub-pixel R, the green sub-pixel G and the blue sub-pixel B, as shown in FIG. 1B instead of FIG. 1A.
  • each of the red sub-pixel, the green sub-pixel, and the blue sub-pixel is one column, and the red sub-pixel column, the green sub-pixel column, and the blue sub-pixel column are alternately arranged in the column direction. Using the arrangement in Figure 1B, the same can be done. The technical effect of the present invention is now achieved.
  • FIG. 2A is a diagram showing a correspondence relationship between actual pixels and input signals of red sub-pixels of 3 rows ⁇ 5 columns centered on the sth row and the tth column, taking the red sub-pixel as an example.
  • the sth row and the tth column in FIG. 2A are centered only for convenience of explanation and do not have a special meaning.
  • the square area in FIG. 2A is an input signal, and the corresponding input signal number is r_01, r_02...r_15, the oblique line background area is the actual pixel position (output signal position), and the actual pixel is centered on the sth line and the tth column.
  • the corresponding input signal coordinates are the sth row and the 2t-1th column.
  • an odd row represented by an array of grayscale values of a specific sub-pixel within the s ⁇ mth row and the t ⁇ nth column pixel centered on the pixel of the tth column of the sth row may be employed.
  • ⁇ odd-numbered columns have grayscale values.
  • m is 1
  • n is 2
  • the s row and the t column are arbitrarily selected row numbers and column numbers.
  • the odd-numbered rows/odd-numbered grayscale values may be grayscale values of specific sub-pixels within 3 rows ⁇ 5 columns or 5 rows ⁇ 7 columns. In the case shown in FIG.
  • the gray scale value of the red sub-pixel in 3 rows ⁇ 5 columns is taken as an example, that is, the gray scale value centered on (s, t) constitutes an array, [r_01 , r_02, r_03, ..., r_14, r_15].
  • the arrays [r_01, r_02, r_03, ..., r_14, r_15] here are gray scale values including 15 red sub-pixels in the s ⁇ 1th row and the t ⁇ 2th column pixel shown in FIG. 2A. An array of constituents.
  • the array of gray scale values of the red sub-pixels includes an array of gray scale values of the red sub-pixels in the s ⁇ 2th row and the t ⁇ 3th column pixel, where m is 2, n is 3.
  • the case where the gray scale values of the red sub-pixels in the 5 rows ⁇ 7 columns constitute an array is not shown in the drawings of the specification, but it is not difficult to understand by those skilled in the art.
  • FIG. 2B is an example of the input of the red sub-pixels of the 3 rows ⁇ 5 columns centering on the s-th row and the t-th column in the case of FIG. 1B.
  • the sth row and the tth column in FIG. 2 are centered only for the convenience of explanation and do not have a special meaning.
  • the square area is the input signal, and the corresponding input signal number is r_01, r_02...r_15.
  • an odd row represented by an array of grayscale values of a specific sub-pixel within the s ⁇ mth row and the t ⁇ nth column pixel centered on the pixel of the tth column of the sth row may be employed.
  • ⁇ odd-numbered columns have grayscale values.
  • m is 1, n is 2, and the s row and the t column are arbitrarily selected row numbers and column numbers.
  • the odd-numbered rows/odd-numbered grayscale values may be grayscale values of specific sub-pixels within 3 rows ⁇ 5 columns or 5 rows ⁇ 7 columns. In the case shown in Fig. 2B, it is 3 rows x 5 columns.
  • the gray scale value of the red sub-pixel is explained as an example, that is, the gray scale value centered on (s, t) constitutes an array, [r_01, r_02, r_03, ..., r_14, r_15].
  • the arrays [r_01, r_02, r_03, ..., r_14, r_15] here are gray scale values including 15 red sub-pixels in the s ⁇ 1th row and the t ⁇ 2th column pixel shown in FIG. 2B.
  • the array of gray scale values of the red sub-pixels includes an array of gray scale values of the red sub-pixels in the s ⁇ 2th row and the t ⁇ 3th column pixel, where m is 2, n is 3.
  • m is 2, n is 3.
  • the gray scale values of the red sub-pixels in the 5 rows ⁇ 7 columns constitute an array is not shown in the drawings of the specification, but it is not difficult to understand by those skilled in the art.
  • the array [r_01, r_02, r_03, ..., r_14, r_15] consisting of grayscale values centered at arbitrary (s, t) as shown in Fig. 2A or Fig. 2B is ordered. Arrange, assuming that the array is arranged in descending order, from large to small, [r_01, r_02, r_03, ..., r_14, r_15]. Alternatively, the array can also be arranged in ascending order.
  • step S36 if the grayscale values of the larger N specific sub-pixels in the array are both greater than the grayscale value of the given value, and the variance is less than or equal to the specific threshold, the s ⁇ mth row and the tth are determined in step S38.
  • the specific sub-pixels in the ⁇ n column are high-brightness background regions, otherwise it is determined in step S39 that the specific sub-pixels in the s ⁇ mth row and the t ⁇ nth column are non-high-brightness background regions.
  • the larger N red sub-pixels in the array [r_01, r_02, r_03, ..., r_14, r_15] can select different N numbers depending on whether the luminance background discrimination or the loose luminance background discrimination is performed. It should be noted that the more the number N of specific sub-pixels larger than the grayscale value of the given value, the more severe the discrimination condition.
  • the condition of the number N of specific sub-pixels larger than the grayscale value of the given value is selected to be 7, which means that if there is If 7 or more red sub-pixels satisfy the grayscale value whose gray value is greater than a given value, and the variance is less than or equal to a certain threshold, then 15 red children represented by grayscale values centered on arbitrary (s, t) are considered
  • the pixels are all high-brightness background regions.
  • red sub-pixels satisfying the gray-scale value whose gray value is greater than a given value, and the variance is less than or equal to a certain threshold, it is considered to be arbitrary (s, t)
  • the 15 red sub-pixels represented by the center grayscale values are non-brightness background regions.
  • the condition of the number N of specific subpixels larger than the grayscale value of the given value is selected to be 5, which means that if If five or more red sub-pixels satisfy the grayscale value whose gray value is greater than a given value, and the variance is less than or equal to a certain threshold, it is considered to represent the grayscale value centered on arbitrary (s, t).
  • the 15 red sub-pixels are all high-brightness background areas.
  • red sub-pixels satisfying the gray-scale value whose gray value is greater than a given value, and the variance is less than or equal to a certain threshold, it is considered
  • the 15 red sub-pixels represented by arbitrary (s, t)-centered grayscale values are non-brightness background regions.
  • the number N of specific sub-pixels larger than the gray value of the given value is selected to be 7.
  • the condition that the number N of specific sub-pixels larger than the gray-scale value of the given value is selected to be 5 is more severe.
  • FIG. Fig. 5 is a view showing the result displayed in the case of different severity determination of brightness in the content displayed on the screen.
  • the image of many areas near the number "1.3" is discriminated as high luminance, and is displayed as White, the rest of the area is shown in black.
  • an array of grayscale values of a particular sub-pixel determined to be a non-high-brightness background region is low-pass filtered.
  • the result obtained by subtracting the image obtained by the harsh luminance background discrimination condition from the image obtained by the loose luminance background discrimination condition is referred to as a transition region.
  • the transition region is then low pass filtered. That is, the non-high-brightness background area actually contains the transition area and the true low-brightness background area.
  • transition region is distinguished from the non-high-brightness background region.
  • the reason why the transition region is distinguished from the non-high-brightness background region is to perform low-pass filtering on the transition region later, which can improve the color glitch appearing at the edge of an image such as a font. It should be pointed out that here is the transition zone. Low pass filtering is not required. In some cases, the step of low pass filtering the transition region may be omitted in the case where the image, such as a colored glitch appearing at the edge of the font, is not very severe.
  • 4 is a result of discrimination of high luminance background discrimination according to an embodiment of the present invention. The image is divided into three parts in FIG. 4: a high-brightness background area 42, a low-brightness background area 46, and a transition area 44.
  • a subsequent corresponding high-brightness algorithm may be performed for the high-brightness background area 42.
  • a subsequent corresponding low-brightness algorithm may be performed for the low-brightness background area 46, and for the transition area 44, subsequent low-pass filtering may be performed.
  • the corresponding high-brightness algorithm, the low-brightness algorithm, and the low-pass filtering algorithm those skilled in the art can refer to other related patent applications of the applicant, and these are not the inventions of the present invention, and are not described herein again.
  • the variance is the average of the sum of the squares of the differences between the individual data and their mean, and the variance is used to measure the degree of deviation between the random variable and its mathematical expectation (i.e., mean).
  • the variance of the arrays [r_01, r_02, r_03, ..., r_14, r_15] is less than or equal to 50.
  • the variance of the array [r_01, r_02, r_03, ..., r_14, r_15] is less than or equal to 40.
  • the input image information includes grayscale values for each of the sub-pixels in each pixel.
  • the grayscale values of the respective sub-pixels are in the range of 0-256 in the usual sense, wherein the grayscale value of the given value may be greater than 180.
  • the grayscale value of the given value is greater than 200.
  • the difference in the number of N specific sub-pixels larger than the gray value of the given value affects the severity of the luminance background discrimination.
  • the grayscale value of the given value when the grayscale value of the given value is selected to be 180, if the array is larger than 180
  • the number of larger specific sub-pixels of the grayscale value is set to seven, if actually, the grayscale values of the eight larger red sub-pixels are greater than the grayscale value of the given value by 180, and the variance is less than or equal to the specific
  • the threshold value determines that the red sub-pixels in the s ⁇ 1th row and the t ⁇ 2th column are high-brightness background regions, if actually, the grayscale values of the six larger red sub-pixels are greater than the grayscale value of the given value.
  • the red sub-pixels in the s ⁇ 1th row and the t ⁇ 2th column are non-high-brightness background regions.
  • the grayscale value of the given value is 200, if the number of larger specific subpixels larger than 200 grayscale values in the array is still set to 7, if there are actually 8 larger red subpixels
  • the grayscale value is greater than the grayscale value of 200 of the given value, and the variance is less than or equal to a certain threshold, it is determined that the red subpixel in the s ⁇ 1th row and the t ⁇ 2th column is a high-brightness background region, if there are actually 6
  • the grayscale values of the larger red sub-pixels are greater than Given a grayscale value of 200, and the variance is less than or equal to a certain threshold, it is still determined that the red subpixels in the s ⁇ 1th and t ⁇ 2th columns are non-high-brightness background regions. Obviously, the larger the grayscale value of the given value is 200, if the number of larger specific
  • the specific threshold of the variance can also be set differently as needed.
  • the grayscale value at a given value is set to 180, which is larger than the given value.
  • the number of the larger N red sub-pixels of the grayscale value 180 is set to 7, and the number of the grayscale values greater than 180 in the array [r_01, r_02, r_03, ..., r_14, r_15] is actually 8
  • the variance is 40.
  • the specific threshold of the set variance is 45, since the variance 40 of the 8 gray values is less than the set variance threshold 45, 15 of the arrays [r_01, r_02, r_03, ..., r_14, r_15] are considered to be represented.
  • the area of the red sub-pixel is a high-brightness background area. If the specific threshold of the set variance is 39, since the variance 40 of the 8 gray values is greater than the set variance threshold 39, the other two conditions are satisfied, that is, the array [r_01, r_02, r_03, ...
  • the number of grayscale values 180 greater than a given value is 8 (greater than the setting of the number of larger N red subpixels 7), but the array [r_01, r_02, r_03, The area of the 15 red sub-pixels represented by ..., r_14, r_15] is a non-high-brightness background area. It can be seen that the specific threshold setting of the variance also has an influence on the severity of the luminance background discrimination.
  • the grayscale value of different given values, the number of larger N specific sub-pixels larger than the grayscale value of the given value, and the variance of different specific thresholds are all severe for the brightness background discrimination.
  • the degree of influence, all of which are parameters that affect the severity of the brightness background, are independent of each other.
  • the grayscale value of the given value may be selected to be 200, the specific threshold of the variance is 50, and the number of the larger N red subpixels greater than the grayscale value of the given value is set. Is 5. If there are actually more than 5 large red sub-pixels in the array [r_01, r_02, r_03, ..., r_14, r_15], the grayscale values are greater than the grayscale value of 200 of the given value, and the variance is less than or equal to the specific
  • the threshold value of 50 determines that the 15 red sub-pixels in the s ⁇ 1th row and the t ⁇ 2th column are high-brightness background regions, otherwise it is determined that the 15 red sub-pixels in the s ⁇ 1th row and the t ⁇ 2th column are non- High brightness background area.
  • the gray scale value of different given values, the number of larger N specific sub-pixels larger than the gray scale value of the given value, and different The variance of a specific threshold can be judged differently for the degree of severity of the luminance background.
  • the entire image area is discriminated as a high-luminance area, a low-luminance area, and a transition area between the high-luminance area and the low-luminance area, respectively.
  • the regions of different luminance backgrounds are subjected to corresponding refinement processing.
  • the present invention is directed to a high resolution algorithm design based on high brightness background discrimination.
  • the present invention discriminates between two common backgrounds (high-brightness backgrounds and non-high-brightness backgrounds) to distinguish between high-brightness backgrounds and non-high-brightness backgrounds.
  • the present invention can change the high brightness by adjusting parameters such as a grayscale value of a given value, a setting of a larger number of N specific sub-pixels greater than a grayscale value of the given value, and/or a specific threshold of variance.
  • the severity of the background discrimination By changing the severity, you can change the range of the determined high-brightness area.
  • the invention can also be processed by different algorithms for different regions.
  • the range of high-brightness regions determined may vary. As shown in Figure 5A, the relaxed brightness background discrimination results in a more white background with less black background. As shown in Figure 5B, the harsh brightness background discrimination results in fewer white backgrounds and more black background.
  • the luminance background discrimination method of the present invention needs to refer to luminance data in one region, and determines the luminance background based on the range of these data. As mentioned above, these data can be adjusted by using different grayscale values of a given value, the number of larger N specific sub-pixels larger than the grayscale value of the given value, and the variance of different specific thresholds. The size of the range changes the severity of the discriminant algorithm.
  • an apparatus for discriminating an image brightness background may include: a receiving unit, configured to receive image information to be discriminated, the image information including grayscale values of respective sub-pixels in each pixel a storage unit configured to form an array of grayscale values of the specific sub-pixels in the s ⁇ mth row and the t ⁇ nth column of the image in the s-th row and the t-th column of the image, and order the array Arrangement, wherein s, m, t, n are natural numbers; determining unit, if the grayscale values of the larger N specific sub-pixels in the array are greater than the grayscale value of the given value, and the variance is less than or equal to a certain threshold, then determining The specific sub-pixels in the s ⁇ m rows and the t ⁇ nth columns are high-brightness background regions, otherwise it is determined that the specific sub-pixels in the s ⁇ m rows and t ⁇ n columns are non-high-brightness background regions
  • the grayscale value of different given values the number of larger N specific sub-pixels larger than the grayscale value of the given value, and the variance of different specific thresholds are used. Differentiating the severity of the brightness background can be made. For example will The entire image area is discriminated as a high brightness area, a low brightness area, and a transition area between the high brightness area and the low brightness area, respectively. After the high-luminance region, the low-luminance region, and the transition region are discriminated, the regions of different luminance backgrounds are subjected to corresponding refinement processing. In other words, the present invention is directed to a high resolution algorithm design based on high brightness background discrimination.
  • the present invention discriminates between two common backgrounds (high-brightness backgrounds and non-high-brightness backgrounds) to distinguish between high-brightness backgrounds and non-high-brightness backgrounds.
  • the present invention can change the high brightness by adjusting parameters such as a grayscale value of a given value, a setting of a larger number of N specific sub-pixels greater than a grayscale value of the given value, and/or a specific threshold of variance.
  • the severity of the background discrimination By changing the severity, you can change the range of the determined high-brightness area.
  • the invention can also be processed by different algorithms for different regions.
  • the variance is less than or equal to 50. Alternatively, the variance is less than or equal to 40.
  • the more the number N of specific sub-pixels larger than the grayscale value of the given value the more severe the discrimination condition.
  • the larger the gray scale value of a given value the more stringent the discrimination condition.
  • the smaller the variance the more stringent the discrimination conditions.
  • a display apparatus which may include a method of discriminating an image luminance background as described above and/or the above-described apparatus for discriminating an image luminance background.

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Abstract

一种判别图像亮度背景的方法、装置和显示装置，其中判别图像亮度背景的方法包括下面的步骤：接收待判别的图像信息，该图像信息包含了每个像素中各个子像素的灰阶值；将该图像信息中以第s行第t列像素为中心的第s±m行第t±n列像素内特定子像素的灰阶值构成数组，并且将此数组按序排列，其中s, m, t, n是自然数；若数组内较大的N个特定子像素的灰阶值均大于给定值的灰阶值，并且方差小于等于特定阈值，则判定该第s±m行和第t±n列内特定子像素为高亮度背景区域，否则判定该第s±m行和第t±n列内特定子像素为非高亮度背景区域。借助于本方法，可以将图像区域判别为高亮度区域或非高亮度区域。

Description

一种判别图像亮度背景的方法、装置和显示装置 技术领域
本发明涉及图像显示领域，特别涉及一种判别图像亮度背景的方法、一种判别图像亮度背景的装置及其显示装置。
背景技术
在显示领域中，例如移动显示领域中，高亮度背景(比如文字页面的白色背景)和低亮度背景(比如文字页面的夜间模式)是非常常见的两种应用场景，这两类图像的处理方式存在差别。但是在现有技术中对于不同的亮度背景仅仅是通过不同的灰阶值进行物理的表示，并没有认识到图像的亮度背景还存在还进的余地，以便更好地显示和处理图像。
在现有技术中亟待一种改进图像的亮度背景，以便更好地显示和处理图像的技术。
发明内容
有鉴于此，本发明提供一种判别图像亮度背景的方法、一种判别图像亮度背景的装置及其显示装置，其能够解决或者至少缓解现有技术中存在的至少一部分缺陷。
根据本发明的第一个方面，提供一种判别图像亮度背景的方法，其可以包括下面的步骤：接收待判别的图像信息，该图像信息包含了每个像素中各个子像素的灰阶值；将该图像信息中以第s行第t列像素为中心的第s±m行第t±n列像素内特定子像素的灰阶值构成数组，并且将此数组按序排列，其中s，m，t，n是自然数；若数组内较大的N个特定子像素的灰阶值均大于给定值的灰阶值，并且方差小于等于特定阈值，则判定该第s±m行和第t±n列内特定子像素为高亮度背景区域，否则判定该第s±m行和第t±n列内特定子像素为非高亮度背景区域。
借助于本发明的判别图像亮度背景的方法，利用不同的给定值的灰阶值、大于该给定值的灰阶值的较大N个特定子像素的个数、不同特定阈值的方差，可以对于亮度背景进行严苛程度不同的判别。例如 将整个图像区域分别判别为高亮度区域、低亮度区域和介于高亮度区域、低亮度区域两者之间的过渡区域。在判别了高亮度区域、低亮度区域和过渡区域之后，对于不同亮度背景的区域进行相应的细化处理。换句话说，本发明针对的是一种基于高亮度背景判别的高分辨率算法设计。本发明对常见的两种背景(高亮度背景和非高亮度背景)进行判别，区分出高亮度背景和非高亮度背景。本发明可以通过调整参数，例如给定值的灰阶值、大于该给定值的灰阶值的较大N个特定子像素个数的设定、和/或方差的特定阈值，改变高亮度背景判别的严苛程度。改变严苛程度，可以改变判定出来的高亮度区域的范围。本发明还可以针对不同的区域，采用不同的算法进行处理。
在本发明的一个实施例中，方差小于等于50。备选的，方差小于等于40。
在本发明的另一个实施例中，大于给定值的灰阶值的特定子像素的个数N越多，判别条件越严苛。备选的，给定值的灰阶值越大，判别条件越严苛。备选的，方差越小，判别条件越严苛。
在本发明的再一个实施例中，给定值的灰阶值为大于180。备选的，给定值的灰阶值为大于200。
在本发明的又一个实施例中，以第s行第t列像素为中心的第s±m行和第t±n列像素内特定子像素的灰阶值构成的数组代表奇数行×奇数列个灰阶值。备选的，该奇数行×奇数列个灰阶值是3行×5列或者5行×7列内的特定子像素的灰阶值。
在本发明的一个实施例中，该数组是按照降序排列的。备选的，该数组是按照升序排列的。
在本发明的另一个实施例中，对于判定为非高亮度背景区域的特定子像素的灰阶值数组进行低通滤波。
在本发明的再一个实施例中，该特定子像素是红色子像素、绿色子像素或者蓝色子像素。
根据本发明的第二个方面，提供一种判别图像亮度背景的装置，
可以包括：接收单元，用于接收待判别的图像信息，该图像信息包含了每个像素中各个子像素的灰阶值；存储单元，用于将该图像信息中以第s行第t列像素为中心的第s±m行第t±n列像素内特定子像素的灰阶值构成数组，并且将此数组按序排列，其中s，m，t，n是自 然数；判定单元，若数组内较大的N个特定子像素的灰阶值均大于给定值的灰阶值，并且方差小于等于特定阈值，则判定该第s±m行和第t±n列内特定子像素为高亮度背景区域，否则判定该第s±m行和第t±n列内特定子像素为非高亮度背景区域。
借助于本发明的判别图像亮度背景的装置，利用不同的给定值的灰阶值、大于该给定值的灰阶值的较大N个特定子像素的个数、不同特定阈值的方差，可以对于亮度背景进行严苛程度不同的判别。例如将整个图像区域分别判别为高亮度区域、低亮度区域和介于高亮度区域、低亮度区域两者之间的过渡区域。在判别了高亮度区域、低亮度区域和过渡区域之后，对于不同亮度背景的区域进行相应的细化处理。换句话说，本发明针对的是一种基于高亮度背景判别的高分辨率算法设计。本发明对常见的两种背景(高亮度背景和非高亮度背景)进行判别，区分出高亮度背景和非高亮度背景。本发明可以通过调整参数，例如给定值的灰阶值、大于该给定值的灰阶值的较大N个特定子像素个数的设定、和/或方差的特定阈值，改变高亮度背景判别的严苛程度。改变严苛程度，可以改变判定出来的高亮度区域的范围。本发明还可以针对不同的区域，采用不同的算法进行处理。
在本发明的一个实施例中，其中方差小于等于50。备选的，方差小于等于40。在本发明的另一个实施例中，大于给定值的灰阶值的特定子像素的个数N越多，判别条件越严苛。备选的，给定值的灰阶值越大，判别条件越严苛。备选的，方差越小，判别条件越严苛。
根据本发明的第三个方面，提供一种显示装置，包括使用上述的判别图像亮度背景的方法和/或上述的判别图像亮度背景的装置。
借助于本发明的显示装置，利用不同的给定值的灰阶值、大于该给定值的灰阶值的较大N个特定子像素的个数、不同特定阈值的方差，可以对于亮度背景进行严苛程度不同的判别。例如将整个图像区域分别判别为高亮度区域、低亮度区域和介于高亮度区域、低亮度区域两者之间的过渡区域。在判别了高亮度区域、低亮度区域和过渡区域之后，对于不同亮度背景的区域进行相应的细化处理。换句话说，本发明针对的是一种基于高亮度背景判别的高分辨率算法设计。本发明对常见的两种背景(高亮度背景和非高亮度背景)进行判别，区分出高亮度背景和非高亮度背景。本发明可以通过调整参数，例如给定值的 灰阶值、大于该给定值的灰阶值的较大N个特定子像素个数的设定、和/或方差的特定阈值，改变高亮度背景判别的严苛程度。改变严苛程度，可以改变判定出来的高亮度区域的范围。本发明还可以针对不同的区域，采用不同的算法进行处理。
附图说明
图1A、1B是各个子像素的两种排布方式。
图2A是以红色子像素为例，给出了图1A的情况下以第s行、第t列为中心的3行×5列的红色子像素的输入信息。
图2B是以红色子像素为例，给出了图1B的情况下以第s行、第t列为中心的3行×5列的红色子像素的输入信息。
图3是根据本发明一个实施例的高亮度背景判别的流程图。
图4是根据本发明一个实施例的高亮度背景判别的判别结果。
图5给出了根据本发明一个实施例的宽松高亮度判别和严苛高亮度判别的示例。
具体实施方式
下面，将交叉引用本发明的附图1-5对于本发明的各个实施例进行详细地描述。
图3是根据本发明一个实施例的高亮度背景判别的流程图。在图3所示的判别图像亮度背景的方法30，可以包括下面的步骤：
在步骤S32，接收待判别的图像信息，该图像信息包含了每个像素中各个子像素的灰阶值。例如，灰阶值可以是每个像素中的红色子像素的灰阶值，以数组r_01，r_02，r_03，...，r_n表示。备选的，灰阶值可以是每个像素中的绿色子像素的灰阶值，以数组g_01，g_02，g_03，...，g_n表示。备选的，灰阶值可以是每个像素中的蓝色子像素的灰阶值，以数组b_01，b_02，b_03，...，b_n表示。为了说明的方便，在本发明下面的实施例中是以红色子像素为例进行说明的。例如图2A和2B中所示的以(s，t)为中心的红色子像素灰阶值构成的数组，[r_01，r_02，r_03，...，r_14，r_15]。至于图2A和2B所示的情形，将在下面详细的描述。需要指出的是，下面的实施例中提到的红色子像素仅仅是示意性的，对于绿色子像素、蓝色子像素或者其他颜色的子像素同样可以 进行相应的处理。即，下面的各个实施例中提到的特定子像素可以是红色子像素、绿色子像素、蓝色子像素或者其他颜色的子像素。
在步骤S34，将该图像信息中以第s行第t列像素为中心的第s±m行第t±n列像素内特定子像素(例如红色子像素)的灰阶值构成数组，并且将此数组按序排列，其中s，m，t，n是自然数。在本发明的一个实施例中，可以采用图1所示的子像素排布方式。这种排布方式的子像素能充分利用红绿蓝三种颜色的空间排布，有利于实现更高的分辨率。其中每个子像素例如红色子像素R、绿色子像素G和蓝色子像素B的宽高比为2∶3，在这样的排布中三个子像素构成两个像素，一个重复组包含四个像素，即本领域中所谓的delta像素排列。在图1A所示的红色子像素R、绿色子像素G和蓝色子像素B的排布中，第一行的子像素是按照R、G、B；R、G、B；...的顺序排列的。第二行的子像素是按照B、R、G；B、R、G；...的顺序排列的，并且第二行相对于第一行错开1/2个红色子像素R的位置排列，或者说第二行开头的蓝色子像素B相对于第一行开头的红色子像素R缩进了半个蓝色子像素B或缩进了半个红色子像素R的尺寸开始排列的。第三行重复第一行的排列方式，第四行重复第二行的排列方式，依次进行。采用这样的排列方式，在输入信号为s行、t列的情况下，按照这种排布方式得到的显示屏，只需要输入s行、t/2列，即可以得到与s行、t列一样的分辨率，节省了数据线的布置。至于如何得到与s行、t列一样的分辨率，节省数据线布置这一点，可以参考申请人其他的相关专利申请，这些内容不是本发明的发明点，在此不再赘述。
需要指出的是，图1A仅仅是实现本发明的一个实施例。本发明图像中各个子像素的排布方式也可以采用通常意义上的红色子像素R、绿色子像素G和蓝色子像素B尺寸大小，即宽高比为1∶1，例如图1B所示的，而不是图1A中的红色子像素R、绿色子像素G和蓝色子像素B的宽高比为2∶3。同样，本发明图像中各个子像素的排布方式也可以采用通常意义上的红色子像素R、绿色子像素G和蓝色子像素B排布，如图1B中示出的，而不是图1A中所示的第二行相对于第一行错开、第四行相对于第三行错开的方式进行。图1B中红色子像素、绿色子像素、蓝色子像素各为一列，并且红色子像素列、绿色子像素列、蓝色子像素列在列方向上交替排列。采用图1B中的排布方式，同样可以实 现本发明的技术效果。
图2A是以红色子像素为例，给出了图1A的情况下以第s行、第t列为中心的3行×5列的红色子像素的实际像素和输入信号之间的对应关系。图2A中的第s行、第t列为中心仅仅是为了说明的方便，并不具有特别的含义。图2A中的方形区域为输入信号，对应输入信号的编号为r_01、r_02...r_15，斜线背景区域为实际像素位置(输出信号位置)，实际像素以第s行、第t列为中心，对应的输入信号坐标为第s行、第2t-1列。本区域中对应输入信号的行号和列号都标注在图2A中。在本发明的一个实施例中，可以采用以第s行第t列像素为中心的第s±m行和第t±n列像素内特定子像素的灰阶值构成的数组所代表的奇数行×奇数列个灰阶值。例如在图2A中m为1，n为2，s行和t列是任意选择的行号和列号。奇数行×奇数列个灰阶值可以是3行×5列或者5行×7列内的特定子像素的灰阶值。在图2A所示的情形中，是以3行×5列内的红色子像素的灰阶值作为例子进行说明的，即以(s，t)为中心的灰阶值构成了数组，[r_01，r_02，r_03，...，r_14，r_15]。此处的数组[r_01，r_02，r_03，...，r_14，r_15]是包括了图2A中所示的第s±1行和第t±2列像素内15个红色子像素的灰阶值构成的数组。备选的，可以是5行×7列内的红色子像素的灰阶值构成的数组，[r_01，r_02，r_03，...，r_34，r_35]。在5行×7列的情况下，红色子像素的灰阶值构成的数组包括了第s±2行和第t±3列像素内红色子像素的灰阶值构成的数组，此时m为2，n为3。对于5行×7列内的红色子像素的灰阶值构成数组的情形虽然没有在说明书附图中示出，但本领域技术人员是不难理解的。
图2B是以红色子像素为例，给出了图1B的情况下以第s行、第t列为中心的3行×5列的红色子像素的输入信息。图2中的第s行、第t列为中心仅仅是为了说明的方便，并不具有特别的含义。方形区域为输入信号，对应输入信号的编号为r_01、r_02...r_15。在本发明的一个实施例中，可以采用以第s行第t列像素为中心的第s±m行和第t±n列像素内特定子像素的灰阶值构成的数组所代表的奇数行×奇数列个灰阶值。例如在图2B中m为1，n为2，s行和t列是任意选择的行号和列号。奇数行×奇数列个灰阶值可以是3行×5列或者5行×7列内的特定子像素的灰阶值。在图2B所示的情形中，是以3行×5列 内的红色子像素的灰阶值作为例子进行说明的，即以(s，t)为中心的灰阶值构成了数组，[r_01，r_02，r_03，...，r_14，r_15]。此处的数组[r_01，r_02，r_03，...，r_14，r_15]是包括了图2B中所示的第s±1行和第t±2列像素内15个红色子像素的灰阶值构成的数组。备选的，可以是5行×7列内的红色子像素的灰阶值构成的数组，[r_01，r_02，r_03，...，r_34，r_35]。在5行×7列的情况下，红色子像素的灰阶值构成的数组包括了第s±2行和第t±3列像素内红色子像素的灰阶值构成的数组，此时m为2，n为3。对于5行×7列内的红色子像素的灰阶值构成数组的情形虽然没有在说明书附图中示出，但本领域技术人员是不难理解的。
如在上面提到的，将图2A或者图2B中所示的以任意(s，t)为中心的灰阶值构成的数组[r_01，r_02，r_03，...，r_14，r_15]按序排列，假设该数组是按照降序排列的，由大到小依次为[r_01，r_02，r_03，...，r_14，r_15]。备选的，该数组也可以按照升序排列。
在步骤S36，若数组内较大的N个特定子像素的灰阶值均大于给定值的灰阶值，并且方差小于等于特定阈值，则在步骤S38判定该第s±m行和第t±n列内特定子像素为高亮度背景区域，否则在步骤S39判定该第s±m行和第t±n列内特定子像素为非高亮度背景区域。例如，数组[r_01，r_02，r_03，...，r_14，r_15]内较大的N个红色子像素可以根据是严苛的亮度背景判别还是宽松的亮度背景判别而选择不同的N个数。需要指出的是，大于给定值的灰阶值的特定子像素的个数N越多，判别条件越严苛。例如，在大于给定值的灰阶值，并且方差小于等于特定阈值条件下，大于给定值的灰阶值的特定子像素的个数N的条件选择为7，这就意味着，如果有7个或者以上的红色子像素都满足灰度值大于给定值的灰阶值，并且方差小于等于特定阈值，则认为以任意(s，t)为中心的灰阶值代表的15个红色子像素都是高亮度背景区域，如果有7个以下(不含7个)的红色子像素满足灰度值大于给定值的灰阶值，并且方差小于等于特定阈值，则认为以任意(s，t)为中心的灰阶值代表的15个红色子像素都是非亮度背景区域。类似的，在大于给定值的灰阶值，并且方差小于等于特定阈值条件下，大于给定值的灰阶值的特定子像素的个数N的条件选择为5，这就意味着，如果有5个或者以上的红色子像素都满足灰度值大于给定值的灰阶值，并且方差小于等于特定阈值，则认为以任意(s，t)为中心的灰阶值代表的 15个红色子像素都是高亮度背景区域，如果有5个以下(不含5个)的红色子像素满足灰度值大于给定值的灰阶值，并且方差小于等于特定阈值，则认为以任意(s，t)为中心的灰阶值代表的15个红色子像素都是非亮度背景区域。显然，大于给定值的灰阶值的特定子像素的个数N选择为7比大于给定值的灰阶值的特定子像素的个数N选择为5的条件更加严苛。
对于不同的严苛程度，得到的判别结果是不同的。例如在图5中给出了根据本发明一个实施例的宽松高亮度判别A和严苛高亮度判别B的示例。图5是以屏幕显示的内容示出在不同严苛程度亮度判别情况下显示的结果。在大于给定值的灰阶值的特定子像素的个数N较少的情况下，如图5中的A图所示的，数字“1.3”附近很多区域的图像判别为高亮度，显示为白色，其余区域显示为黑色。换句话说，在这样亮度背景的判别下，较多的区域被判别为高亮度区域，较少的区域被判别为非亮度区域。图像显示的结果为，图像中的白色部分较多，黑色部分较少。这样的亮度判别，我们可以称之为宽松的高亮度判别。备选的，以屏幕显示的相同图像进行另外一种严苛程度较大的判别，即，在大于给定值的灰阶值的特定子像素的个数N较多的情况下，如图5中的B图所示的，数字“1.3”附近很多区域的图像判别为非高亮度，显示为黑色，其余区域显示为白色。换句话说，在这样亮度背景的判别下，较多的区域被判别为非高亮度区域，较少的区域被判别为高亮度区域。图像显示的结果为，图像中的黑色部分较多，白色部分较少。这样的亮度判别，我们可以称之为严苛的高亮度判别。至于影响严苛程度的其他因素还将在下面详细描述。
在本发明的另一个实施例中，我们可以对于被判定为非高亮度背景区域的图像进行进一步的处理。例如对于判定为非高亮度背景区域的特定子像素的灰阶值数组进行低通滤波。具体的，对于同一图像，将采用宽松亮度背景判别条件得到的图像减去采用严苛亮度背景判别条件得到的图像而得到的结果称为过渡区域。然后对于该过渡区域进行低通滤波。也就是说，非高亮度背景区域实际上包含了过渡区域和真正的低亮度背景区域。之所以将过渡区域从非高亮度背景区域中区分出来是为了后面对于过渡区域进行低通滤波，这样可以改善在图像例如字体边缘出现的彩色毛刺。需要指出的是，这里对于过渡区域进 行低通滤波并不是必须的。在有些情况下，在图像例如字体边缘出现的彩色毛刺并不是很严重的情况下，对于过渡区域进行低通滤波的步骤是可以省略的。图4是根据本发明一个实施例的高亮度背景判别的判别结果。图4中示出了将图像区分为三个部分：高亮度背景区域42、低亮度背景区域46、过渡区域44。对于高亮度背景区域42，可以进行后续的对应的高亮度算法，对于低亮度背景区域46，可以进行后续的对应的低亮度算法，对于过渡区域44，可以进行后续的低通滤波。至于如何进行相应的高亮度算法、低亮度算法、低通滤波算法，本领域技术人员可以参考申请人其他相关的专利申请，这些内容并不是本发明的发明点，在此不再赘述。
本领域技术人员知晓的是，方差是各个数据分别与其平均数之差的平方的和的平均数，方差用来度量随机变量和其数学期望(即均值)之间的偏离程度。在本发明的各个实施例中，数组[r_01，r_02，r_03，...，r_14，r_15]的方差小于等于50。优选的，数组[r_01，r_02，r_03，...，r_14，r_15]方差小于等于40。
在本发明的各个实施例中，输入的图像信息包括每个像素中各个子像素的灰阶值。各个子像素的灰阶值处于通常意义上的0-256范围，其中给定值的灰阶值可以大于180。优选的，给定值的灰阶值大于200。
需要指出的是，如在上面提到的，大于给定值的灰阶值的较大N个特定子像素的个数不同影响了亮度背景判别的严苛程度。例如在15个红色子像素的灰度值构成的数组[r_01，r_02，r_03，...，r_14，r_15]中，在选择给定值的灰阶值为180时，如果该数组中大于180灰阶值的较大特定子像素的个数设定为7个，若实际上有8个较大的红色子像素的灰阶值均大于给定值的灰阶值180，并且方差小于等于特定阈值，则判定第s±1行和第t±2列内红色子像素为高亮度背景区域，若实际上有6个较大的红色子像素的灰阶值均大于给定值的灰阶值180，并且方差小于等于特定阈值，则仍然判定第s±1行和第t±2列内红色子像素为非高亮度背景区域。在选择给定值的灰阶值为200时，如果该数组中大于200灰阶值的较大特定子像素的个数仍然设定为7个，若实际上有8个较大的红色子像素的灰阶值均大于给定值的灰阶值200，并且方差小于等于特定阈值，则判定第s±1行和第t±2列内红色子像素为高亮度背景区域，若实际上有6个较大的红色子像素的灰阶值均大于 给定值的灰阶值200，并且方差小于等于特定阈值，则仍然判定第s±1行和第t±2列内红色子像素为非高亮度背景区域。显然，设定的给定值的灰阶值越大，亮度背景判别越严苛。由此可见，给定值的灰阶值的设定对于亮度背景判别的严苛程度是有影响的。
另外，还需要指出的是，方差的特定阈值也可以根据需要进行不同的设定。例如在15个红色子像素的灰度值构成的数组[r_01，r_02，r_03，...，r_14，r_15]中，在给定值的灰阶值设定为180，大于该给定值的灰阶值180的较大N个红色子像素的个数设定为7，实际上数组[r_01，r_02，r_03，...，r_14，r_15]中大于180灰阶值的个数为8个的情况下，该8个灰度值的方差为40。如果设定方差的特定阈值为45，由于该8个灰度值的方差40小于设定的方差阈值45，则认为数组[r_01，r_02，r_03，...，r_14，r_15]代表的15个红色子像素的区域为高亮度背景区域。如果设定方差的特定阈值为39，由于该8个灰度值的方差40大于设定的方差阈值39，此时虽然满足了另外两个条件，即数组[r_01，r_02，r_03，...，r_14，r_15]中大于给定值的灰阶值180的个数为8个(大于较大N个红色子像素的个数7的设定)，但仍然认为数组[r_01，r_02，r_03，...，r_14，r_15]代表的15个红色子像素的区域为非高亮度背景区域。由此可见，方差的特定阈值设定对于亮度背景判别的严苛程度也是有影响的。
基于上面的分析可见，不同的给定值的灰阶值、大于该给定值的灰阶值的较大N个特定子像素的个数、不同特定阈值的方差都会对于亮度背景判别的严苛程度产生影响，这三者都是影响亮度背景判别严苛程度的参数，并且是相互独立的。
在本发明的一个实施例中，可以选择给定值的灰阶值为200，方差的特定阈值为50，大于该给定值的灰阶值的较大N个红色子像素的个数设定为5。如果数组[r_01，r_02，r_03，...，r_14，r_15]中实际上有5个以上较大的红色子像素的灰阶值均大于给定值的灰阶值200，并且方差小于等于特定阈值50，则判定第s±1行和第t±2列内15个红色子像素为高亮度背景区域，否则判定该第s±1行和第t±2列内15个红色子像素为非高亮度背景区域。
借助于本发明的判别图像亮度背景的方法，利用不同的给定值的灰阶值、大于该给定值的灰阶值的较大N个特定子像素的个数、不同 特定阈值的方差，可以对于亮度背景进行严苛程度不同的判别。例如将整个图像区域分别判别为高亮度区域、低亮度区域和介于高亮度区域、低亮度区域两者之间的过渡区域。在判别了高亮度区域、低亮度区域和过渡区域之后，对于不同亮度背景的区域进行相应的细化处理。换句话说，本发明针对的是一种基于高亮度背景判别的高分辨率算法设计。本发明对常见的两种背景(高亮度背景和非高亮度背景)进行判别，区分出高亮度背景和非高亮度背景。本发明可以通过调整参数，例如给定值的灰阶值、大于该给定值的灰阶值的较大N个特定子像素个数的设定、和/或方差的特定阈值，改变高亮度背景判别的严苛程度。改变严苛程度，可以改变判定出来的高亮度区域的范围。本发明还可以针对不同的区域，采用不同的算法进行处理。
如在上面提到的，使用不同严苛程度的判别算法，判定出的高亮度区域范围会有差别。如在图5A中所示的，宽松的亮度背景判别得到较多的白色背景，较少的黑色背景。如在图5B中所示的，严苛的亮度背景判别得到较少的白色背景，较多的黑色背景。
本发明的亮度背景判别方法需要参考一个区域内的亮度数据，根据这些数据的范围来判定亮度背景。如在上面提到的，利用不同的给定值的灰阶值、大于该给定值的灰阶值的较大N个特定子像素的个数、不同特定阈值的方差，可以调节这些数据的范围的大小来改变判别算法的严苛程度。
根据本发明的第二个方面，提供一种判别图像亮度背景的装置，可以包括：接收单元，用于接收待判别的图像信息，该图像信息包含了每个像素中各个子像素的灰阶值；存储单元，用于将该图像信息中以第s行第t列像素为中心的第s±m行第t±n列像素内特定子像素的灰阶值构成数组，并且将此数组按序排列，其中s，m，t，n是自然数；判定单元，若数组内较大的N个特定子像素的灰阶值均大于给定值的灰阶值，并且方差小于等于特定阈值，则判定该第s±m行和第t±n列内特定子像素为高亮度背景区域，否则判定该第s±m行和第t±n列内特定子像素为非高亮度背景区域。
在本发明的判别图像亮度背景的装置中，利用不同的给定值的灰阶值、大于该给定值的灰阶值的较大N个特定子像素的个数、不同特定阈值的方差，可以对于亮度背景进行严苛程度不同的判别。例如将 整个图像区域分别判别为高亮度区域、低亮度区域和介于高亮度区域、低亮度区域两者之间的过渡区域。在判别了高亮度区域、低亮度区域和过渡区域之后，对于不同亮度背景的区域进行相应的细化处理。换句话说，本发明针对的是一种基于高亮度背景判别的高分辨率算法设计。本发明对常见的两种背景(高亮度背景和非高亮度背景)进行判别，区分出高亮度背景和非高亮度背景。本发明可以通过调整参数，例如给定值的灰阶值、大于该给定值的灰阶值的较大N个特定子像素个数的设定、和/或方差的特定阈值，改变高亮度背景判别的严苛程度。改变严苛程度，可以改变判定出来的高亮度区域的范围。本发明还可以针对不同的区域，采用不同的算法进行处理。
备选的，方差小于等于50。备选的，方差小于等于40。
备选的，大于给定值的灰阶值的特定子像素的个数N越多，判别条件越严苛。备选的，给定值的灰阶值越大，判别条件越严苛。备选的，方差越小，判别条件越严苛。
根据本发明的第三个方面，提供一种显示装置，其可以包括使用上述的判别图像亮度背景的方法和/或上述的判别图像亮度背景的装置。
虽然已经参考目前考虑到的实施例描述了本发明，但是应该理解本发明不限于所公开的实施例。相反，本发明旨在涵盖所附权利要求的精神和范围之内所包括的各种修改和等同布置。以下权利要求的范围符合最广泛解释，以便包含每个这样的修改及等同结构和功能。

Claims (21)

  1. 一种判别图像亮度背景的方法，包括下面的步骤：
    接收待判别的图像信息，所述图像信息包含了每个像素中各个子像素的灰阶值；
    将所述图像信息中以第s行第t列像素为中心的第s±m行第t±n列像素内特定子像素的灰阶值构成数组，并且将此数组按序排列，其中s，m，t，n是自然数；
    若数组内较大的N个特定子像素的灰阶值均大于给定值的灰阶值，并且方差小于等于特定阈值，则判定所述第s±m行和第t±n列内特定子像素为高亮度背景区域，否则判定所述第s±m行和第t±n列内特定子像素为非高亮度背景区域。
  2. 根据权利要求1所述的判别图像亮度背景的方法，其特征在于，所述方差小于等于50。
  3. 根据权利要求2所述的判别图像亮度背景的方法，其特征在于，所述方差小于等于40。
  4. 根据权利要求2所述的判别图像亮度背景的方法，其特征在于，大于给定值的灰阶值的特定子像素的个数N越多，判别条件越严苛。
  5. 根据权利要求2所述的判别图像亮度背景的方法，其特征在于，所述给定值的灰阶值越大，判别条件越严苛。
  6. 根据权利要求2所述的判别图像亮度背景的方法，其特征在于，所述方差越小，判别条件越严苛。
  7. 根据权利要求4-6中任一项所述的判别图像亮度背景的方法，其特征在于，所述给定值的灰阶值为大于180。
  8. 根据权利要求7所述的判别图像亮度背景的方法，其特征在于，所述给定值的灰阶值为大于200。
  9. 根据权利要求7所述的判别图像亮度背景的方法，其特征在于，以第s行第t列像素为中心的第s±m行和第t±n列像素内特定子像素的灰阶值构成的数组代表奇数行×奇数列个灰阶值。
  10. 根据权利要求9所述的判别图像亮度背景的方法，其特征在于，所述奇数行×奇数列个灰阶值是3行×5列或者5行×7列内的特定子像素的灰阶值。
  11. 根据权利要求10所述的判别图像亮度背景的方法，其特征在于，所述数组是按照降序排列的。
  12. 根据权利要求10所述的判别图像亮度背景的方法，其特征在于，所述数组是按照升序排列的。
  13. 根据权利要求10所述的判别图像亮度背景的方法，其特征在于，对于判定为非高亮度背景区域的特定子像素的灰阶值数组进行低通滤波。
  14. 根据权利要求1-6中任一项所述的判别图像亮度背景的方法，其特征在于，所述特定子像素是红色子像素、绿色子像素或者蓝色子像素。
  15. 一种判别图像亮度背景的装置，包括：
    接收单元，用于接收待判别的图像信息，所述图像信息包含了每个像素中各个子像素的灰阶值；
    存储单元，用于将所述图像信息中以第s行第t列像素为中心的第s±m行第t±n列像素内特定子像素的灰阶值构成数组，并且将此数组按序排列，其中s，m，t，n是自然数；
    判定单元，若数组内较大的N个特定子像素的灰阶值均大于给定值的灰阶值，并且方差小于等于特定阈值，则判定所述第s±m行和第t±n列内特定子像素为高亮度背景区域，否则判定所述第s±m行和第t±n列内特定子像素为非高亮度背景区域。
  16. 根据权利要求15所述的判别图像亮度背景的装置，其中所述方差小于等于50。
  17. 根据权利要求16所述的判别图像亮度背景的装置，其中所述方差小于等于40。
  18. 根据权利要求16所述的判别图像亮度背景的装置，其特征在于，大于给定值的灰阶值的特定子像素的个数N越多，判别条件越严苛。
  19. 根据权利要求16所述的判别图像亮度背景的装置，其特征在于，所述给定值的灰阶值越大，判别条件越严苛。
  20. 根据权利要求16所述的判别图像亮度背景的装置，其特征在于，所述方差越小，判别条件越严苛。
  21. 一种显示装置，包括使用权利要求1-14中任一项所述的判别 图像亮度背景的方法和/或权利要求15-20中任一项所述的判别图像亮度背景的装置。
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