WO2020107660A1 - Method for recognizing single-tone image - Google Patents

Abstract

The present invention provides a method for recognizing a single-tone image. The method for recognizing a single-tone image comprises: converting a plurality of rgb optical values corresponding to a plurality of pixels into an HSV color model; forming a statistical histogram according to a plurality of tone values in the HSV color model respectively corresponding to the plurality of pixels, the statistical histogram comprising a plurality of bars, and the plurality of bars respectively corresponding to the quantities of pixels located in different tone value intervals; and determining, according to the quantity of bars, in the statistical histogram, having the quantities of pixels greater than a preset quantity threshold, whether an image is a single-tone image. The method can effectively recognize a single-tone image.

Description

Method for identifying single-tone image Technical field

The present invention relates to the field of display technology, and in particular to a method for identifying single-tone images.

Background technique

Thin film transistor (Thin Film Transistor, TFT) is the main driving element in the current liquid crystal display device (Liquid Crystal Display) and active matrix driven organic electroluminescence display device (Active Matrix Organic Light-Emitting Diode, AMOLED), It is directly related to the display performance of the flat panel display device.

Most of the liquid crystal displays on the existing market are backlight type 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 infuse liquid crystal molecules between the thin film transistor array substrate (Thin Film Transistor Array Substrate, TFT Array Substrate) and the color filter (CF) substrate, and apply them separately on the two substrates The pixel voltage and the common voltage control the rotation direction of the liquid crystal molecules by the electric field formed between the pixel voltage and the common voltage, so as to transmit the light of the backlight module to generate a picture.

The existing OLED display device usually includes a substrate, an anode provided on the substrate, an organic light emitting layer provided on the anode, an electron transport layer provided on the organic light emitting layer, and a cathode provided on the electron transport layer. During operation, the hole from the anode and the electron from the cathode are emitted to the organic light-emitting layer, and these electrons and holes are combined to generate an excited electron-hole pair, and the excited electron-hole pair is output from the excited state to the ground state Achieve glow.

In the display industry, color temperature is an important parameter used to characterize the color characteristics of light. The lower the color temperature, the more reddish the light color, and conversely, the more blued the light color. The overall color temperature of the image can characterize the overall feeling of the image to the viewer. In the prior art, the image color temperature is obtained based on the correlated color temperature (CCT) and the color temperature partition. By converting the digital rgb value of the image, the digital rgb value is converted into the chromaticity coordinates of the processing pixel in the chromatogram, and the chromaticity coordinates are located according to the chromaticity coordinates. The color temperature is calculated for the area. For the existing method of acquiring image color temperature, for a large area of a single warm color tone image, the calculated color temperature value is often much warmer than the expected color, which greatly affects the calculation result. There is an urgent need for a method that can effectively identify a single tone image.

Summary of the invention

An object of the present invention is to provide a method for identifying a single-tone image, which can effectively identify a single-tone image.

To achieve the above object, the present invention provides a method for identifying a single-tone image, including the following steps:

Step S1: Provide image display data; the image includes a plurality of pixels, and the image display data includes a plurality of rgb optical values corresponding to the plurality of pixels; convert the plurality of rgb optical values into an HSV color model;

Step S2. Form a statistical histogram according to multiple tonal values corresponding to multiple pixels in the HSV color model respectively. The statistical histogram has multiple histogram bars, and the multiple histogram bars respectively correspond to The number of pixels;

Step S3. Determine whether the image is a single-tone image according to the number of histograms in the statistical histogram where the number of pixels is greater than a preset number threshold; when the number of pixels is greater than a preset number threshold, the number of histograms is 1 Or, when the number of histograms with a pixel number greater than a preset number threshold is 2, and the tone value intervals corresponding to the two histograms are adjacent to each other, the image is determined to be a single-tone image, otherwise, then Determine that the image is not a monotone image.

The size range of the tone value is 0-1, the number of the plurality of histogram bars is n, and the interval of the tone value corresponding to each histogram bar is

Where m is the m-th histogram, h _m is the tone value interval corresponding to the m-th histogram, n and m are both positive integers and n>=2, m>=1.

The preset number threshold is 8% of the total number of pixels in the image corresponding to the histogram.

The method for recognizing a single-tone image further includes step S4, selecting the tone value interval corresponding to the histogram with the largest number of pixels, and removing the saturation value of the histogram that is in the tone value interval and the saturation is greater than a preset saturation threshold For pixels whose brightness is less than a preset brightness threshold, the remaining multiple pixels are obtained;

Step S5: Calculate the color temperature values of the remaining pixels according to the image color temperature acquisition method to obtain the color temperature value of the single-tone image.

The specific steps of step S5 are:

Step S51: Establish a statistical table; the statistical table includes multiple reference color temperatures and multiple weights corresponding to the multiple reference color temperatures, respectively, the multiple reference color temperatures include a preset minimum color temperature, a preset maximum color temperature, and multiple Intermediate color temperature, multiple weights are 0; multiple intermediate color temperatures gradually increase, and are all greater than the minimum color temperature and less than the maximum color temperature;

Step S52, providing a chromatogram, dividing the color gamut space in the chromatogram into the first zone, the second zone, and the third zone connected in pairs; the boundary between the first zone and the second zone, the second zone, and the third zone The boundary line of the zone and the boundary line of the third zone and the first zone converge at a reference point. The boundary line of the first zone and the second zone coincides with the isochromatic temperature line corresponding to the maximum color temperature. The junction of the first zone and the third zone The line coincides with the equal color temperature line corresponding to the minimum color temperature, and the boundary between the second zone and the third zone is parallel to the ordinate axis of the chromatogram;

Step S53: Select one of the remaining pixels as the processing pixel; convert the rgb optical value of the processing pixel into the chromaticity coordinates of the processing pixel in the chromatogram;

Step S54: Determine the position of the chromaticity coordinates of the processing pixel in the color gamut space; if the chromaticity coordinates of the processing pixel are located in the first zone, then calculate the processing pixel's chromaticity coordinates and the preset pixel color temperature calculation formula Color temperature value, to determine whether the color temperature value of the processing pixel is one of multiple reference color temperatures, if so, increase the weight corresponding to the color temperature value of the processing pixel in the statistical table by 1, otherwise the color temperature value and 1 of the processing pixel are used as the reference color temperature And their corresponding weights are added to the statistics table; if the chromaticity coordinates of the processed pixel are in the second area, the connection between the point corresponding to the chromaticity coordinates of the processed pixel and the reference point and the The angle between the boundary lines and the preset first weight value calculation formula calculate the weight value of the processed pixel, and add the weight value to the weight corresponding to the maximum color temperature in the statistical table; if the chromaticity coordinates of the processed pixel are located in the third area , Then the weight value of the processing pixel is calculated according to the angle between the connection line between the point corresponding to the chromaticity coordinates of the processing pixel and the reference point and the boundary between the first area and the third area, and the preset second weight value calculation formula , And add the weight value to the weight corresponding to the minimum color temperature in the statistical table;

Step S55. Repeat steps S53 and S54 until the remaining multiple pixels all execute steps S53 and S54;

Step S56: Multiply each reference color temperature in the statistical table by the corresponding weight, and divide the sum of the products of multiple reference color temperatures and corresponding weights by the sum of the weights corresponding to multiple reference color temperatures to obtain the color temperature of the single-tone image value.

The plurality of rgb optical values are obtained from the plurality of rgb digital values corresponding to the plurality of pixels according to an optical value calculation formula, and the optical value calculation formula is:

Where R is the red optical value in the rgb optical value, G is the green optical value in the rgb optical value, B is the blue optical value in the rgb optical value, r is the red digital value in the rgb digital value, and g is rgb The green digital value in the digital value, b is the blue digital value in the rgb digital value,

Represents the value obtained by performing gamma transformation on r,

Represents the value obtained by performing gamma transformation on b,

Represents the value obtained by performing gamma transformation on g.

The specific process of converting the rgb optical value of the processing pixel to the chromaticity coordinates of the processing pixel in the chromatogram in the step S53 is as follows: calculating the tristimulus of the processing pixel according to the optical rgb value of the processing pixel and a preset tristimulus value calculation formula Value, calculate the chromaticity coordinates of the processed pixel in the chromatogram according to the tristimulus value of the processed pixel and the preset chromaticity coordinate calculation formula;

The preset formula for calculating the tristimulus value is:

Wherein, X is the red stimulus value in the tristimulus value, Y is the green stimulus value in the tristimulus value, Z is the blue stimulus value in the tristimulus value, and T is the preset conversion matrix;

The preset chromaticity coordinate formula is:

Where a is the horizontal coordinate of the chromaticity coordinate of the processing pixel in the chromatogram, and b is the vertical coordinate of the chromaticity coordinate of the processing pixel in the chromatogram.

The coordinates of the reference points where the boundary between the first zone and the second zone, the boundary between the second zone and the third zone, and the boundary between the third zone and the first zone in the chromatogram are (0.332, 0.1858); The preset calculation formula of the pixel color temperature value is: CT=-437*s ³ +3601*s ² -6861*s+5514.31, where CT is the pixel color temperature value,

The preset formula for calculating the first weight value is: γ ₁ =1-α ₁ /β ₁ , where γ ₁ is the weight value of the processing pixel when the chromaticity coordinates of the processing pixel are located in the second zone, and α ₁ is the processing The angle between the line connecting the point corresponding to the chromaticity coordinates of the pixel and the reference point and the boundary between the first and second regions, β ₁ is the boundary between the first and second regions and the second and second regions The angle between the boundary lines of the three districts;

The preset second weight value calculation formula is: γ ₂ =1-α ₂ /β ₂ , where γ ₂ is the weight value of the processing pixel when the chromaticity coordinates of the processing pixel are located in the third zone, and α ₂ is the processing The angle between the line between the point corresponding to the chromaticity coordinates of the pixel and the reference point and the boundary between the first and third regions, β ₂ is the boundary between the first and third regions and the second and third regions The angle between the boundaries of the three districts.

The chromatogram is a CIE1931 chromatogram; the preset minimum color temperature is 1000K; and the preset maximum color temperature is 15000K.

The invention also provides a method for identifying single-tone images, including the following steps:

Step S1: Provide image display data; the image includes a plurality of pixels, and the image display data includes a plurality of rgb optical values corresponding to the plurality of pixels; convert the plurality of rgb optical values into an HSV color model;

Step S2. Form a statistical histogram according to multiple tonal values corresponding to multiple pixels in the HSV color model respectively. The statistical histogram has multiple histogram bars, and the multiple histogram bars respectively correspond to The number of pixels;

Step S3. Determine whether the image is a single-tone image according to the number of histograms in the statistical histogram where the number of pixels is greater than a preset number threshold; when the number of pixels is greater than a preset number threshold, the number of histograms is 1 Or, when the number of histograms with a pixel number greater than a preset number threshold is 2, and the tone value intervals corresponding to the two histograms are adjacent to each other, the image is determined to be a single-tone image, otherwise, then Determine that the image is not a single-tone image;

Step S4: Select the tone value interval corresponding to the histogram with the largest number of pixels, and remove pixels in the histogram that are in the tone value interval and have a saturation greater than a preset saturation threshold or a brightness less than a preset brightness threshold To get the remaining pixels;

Step S5: Calculate the color temperature values of the remaining pixels according to the image color temperature acquisition method to obtain the color temperature value of the single-tone image;

The preset number threshold is 8% of the total number of pixels in the image corresponding to the histogram.

Beneficial effect of the present invention: The method for identifying single-tone images of the present invention converts multiple rgb optical values corresponding to multiple pixels into an HSV color model, and according to the multiple tone values corresponding to multiple pixels in the HSV color model, respectively Forming a statistical histogram, the statistical histogram has a plurality of histograms, the plurality of histograms respectively corresponding to the number of pixels in different tone value intervals, according to the statistical histogram, the number of pixels is greater than a preset number threshold The number of histograms to determine whether the image is a single-tone image can effectively identify a single-tone image.

BRIEF DESCRIPTION

In order to further understand the features and technical content of the present invention, please refer to the following detailed description and drawings of the present invention. However, the drawings are provided for reference and explanation only, and are not intended to limit the present invention.

In the drawings,

FIG. 1 is a flowchart of a method for identifying single-tone images of the present invention;

2 and 3 are schematic diagrams of statistical histograms of the method for identifying single-tone images of the present invention;

4 is a schematic diagram of a chromatogram of the method for identifying a single-tone image of the present invention.

detailed description

In order to further elaborate on the technical means adopted by the present invention and its effects, the following will be described in detail with reference to the preferred embodiments of the present invention and the accompanying drawings.

Please refer to FIG. 1, the present invention provides a method for identifying a single-tone image, including the following steps:

Step S1: Provide display data of the image; the image includes a plurality of pixels, and the display data of the image includes a plurality of rgb optical values corresponding to the plurality of pixels; convert the plurality of rgb optical values to HSV (Hue Saturation Value) ) Color model;

Step S2. Please refer to FIG. 2 and FIG. 3, a statistical histogram is formed according to multiple Hue values corresponding to multiple pixels in the HSV color model, and the statistical histogram has multiple histogram bars. The histograms correspond to the number of pixels in different tonal value ranges respectively;

Step S3. Determine whether the image is a single-tone image according to the number of histograms in the statistical histogram where the number of pixels is greater than a preset number threshold; when the number of pixels is greater than a preset number threshold, the number of histograms is 1 Or, when the number of histograms with a pixel number greater than a preset number threshold is 2, and the tone value intervals corresponding to the two histograms are adjacent to each other, the image is determined to be a single-tone image, otherwise, then Determine that the image is not a monotone image.

It should be noted that the present invention converts multiple rgb optical values corresponding to multiple pixels into an HSV color model, and forms a statistical histogram according to multiple Hue values corresponding to multiple pixels in the HSV color model, The statistical histogram has multiple histogram bars, and the multiple histogram bars respectively correspond to the number of pixels located in different tone value intervals. According to the number of pixels in the statistical histogram, the number of pixels is greater than a preset number threshold To determine whether the image is a monotone image, it can effectively identify the monotone image.

Specifically, the size range of the tone value is 0-1, the number of the plurality of histogram bars is n, and the tone value interval corresponding to each histogram bar is

Where m is the m-th histogram, h _m is the tone value interval corresponding to the m-th histogram, n and m are both positive integers and n>=2, m>=1. For example, when the number of multiple histogram bars is 10, the tone value interval corresponding to the first histogram bar is 0<=h ₁ <0.1, and the tone value interval corresponding to the second histogram bar is 0.1<=h ₂ <0.2, By analogy, the hue value interval corresponding to the tenth histogram is 0.9<=h ₁₀ <1. Since the hue value in the HSV color model is a circular data, the hue value 1 is the hue value 0.

Further, the greater the number of histogram bars in the statistical histogram, the more intuitive the statistical data. Therefore, the number of multiple histogram bars of the present invention is greater than or equal to 10 to improve the accuracy of single-tone image recognition.

Specifically, the preset number threshold is that the number of pixels corresponding to the histogram takes up 8% of the total number of pixels in the image, that is, according to the statistical histogram, the number of pixels in the present invention is greater than 8% of the total number of pixels The number of bars determines whether the image is a monotone image.

Specifically, the plurality of rgb optical values are obtained from the plurality of rgb digital values respectively corresponding to the plurality of pixels according to an optical value calculation formula, and the optical value calculation formula is:

Where R is the red optical value in the rgb optical value, G is the green optical value in the rgb optical value, B is the blue optical value in the rgb optical value, r is the red digital value in the rgb digital value, and g is rgb The green digital value in the digital value, b is the blue digital value in the rgb digital value,

Represents the value obtained by performing gamma transformation on r,

Represents the value obtained by performing gamma transformation on b,

Represents the value obtained by performing gamma transformation on g.

Specifically, the color temperature value of the single-tone image needs to be acquired later, so the present invention further includes step S4, selecting the tone value interval corresponding to the histogram with the largest number of pixels, and removing the saturation and saturation of the histogram located in the tone value interval For pixels that are greater than a preset saturation threshold or whose brightness is less than a preset brightness threshold, the remaining multiple pixels are obtained;

Step S5: Calculate the color temperature values of the remaining pixels according to the image color temperature acquisition method to obtain the color temperature value of the single-tone image. That is, the invention removes the noise pixels of the color temperature value of the single-tone image, so that the calculation of the color temperature value of the single-tone image is more accurate.

Further, the specific steps of step S5 are:

Step S51: Establish a statistical table; the statistical table includes multiple reference color temperatures and multiple weights corresponding to the multiple reference color temperatures, respectively, the multiple reference color temperatures include a preset minimum color temperature, a preset maximum color temperature, and multiple Intermediate color temperature, multiple weights are all 0; multiple intermediate color temperatures gradually increase, and are all greater than the minimum color temperature and less than the maximum color temperature.

Specifically, the preset minimum color temperature is 1000K; the preset maximum color temperature is 15000K.

Specifically, the plurality of intermediate color temperatures may be set at equal intervals between the minimum color temperature and the maximum color temperature.

Further, the statistical table may be a statistical table as shown in Table 1 below. Among multiple intermediate color temperatures, the difference between each two adjacent color temperatures is 500K, and the difference between the minimum intermediate color temperature and the minimum color temperature is 500K. The difference between the maximum color temperature and the maximum intermediate color temperature is 500K.

Table 1. Statistics

Reference color temperature	1000K	1500K	...	15000K
Weights	0	0	...	0

Step S52. Please refer to FIG. 4 to provide a chromatogram, and to divide the color gamut space in the chromatogram into a first area A, a second area B, and a third area C connected in pairs. The boundary between the first area A and the second area B, the boundary between the second area B and the third area C, and the boundary between the third area C and the first area A converge at a reference point O, the first area A and The boundary line of the second zone B coincides with the isochromatic temperature line corresponding to the maximum color temperature, the boundary line of the first zone A and the third zone C coincides with the isochromatic temperature line corresponding to the minimum color temperature, and the boundary of the second zone B and the third zone C The line is parallel to the ordinate axis of the chromatogram.

Specifically, the chromatogram is a CIE1931 chromatogram.

Specifically, all the isochromatic temperature lines in the chromatogram converge on this reference point O.

Specifically, the coordinates of the reference point O are (0.332, 0.1858).

Step S53: Select one of the remaining pixels as the processing pixel; convert the rgb optical value of the processing pixel into the chromaticity coordinates of the processing pixel in the chromatogram.

Specifically, the specific process of converting the rgb optical value of the processing pixel into the chromaticity coordinates of the processing pixel in the chromatogram in the step S53 is as follows: calculating the processing pixel according to the optical rgb value of the processing pixel and a preset tristimulus value calculation formula The tristimulus value of the pixel is calculated according to the tristimulus value of the processed pixel and the preset chromaticity coordinate calculation formula;

The preset formula for calculating the tristimulus value is:

Wherein, X is the red stimulus value in the tristimulus value, Y is the green stimulus value in the tristimulus value, Z is the blue stimulus value in the tristimulus value, and T is the preset conversion matrix;

The preset chromaticity coordinate formula is:

Where a is the horizontal coordinate of the chromaticity coordinate of the processing pixel in the chromatogram, and b is the vertical coordinate of the chromaticity coordinate of the processing pixel in the chromatogram.

Step S54: Determine the position of the chromaticity coordinates of the processing pixel in the color gamut space. If the chromaticity coordinates of the processing pixel are located in the first area A, for example, at point P(A) in FIG. 2, then the color temperature value of the processing pixel is calculated according to the chromaticity coordinates of the processing pixel and the preset calculation formula of the pixel color temperature value Whether the color temperature value of a pixel is one of multiple reference color temperatures, if it is, the weight corresponding to the color temperature value of the processed pixel in the statistical table is increased by 1, otherwise the color temperature value and 1 of the processed pixel are used as the reference color temperature and their corresponding weights, respectively Add to the statistics table. If the chromaticity coordinates of the processing pixel are located in the second area B, for example, at the point P(B) in FIG. 2, the line between this point and the reference point O and the boundary line between the first area A and the second area B The angle of is α ₁ , and the angle between the boundary between the first area A and the second area B and the boundary between the second area B and the third area C is β ₁ , which corresponds to the chromaticity coordinates of the processed pixel The angle between the line connecting the reference point and the reference point and the boundary between the first area A and the second area B is α ₁ , the preset first weight value calculation formula calculates the weight value of the processed pixel, and the weight The value is added to the weight corresponding to the maximum color temperature of 15000K in the statistical table. If the chromaticity coordinates of the processed pixel are located in the third area C, for example, at the point P(C) in FIG. 3, the line between this point and the reference point O and the boundary between the first area A and the third area C The angle is α ₂ , and the angle between the boundary between the first area A and the third area C and the boundary between the second area B and the third area C is β ₂ , which corresponds to the chromaticity coordinates of the processed pixel The angle between the line connecting the reference point and the reference point and the boundary between the first area A and the third area C, that is, α ₂ , the preset second weight value calculation formula calculates the weight value of the processed pixel, and the weight The value is added to the weight corresponding to the minimum color temperature of 1000K in the statistical table.

Specifically, the preset calculation formula of the pixel color temperature value is: CT=-437*s ³ +3601*s ² -6861*s+5514.31, where CT is the pixel color temperature value,

Specifically, the preset first weight value calculation formula is: γ ₁ =1-α ₁ /β ₁ , where γ ₁ is the weight value of the processing pixel when the chromaticity coordinates of the processing pixel are located in the second area B, α ₁ is the angle between the line connecting the point corresponding to the chromaticity coordinates of the processing pixel and the reference point and the boundary between the first area A and the second area B, β ₁ is the angle between the first area A and the second area B The angle between the boundary line and the boundary line between the second zone B and the third zone C;

Specifically, the preset calculation formula of the second weight value is: γ ₂ =1-α ₂ /β ₂ , where γ ₂ is the weight value of the processing pixel when the chromaticity coordinates of the processing pixel are located in the third area C, α ₂ is the angle between the line connecting the point corresponding to the chromaticity coordinates of the processing pixel and the reference point and the boundary between the first area A and the third area C, β ₂ is the angle between the first area A and the third area C The angle between the boundary line and the boundary line between the second area B and the third area C.

Step S55. Repeat steps S53 and S54 until the remaining multiple pixels all execute steps S53 and S54;

Step S56: Multiply each reference color temperature in the statistical table by the corresponding weight, and divide the sum of the products of multiple reference color temperatures and corresponding weights by the sum of the weights corresponding to multiple reference color temperatures to obtain the color temperature of the single-tone image value.

In summary, the method for identifying single-tone images of the present invention is formed by converting multiple RGB optical values corresponding to multiple pixels into an HSV color model, based on multiple tone values corresponding to multiple pixels in the HSV color model Statistical histogram, the statistical histogram has multiple histogram bars, the multiple histogram bars respectively correspond to the number of pixels located in different tone value intervals, according to the number of pixels in the statistical histogram is greater than a preset number threshold The number of histograms to determine whether the image is a single-tone image can effectively identify a single-tone image.

As mentioned above, those of ordinary skill in the art can make various other corresponding changes and modifications according to the technical solutions and technical concepts of the present invention, and all such changes and modifications should fall within the protection scope of the claims of the present invention. .

Claims (15)

1. A method for identifying a single-tone image includes the following steps:

   Step S1: Provide image display data; the image includes a plurality of pixels, and the image display data includes a plurality of rgb optical values corresponding to the plurality of pixels; convert the plurality of rgb optical values into an HSV color model;

   Step S2. Form a statistical histogram according to multiple tonal values corresponding to multiple pixels in the HSV color model respectively. The statistical histogram has multiple histogram bars, and the multiple histogram bars respectively correspond to The number of pixels;

   Step S3. Determine whether the image is a single-tone image according to the number of histograms in the statistical histogram where the number of pixels is greater than a preset number threshold; when the number of pixels is greater than a preset number threshold, the number of histograms is 1 Or, when the number of histograms with a pixel number greater than a preset number threshold is 2, and the tone value intervals corresponding to the two histograms are adjacent to each other, the image is determined to be a single-tone image, otherwise, then Determine that the image is not a monotone image.
2. The method for identifying a single-tone image according to claim 1, wherein the size range of the tone value is 0-1, the number of the plurality of histogram bars is n, and the tone value interval corresponding to each histogram bar is

   

   Where m is the m-th histogram, h _m is the tone value interval corresponding to the m-th histogram, n and m are both positive integers and n>=2, m>=1.
3. The method for identifying a single-tone image according to claim 1, wherein the preset number threshold is 8% of the total number of pixels in the image corresponding to the histogram.
4. The method for identifying a single-tone image according to claim 1, further comprising step S4, selecting a tone value interval corresponding to the histogram with the largest number of pixels, and removing the histogram located in the tone value interval and having a saturation greater than a preset The pixels with the set saturation threshold or brightness less than a preset brightness threshold get the remaining pixels;

   Step S5: Calculate the color temperature values of the remaining pixels according to the image color temperature acquisition method to obtain the color temperature value of the single-tone image.
5. The method for identifying a single-tone image according to claim 4, wherein the specific steps of step S5 are:

   Step S51: Establish a statistical table; the statistical table includes multiple reference color temperatures and multiple weights corresponding to the multiple reference color temperatures, respectively, the multiple reference color temperatures include a preset minimum color temperature, a preset maximum color temperature, and multiple Intermediate color temperature, multiple weights are 0; multiple intermediate color temperatures gradually increase, and are all greater than the minimum color temperature and less than the maximum color temperature;

   Step S52, providing a chromatogram, dividing the color gamut space in the chromatogram into the first zone, the second zone, and the third zone connected in pairs; the boundary between the first zone and the second zone, the second zone, and the third zone The boundary line of the zone and the boundary line of the third zone and the first zone converge at a reference point. The boundary line of the first zone and the second zone coincides with the isochromatic temperature line corresponding to the maximum color temperature. The junction of the first zone and the third zone The line coincides with the equal color temperature line corresponding to the minimum color temperature, and the boundary between the second zone and the third zone is parallel to the ordinate axis of the chromatogram;

   Step S53: Select one of the remaining pixels as the processing pixel; convert the rgb optical value of the processing pixel into the chromaticity coordinates of the processing pixel in the chromatogram;

   Step S54: Determine the position of the chromaticity coordinates of the processing pixel in the color gamut space; if the chromaticity coordinates of the processing pixel are located in the first zone, then calculate the processing pixel's chromaticity coordinates according to the processing pixel and the preset pixel color temperature calculation formula Color temperature value, to determine whether the color temperature value of the processing pixel is one of multiple reference color temperatures, if it is, increase the weight corresponding to the color temperature value of the processing pixel in the statistical table by 1, otherwise the color temperature value and 1 of the processing pixel are used as the reference color temperature, respectively And their corresponding weights are added to the statistics table; if the chromaticity coordinates of the processed pixel are in the second area, the connection between the point corresponding to the chromaticity coordinates of the processed pixel and the reference point and the The angle between the boundary lines and the preset first weight value calculation formula calculate the weight value of the processed pixel, and add the weight value to the weight corresponding to the maximum color temperature in the statistical table; if the chromaticity coordinates of the processed pixel are located in the third area , Then the weight value of the processing pixel is calculated according to the angle between the connection line between the point corresponding to the chromaticity coordinates of the processing pixel and the reference point and the boundary between the first area and the third area, and the preset second weight value calculation formula , And add the weight value to the weight corresponding to the minimum color temperature in the statistical table;

   Step S55. Repeat steps S53 and S54 until the remaining multiple pixels all execute steps S53 and S54;

   Step S56: Multiply each reference color temperature in the statistical table by the corresponding weight, and divide the sum of the products of multiple reference color temperatures and corresponding weights by the sum of the weights corresponding to multiple reference color temperatures to obtain the color temperature of the single-tone image value.
6. The method for identifying a single-tone image according to claim 5, wherein the plurality of rgb optical values are obtained from a plurality of rgb digital values corresponding to the plurality of pixels according to an optical value calculation formula, the optical value calculation formula is:

   

   Where R is the red optical value in the rgb optical value, G is the green optical value in the rgb optical value, B is the blue optical value in the rgb optical value, r is the red digital value in the rgb digital value, and g is rgb The green digital value in the digital value, b is the blue digital value in the rgb digital value,

   

   Represents the value obtained by performing gamma transformation on r,

   

   Represents the value obtained by performing gamma transformation on b,

   

   Represents the value obtained by performing gamma transformation on g.
7. The method for identifying a single-tone image according to claim 6, wherein the specific process of converting the rgb optical value of the processing pixel into the chromaticity coordinates of the processing pixel in the chromatogram in step S53 is: according to the optical rgb of the processing pixel The value and the preset tristimulus value calculation formula calculate the tristimulus value of the processing pixel, and the chromaticity coordinate of the processing pixel in the chromatogram is calculated according to the tristimulus value of the processing pixel and the preset chromaticity coordinate calculation formula;

   The preset formula for calculating the tristimulus value is:

   

   Wherein, X is the red stimulus value in the tristimulus value, Y is the green stimulus value in the tristimulus value, Z is the blue stimulus value in the tristimulus value, and T is the preset conversion matrix;

   The preset chromaticity coordinate formula is:

   

   Where a is the horizontal coordinate of the chromaticity coordinate of the processing pixel in the chromatogram, and b is the vertical coordinate of the chromaticity coordinate of the processing pixel in the chromatogram.
8. The method for identifying a single-tone image according to claim 7, wherein the boundary between the first and second regions, the boundary between the second and third regions, and the third and first regions in the chromatogram The coordinate of the reference point where the boundary line converges is (0.332, 0.1858); the calculation formula of the preset pixel color temperature value is: CT=-437*s ³ +3601*s ² -6861*s+5514.31, where, CT Is the pixel color temperature value,

   
9. The method for identifying a single-tone image according to claim 5, wherein the preset formula for calculating the first weight value is: γ ₁ =1-α ₁ /β ₁ , where γ ₁ is the chromaticity of the processed pixel The weight value of the processing pixel when the coordinates are in the second zone, α ₁ is the angle between the line connecting the point corresponding to the chromaticity coordinates of the processing pixel and the reference point and the boundary between the first zone and the second zone, β ₁ is The angle between the boundary between the first and second areas and the boundary between the second and third areas;

   The preset second weight value calculation formula is: γ ₂ =1-α ₂ /β ₂ , where γ ₂ is the weight value of the processing pixel when the chromaticity coordinates of the processing pixel are located in the third zone, and α ₂ is the processing The angle between the line between the point corresponding to the chromaticity coordinates of the pixel and the reference point and the boundary between the first and third regions, β ₂ is the boundary between the first and third regions and the second and third regions The angle between the boundaries of the three districts.
10. The method for identifying a single-tone image according to claim 5, wherein the chromatogram is a CIE1931 chromatogram; the preset minimum color temperature is 1000K; and the preset maximum color temperature is 15000K.
11. A method for identifying a single-tone image includes the following steps:

    Step S1: Provide image display data; the image includes a plurality of pixels, and the image display data includes a plurality of rgb optical values corresponding to the plurality of pixels; convert the plurality of rgb optical values into an HSV color model;

    Step S2. Form a statistical histogram according to multiple tonal values corresponding to multiple pixels in the HSV color model respectively. The statistical histogram has multiple histogram bars, and the multiple histogram bars respectively correspond to The number of pixels;

    Step S3. Determine whether the image is a single-tone image according to the number of histograms in the statistical histogram where the number of pixels is greater than a preset number threshold; when the number of pixels is greater than a preset number threshold, the number of histograms is 1 Or, when the number of histograms with a pixel number greater than a preset number threshold is 2, and the tone value intervals corresponding to the two histograms are adjacent to each other, the image is determined to be a single-tone image, otherwise, then Determine that the image is not a single-tone image;

    Step S4: Select the tone value interval corresponding to the histogram with the largest number of pixels, and remove pixels in the histogram that are in the tone value interval and have a saturation greater than a preset saturation threshold or a brightness less than a preset brightness threshold To get the remaining pixels;

    Step S5: Calculate the color temperature values of the remaining pixels according to the image color temperature acquisition method to obtain the color temperature value of the single-tone image;

    Wherein, the preset number threshold is 8% of the total number of pixels in the image corresponding to the histogram.
12. The method for identifying a single-tone image according to claim 11, wherein the size range of the tone value is 0-1, the number of the plurality of histogram bars is n, and the tone value interval corresponding to each histogram bar is

    

    Where m is the m-th histogram, h _m is the tone value interval corresponding to the m-th histogram, n and m are both positive integers and n>=2, m>=1.
13. The method for identifying a single-tone image according to claim 11, wherein the specific steps of step S5 are:

    Step S51: Establish a statistical table; the statistical table includes multiple reference color temperatures and multiple weights corresponding to the multiple reference color temperatures, respectively, the multiple reference color temperatures include a preset minimum color temperature, a preset maximum color temperature, and multiple Intermediate color temperature, multiple weights are 0; multiple intermediate color temperatures gradually increase, and are all greater than the minimum color temperature and less than the maximum color temperature;

    Step S52, providing a chromatogram, dividing the color gamut space in the chromatogram into the first zone, the second zone, and the third zone connected in pairs; the boundary between the first zone and the second zone, the second zone, and the third zone The boundary line of the zone and the boundary line of the third zone and the first zone converge at a reference point. The boundary line of the first zone and the second zone coincides with the isochromatic temperature line corresponding to the maximum color temperature. The junction of the first zone and the third zone The line coincides with the equal color temperature line corresponding to the minimum color temperature, and the boundary between the second zone and the third zone is parallel to the ordinate axis of the chromatogram;

    Step S53: Select one of the remaining pixels as the processing pixel; convert the rgb optical value of the processing pixel into the chromaticity coordinates of the processing pixel in the chromatogram;

    Step S54: Determine the position of the chromaticity coordinates of the processing pixel in the color gamut space; if the chromaticity coordinates of the processing pixel are located in the first zone, then calculate the processing pixel's chromaticity coordinates according to the processing pixel and the preset pixel color temperature calculation formula Color temperature value, to determine whether the color temperature value of the processing pixel is one of multiple reference color temperatures, if it is, increase the weight corresponding to the color temperature value of the processing pixel in the statistical table by 1, otherwise the color temperature value and 1 of the processing pixel are used as the reference color temperature, respectively And their corresponding weights are added to the statistics table; if the chromaticity coordinates of the processed pixel are in the second area, the connection between the point corresponding to the chromaticity coordinates of the processed pixel and the reference point and the The angle between the boundary lines and the preset first weight value calculation formula calculate the weight value of the processed pixel, and add the weight value to the weight corresponding to the maximum color temperature in the statistical table; if the chromaticity coordinates of the processed pixel are located in the third area , Then the weight value of the processing pixel is calculated according to the angle between the connection line between the point corresponding to the chromaticity coordinates of the processing pixel and the reference point and the boundary between the first area and the third area, and the preset second weight value calculation formula , And add the weight value to the weight corresponding to the minimum color temperature in the statistical table;

    Step S55. Repeat steps S53 and S54 until the remaining multiple pixels all execute steps S53 and S54;

    Step S56: Multiply each reference color temperature in the statistical table by the corresponding weight, and divide the sum of the products of multiple reference color temperatures and corresponding weights by the sum of the weights corresponding to multiple reference color temperatures to obtain the color temperature of the single-tone image value.
14. The method for identifying a single-tone image according to claim 13, wherein the plurality of rgb optical values are obtained from a plurality of rgb digital values respectively corresponding to the plurality of pixels according to an optical value calculation formula, and the optical value calculation formula is:

    

    Where R is the red optical value in the rgb optical value, G is the green optical value in the rgb optical value, B is the blue optical value in the rgb optical value, r is the red digital value in the rgb digital value, and g is rgb The green digital value in the digital value, b is the blue digital value in the rgb digital value,

    

    Represents the value obtained by performing gamma transformation on r,

    

    Represents the value obtained by performing gamma transformation on b,

    

    Represents the value obtained by performing gamma transformation on g.
15. The method of identifying a single-tone image according to claim 14, wherein the specific process of converting the rgb optical value of the processing pixel into the chromaticity coordinates of the processing pixel in the chromatogram in the step S53 is: according to the optical rgb of the processing pixel The value and the preset tristimulus value calculation formula calculate the tristimulus value of the processing pixel, and the chromaticity coordinate of the processing pixel in the chromatogram is calculated according to the tristimulus value of the processing pixel and the preset chromaticity coordinate calculation formula;

    The preset formula for calculating the tristimulus value is:

    

    Wherein, X is the red stimulus value in the tristimulus value, Y is the green stimulus value in the tristimulus value, Z is the blue stimulus value in the tristimulus value, and T is the preset conversion matrix;

    The preset chromaticity coordinate formula is:

    

    Where a is the horizontal coordinate of the chromaticity coordinate of the processing pixel in the chromatogram, and b is the vertical coordinate of the chromaticity coordinate of the processing pixel in the chromatogram.

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