CN117873415A - Image conversion method, device, equipment, medium and program product - Google Patents
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Abstract
The present application relates to an image conversion method, apparatus, device, medium, and program product, the image conversion method including: obtaining initial RGB image data by linearly resampling the acquired Pentille image; determining a pixel local area and a display color to which each pixel position belongs based on the initial RGB image data; if the pixel local area belongs to a slit area of the image and the display color belongs to a preset target color to be processed, determining a pixel point corresponding to the pixel position as a pixel point to be processed; and carrying out image enhancement by adopting green G channel information of the pixel points to be processed based on the initial RGB image data to obtain an RGB image corresponding to the Pentille image, thereby reducing the pseudo color of the generated RGB image and solving the pseudo color problem of the generated RGB image from the Pentille image.
Description
Technical Field
The present invention relates to the field of image processing, and in particular, to an image conversion method, apparatus, device, medium, and program product.
Background
The Pentile array image is generated along with the generation of an Organic Light-Emitting Diode (OLED) display material. The conventional Red (Red, R), green (Green, G) and Blue (B) arrangement images have been used in liquid crystal displays, the liquid crystal is passively illuminated by a backlight, and the RGB image is embodied on the display in the form of a filter, which is relatively simple to manufacture, and the cost of manufacturing a high-density RGB color band does not increase greatly. However, the RGB arrangement image of the OLED is made of red, green and blue light-emitting organic materials, so that the resolution of the display used at present is high, which requires small and high-density integration of each light-emitting material, and increases the process difficulty and the cost. By adopting the Pentille arrangement image, only two materials are arranged on each display unit, and the material area is larger, so that the process difficulty is reduced, and the cost is also reduced.
In the Pentile-array image, the Pentile-array images of different manufacturers are different in Pixel distribution form, and the Pentile-array images of different distribution forms can improve the yield of the OLED screen by reducing the number of sub-pixels per Pixel (Pixel), but the resolution of the image is sacrificed, and particularly, the sub-pixels of three channels of the RGB image in the Pentile-array format are not regularly arranged any more, which results in the fact that when the RGB display screen receives the Pentile image, the image cannot be converted into the RGB image from the Pentile image.
At present, a new RGB image is obtained mainly by resampling a Pentile image and using a linear filter. However, when the pixel value of the boundary region is suddenly changed, the conventional linear filter method cannot cope with the situation that the generated RGB data is not aligned, and the generated RGB data may have a problem of pseudo color.
Disclosure of Invention
The application provides an image conversion method, an image conversion device, an image conversion medium and a program product, so as to solve the problem of pseudo color of RGB images generated from Pentille images.
In a first aspect, the present application provides an image conversion method, including:
obtaining initial RGB image data by linearly resampling the acquired Pentille image;
determining a pixel local area and a display color to which each pixel position belongs based on the initial RGB image data;
if the pixel local area belongs to a slit area of the image and the display color belongs to a preset target color to be processed, determining a pixel point corresponding to the pixel position as a pixel point to be processed;
and carrying out image enhancement by adopting green G channel information of the pixel points to be processed based on the initial RGB image data to obtain an RGB image corresponding to the Pentille image.
Optionally, the initial RGB image data includes RGB three-channel data, and determining, based on the initial RGB image data, a pixel local area and a display color to which each pixel position belongs includes:
generating an initial RGB image by adopting the RGB three-channel data;
traversing and detecting each pixel in the initial RGB image to obtain the pixel position of each pixel and the local area pixel information corresponding to each pixel position;
for each pixel position, determining a local area direction corresponding to the pixel position and a display color corresponding to the pixel position by adopting the local area pixel information;
and determining the pixel position corresponding to the local area direction as the edge direction as an edge pixel position, and determining the pixel local area to which the edge pixel position belongs as a slit area.
Optionally, the local area pixel information includes an image pixel of a local area of a pixel to which the pixel position belongs, and the determining, by using the local area pixel information, a local area direction corresponding to the pixel position includes:
for each pixel position, convoluting the image pixels of the pixel local area with a preset direction judgment operator to obtain a convolution result, wherein the convolution result comprises detection values corresponding to all detection directions;
Selecting the largest detection value from the convolution result;
and determining the detection direction corresponding to the maximum detection value as the local area direction.
Optionally, after determining the local area direction corresponding to the pixel position by using the local area pixel information, the method further includes:
judging whether the local area direction is an edge direction or not;
if the direction of the local area is the edge direction, determining a second-order gradient value of a G channel by adopting green G channel data of the pixel local area;
and if the absolute value of the second-order gradient value is larger than a preset gradient threshold value, the step of determining the pixel position corresponding to the local area direction as the edge pixel position is executed.
Optionally, the local area pixel information includes an image pixel of a local area of a pixel to which the pixel position belongs, and the determining, for each pixel position, a local area direction corresponding to the pixel position and a display color corresponding to the pixel position by using the local area pixel information includes:
determining the local area direction corresponding to each pixel position by adopting the local area pixel information corresponding to each pixel position;
Judging whether the local area direction is an edge direction or not according to each pixel position;
and if the local area direction is the edge direction, determining the display color by using the image pixels of the pixel local area.
Optionally, based on the initial RGB image data, performing image enhancement by using green G channel information of the pixel to be processed to obtain an RGB image corresponding to the Pentile image, including:
extracting green G channel information and channel information to be enhanced of the pixel points to be processed from the initial RGB image data;
correcting the channel information to be enhanced by adopting the green G channel information to obtain corrected image information;
and generating an RGB image corresponding to the Pentille image by combining the initial RGB image data by utilizing the corrected image information.
Optionally, the channel information to be enhanced includes a pixel value of a channel to be enhanced, the channel to be enhanced includes a red R channel and a blue B channel, and the modifying the channel information to be enhanced by using the green G channel information to obtain modified image information includes:
determining second derivative information of the green G channel by using the green G channel information;
Comparing the pixel value with a channel pixel average value corresponding to a target pixel area for each channel to be enhanced, wherein the target pixel area is a pixel area to which the pixel point to be processed belongs;
if the pixel value is larger than the average value of the channel pixels, the pixel value is enhanced by utilizing the maximum pixel value of the channel to be enhanced and combining the second derivative information, so as to obtain a pixel enhancement value;
if the pixel value is smaller than the average value of the channel pixels, the pixel value is reduced by utilizing the minimum pixel value of the channel to be enhanced and combining the second derivative information, so as to obtain a pixel reduction value;
the pixel enhancement value and the pixel reduction value are determined as the modified image information.
In a second aspect, the present application provides an image conversion apparatus including:
the linear resampling module is used for obtaining initial RGB image data by linearly resampling the acquired Pentille image;
a local area and color determining module, configured to determine, based on the initial RGB image data, a local area of a pixel and a display color to which each pixel position belongs;
a pixel point to be processed module, configured to determine a pixel point corresponding to the pixel position as a pixel point to be processed if the pixel local area belongs to a slit area of an image and the display color belongs to a preset target color to be processed;
And the image enhancement module is used for carrying out image enhancement by adopting the green G channel information of the pixel points to be processed based on the initial RGB image data to obtain an RGB image corresponding to the Pentille image.
In a third aspect, the present application provides an image conversion apparatus including: the device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;
a memory for storing a computer program;
a processor for implementing the steps of the image conversion method according to any one of the first aspects when executing a program stored on a memory.
In a fourth aspect, the present application also provides a computer storage medium storing computer executable instructions for performing the steps of the image conversion method according to any one of the first aspects.
In a fifth aspect, the present application also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of the image conversion method according to any of the first aspects.
According to the embodiment of the application, the obtained Pentille image is subjected to linear resampling to obtain initial RGB image data, and then the local pixel area and the display color of each pixel position are determined based on the initial RGB image data; if the pixel local area belongs to a slit area of an image and the display color belongs to a preset target color to be processed, determining a pixel point corresponding to the pixel position as the pixel point to be processed, so that image enhancement can be performed by adopting green G channel information of the pixel point to be processed based on the initial RGB image data to obtain an RGB image corresponding to the Pentille image, the pseudo color of the RGB image can be effectively reduced, and the problem of pseudo color of the RGB image generated from the Pentille image is solved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to a person skilled in the art that other drawings can be obtained from these drawings without inventive effort.
One or more embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements, and in which the figures of the drawings are not to be taken in a limiting sense, unless otherwise indicated.
Fig. 1 is a schematic flow chart of steps of an image conversion method according to an embodiment of the present application;
fig. 2 is a schematic layout diagram of a Pentile image according to an embodiment of the present application;
FIG. 3 is a schematic diagram of R channel data sampled with the same number of points as G in an example of the present application;
FIG. 4 is a schematic diagram of R channel pixel values at RX using R0 and R1 in an example of the present application;
FIG. 5 is a schematic diagram of an image with the same number of pixels as G in the horizontal direction R, B according to an example of the present application;
FIG. 6 is a schematic diagram of calculating R values at the same positions as G by linear interpolation in an example of the present application;
FIG. 7 is a schematic diagram of an initial RGB image arrangement according to an example of the present application;
FIG. 8 is a schematic diagram of a pixel local area according to an example of the present application;
fig. 9 is a schematic diagram of dot multiplication between 25 pixel values provided in an example of the present application and a preset direction judgment operator K1;
FIG. 10 is a schematic diagram of a convolution kernel provided by an example of the present application;
FIG. 11 is a schematic diagram of G-channel data according to an example of the present application;
FIG. 12 is a schematic diagram of a point multiplication of G-channel data with a convolution kernel according to an example of the present application;
fig. 13 is a block diagram of an image conversion apparatus according to an embodiment of the present application;
fig. 14 is a schematic structural diagram of an image conversion apparatus according to an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present application based on the embodiments herein.
The following disclosure provides many different embodiments, or examples, for implementing different structures of the invention. In order to simplify the present disclosure, components and arrangements of specific examples are described below. They are, of course, merely examples and are not intended to limit the invention. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed.
Unlike conventional RGB-arrayed images, the single pixels of the Pentile-arrayed image are different, one being red-green and one being blue-green. Only three primary colors can form all colors, but two colors cannot form all colors, so that when an image is actually displayed, one pixel point of a Pentile array image can "borrow" to form three primary colors by using the other color of the adjacent pixel point, for example, each pixel and the adjacent pixel share a sub-pixel of the color which is not possessed by the pixel in the horizontal direction, and white display is achieved jointly.
In order to solve the problem of pseudo color of RGB images generated from Pentile images in the prior art, the application provides an image conversion method, an image conversion device, image conversion equipment, an image conversion medium and a program product, which can effectively reduce the pseudo color after the RGB images are restored from the Pentile images and realize the pseudo color elimination effect of the RGB images generated from the Pentile.
The RGB image refers to an RGB arrangement image, that is, an RGB image refers to a full color image arranged in an RGB format. The Pentile image refers to a Pentile arrangement image, and may be, for example, a Pentile image arranged in an RGBG format, and this embodiment limits this step.
Fig. 1 is a schematic step diagram of an image conversion method according to an embodiment of the present application. As shown in fig. 1, the image conversion method provided in the embodiment of the present application may include the following steps:
step 110, obtaining initial RGB image data by linearly resampling the obtained Pentille image;
in this step, a Pentile image, such as an input Pentile image, may be acquired, and the acquired Pentile image may be linearly resampled to obtain RGB three-channel data sampled at the same location, and then the RGB three-channel data sampled at the same location may be determined as initial RGB image data, so that an initial RGB image may be generated using the RGB three-channel data later. For example, the Pentile image may be linearly resampled using a linear filter to obtain RGB three-channel data sampled at the same location, so that an initial RGB image may be generated using the RGB three-channel data.
Step 120, determining a pixel local area and a display color to which each pixel position belongs based on the initial RGB image data;
specifically, after the initial RGB image data is obtained, the local area pixel information corresponding to each pixel position may be detected based on the initial RGB image data, so as to determine the local area direction and the display color corresponding to each pixel position according to the local area pixel information corresponding to each pixel position, and then whether the pixel area to which each pixel position belongs to the slit area of the image may be determined according to the local area direction, for example, when the local area direction corresponding to a certain pixel position is the edge direction, the pixel area to which the pixel position belongs may be determined as the slit area, and further it may be determined that the pixel area to which the pixel position belongs to the slit area of the image.
Step 130, if the local pixel area belongs to a slit area of the image and the display color belongs to a preset target color to be processed, determining a pixel point corresponding to the pixel position as a pixel point to be processed;
in this embodiment of the present application, whether a local area of a pixel to which the pixel belongs to a slit area of an image may be determined for each pixel, and whether a display color of the pixel belongs to a preset target color to be processed may be determined, so that when the local area of the pixel belongs to the slit area of the image and the display color belongs to the target color to be processed, that is, when the pixel corresponds to the two conditions, a pixel corresponding to the pixel is determined as a pixel to be processed, so that a channel with stronger information in an RGB channel is used to correct other channels of the pixel to be processed, thereby achieving the purposes of aligning channels with different colors and eliminating a false color. The preset target color to be processed may be a preset target color to be processed, and the target color may be a color that is easy to generate a pseudo color, for example, may include a color that is easy to generate a pseudo color, such as black, white, green, purple, and the like.
And 140, performing image enhancement by adopting green G channel information of the pixel points to be processed based on the initial RGB image data to obtain an RGB image corresponding to the Pentille image.
In a specific implementation, the green G channel is a channel with stronger information in the RGB channel. In this embodiment, after determining the pixel point to be processed, the information of other channels may be corrected by using green G channel information based on the initial RGB image data obtained in step 110, for example, the first-order derivative information and the second-order derivative information of other channels may be corrected by using the G channel information with stronger information in the RGB channels, so as to implement image enhancement, and obtain an RGB image corresponding to the Pentile image.
Therefore, according to the embodiment of the application, the obtained Pentile image is subjected to linear resampling to obtain initial RGB image data, then, based on the initial RGB image data, the local pixel area and the display color of each pixel position are determined, so that when the local pixel area of each pixel position belongs to the slit area of the image and the display color belongs to the preset target color to be processed, the pixel point corresponding to the pixel position is determined to be the pixel point to be processed, then, based on the initial RGB image data, the green G channel information of the pixel point to be processed is adopted for image enhancement, so that other channels with stronger information in the RGB channels are used, the aim of aligning different color channels and eliminating the false color is achieved, the RGB image corresponding to the Pentile image is obtained, the false color of the RGB image generated from the Pentile image can be effectively reduced, and the false color problem of the RGB image generated from the Pentile image is solved.
In a specific implementation, in a Pentile image generated according to the Pentile image format, since the R, B channel and the G channel are half a pixel out of phase (i.e., not at the same horizontal position) in the vertical direction, the R/B channels intersect in odd-even rows, such as the first row in RGBG order and the second row in BGRG order, as shown in fig. 2. In order to reduce the false color after recovering the RGB image from the Pentile image, especially at the edge and slit details, the embodiment of the present application may obtain RGB three-channel data sampled at the same location by linearly resampling the Pentile image after obtaining the Pentile image as initial RGB image data, so that the pixel local area and display color to which each pixel location belongs may be determined based on the initial RGB image data later.
For example, after the input Pentile image is acquired, up-sampling may be performed on the R channel of the first row by 2 times to sample the R channel data with the same number of points as G, as shown in fig. 3, and the image after resampling the R channel may be obtained by sampling the left and right pixels at the position corresponding to each G. Taking the pixel at RX as an example, as shown in fig. 4, the pixel at RX may be calculated by using linear interpolation of R0 and R1, for example, considering that RX is located at 1/4 position near R0 and RX is located at 3/4 position near R1, the R channel pixel value at RX may be calculated according to the formula rx=3/4×r0+1/4×r1. Similarly, the B channel may be also sampled horizontally, so as to obtain an image with the same number of pixels as G in the horizontal direction R, B, as shown in fig. 5, where it is possible to see whether R, B channels are different from each other by half pixels in the vertical direction from the G channel, and the R value at the same position as G may be obtained by linear interpolation using the same pixels in the vertical direction of the first row and the second row, as shown in fig. 6, rx= (r0+r1)/2, and finally an image in which R/G/B is sampled at the same position is generated as an initial RGB image, as shown in fig. 7.
In an optional embodiment of the present application, in a case where the initial RGB image data includes RGB three-channel data, the embodiment of the present application determines, based on the initial RGB image data, a pixel local area and a display color to which each pixel position belongs, and may specifically include the following sub-steps:
a substep 1201 of generating an initial RGB image using the RGB three-channel data;
sub-step 1202, traversing and detecting each pixel in the initial RGB image to obtain a pixel position of each pixel and local area pixel information corresponding to each pixel position;
a sub-step 1203 of determining, for each pixel position, a local area direction corresponding to the pixel position and a display color corresponding to the pixel position by using the local area pixel information;
sub-step 1204, determining a pixel position corresponding to the local area direction as an edge pixel position, and determining a pixel local area to which the edge pixel position belongs as a slit area.
Specifically, in order to reduce the false color after recovering the RGB image from the Pentile image, the present embodiment may use the RGB three-channel data sampled at the same location as the initial RGB image data to generate an initial RGB image using the RGB three-channel data, then may determine the pixel location of each pixel in the initial RGB image by detecting each pixel in the initial RGB image through traversal based on the initial RGB image, and then may determine the pixel local area to which each pixel location belongs based on the pixel location of each pixel in the initial RGB image, for example, when a certain pixel in the initial RGB image is detected through traversal, may determine the pixel location of the pixel as the current pixel location to be processed, then may select a corresponding local area as the pixel local area to which the current pixel location to be processed belongs according to a preset area parameter, and then may determine the image pixel in the pixel local area as local area pixel information, so that the pixel location of each pixel location corresponds to each pixel location may be used to determine the local area and the local color location of each pixel.
In an optional embodiment of the present application, the local area pixel information corresponding to the pixel location includes an image pixel of a local area of the pixel to which the pixel location belongs. After determining the local pixel area to which the pixel position belongs, the embodiment of the application can perform convolution calculation by adopting the image pixels of the local pixel area and a preset direction judgment operator for each pixel position, so as to determine the direction of the local area corresponding to the pixel position by using the value obtained by the convolution calculation. Optionally, the determining, by using the local area pixel information, the local area direction corresponding to the pixel position may specifically include: for each pixel position, convoluting the image pixels of the pixel local area with a preset direction judgment operator to obtain a convolution result, wherein the convolution result comprises detection values corresponding to all detection directions; selecting the largest detection value from the convolution result; and determining the detection direction corresponding to the maximum detection value as the local area direction. The preset direction judgment operator may include one or at least two direction judgment operators, so that the convolution result may include a detection value corresponding to at least one detection direction.
It should be noted that the direction judgment operator may be used to determine a detection value corresponding to the detection direction, so that the local area direction corresponding to the pixel position may be determined by using the detection value.
For example, as shown in fig. 8, when it is determined that the pixel local area to which a certain pixel position belongs is a matrix area of 5*5, 25 pixel values of the 5*5 area may be dot multiplied by 25 values of a preset direction judgment operator K1, and as shown in fig. 9, the values of the corresponding positions are multiplied and accumulated to obtain a value, which represents a detection value obtained by applying the direction judgment operator K1 to the pixel local area. If the direction judgment operator K1 represents detecting a vertical edge, the convolution result obtained by the final calculation is 4, that is, the detection value 4 is smaller, so that it can be determined that the local area of the current pixel has no vertical edge and is more biased to the horizontal edge or the flat area. If the detection value obtained by the convolution of the direction judging operator K1 and the image is relatively large, if the detection value obtained by the final calculation is 20, the current pixel local area can be considered to deviate from the vertical edge, and the vertical direction can be further determined as the area direction of the pixel local area.
In an alternative embodiment of the present application, the preset direction judgment operator may include a vertical edge judgment operator, a horizontal edge judgment operator, a first angle judgment operator, and a second angle judgment operator. The convolution result in this embodiment of the present application includes detection values corresponding to each detection direction, for example, may include a vertical edge detection value corresponding to a vertical direction, a horizontal edge detection value corresponding to a horizontal direction, a first inclination detection value corresponding to a 45 degree direction, a second inclination detection value corresponding to a 45 degree direction, and the like, which is not limited in this embodiment.
Optionally, in the embodiment of the present application, convolving an image pixel in a local area of the pixel with a preset direction judgment operator to obtain a convolution result, which may specifically include: performing dot multiplication on the pixel value of the image pixel and the vertical judgment value of the vertical edge judgment operator to obtain a vertical edge detection value; performing dot multiplication on the pixel value of the image pixel and the horizontal judgment value of the horizontal edge judgment operator to obtain a horizontal edge detection value; performing point multiplication on the pixel value of the image pixel and a first angle judgment value of the first angle judgment operator to obtain a first gradient detection value; performing dot multiplication on the pixel value of the image pixel and a second angle judgment value of the second angle judgment operator to obtain a second gradient detection value; and determining the vertical edge detection value, the horizontal edge detection value, the first inclination detection value and the second inclination detection value as the convolution result, so that the convolution result can comprise detection values corresponding to all detection directions.
As an example of the present application, the detection operator int k1_5x5_l [ ] in the vertical direction may be set as the vertical edge judgment operator in advance, so that the detection operator int k1_5x5_l [ ] may be used to convolve with the image later, that is, the pixel value of the image pixel is dot multiplied with the vertical judgment value of the vertical edge judgment operator, to obtain the vertical edge detection value. The vertical judgment value refers to each value in the vertical edge judgment operator, namely, the vertical judgment value comprises each value in the detection operator int K1_5x5_L in the vertical direction. For example, the vertical edge judgment operator may be set to: int k1_5x5_l [ ] =
{ 0，-2，4，-2，0，
0，-4，8，-4，0，
0，-4，8，-4，0，
0，-4，8，-4，0，
0，-2，4，-2，0 }。
In addition, the detection operator int k2_5x5_l [ ] in the horizontal direction may be set as a horizontal edge judgment operator, so that the detection operator int k2_5x5_l [ ] in the horizontal direction may be used to convolve the image subsequently, that is, the pixel value of the image pixel is dot multiplied with the horizontal judgment value of the horizontal edge judgment operator, to obtain the horizontal edge detection value. The horizontal judgment value refers to each value in the horizontal edge judgment operator, namely, the horizontal judgment value comprises each value in the detection operator int K2_5x5_L in the horizontal direction. For example, the horizontal edge judgment operator may be set to:
int K2_5x5_L[] = { 0，0，0，0，0，
-2，-4，-4，-4，-2，
4，8， 8， 8， 4，
-2，-4，-4，-4，-2，
0，0，0，0， 0}。
In an alternative manner of the present application, the 45-degree detection operator int k3_5x5_l [ ] is set as a first angle judgment operator, and the 135-degree detection operator int k4_5x5_l [ ] is set as a second angle judgment operator, so that the first inclination detection value and the second inclination detection value can be determined by using the 45-degree detection operator int k3_5x5_l [ ] and the 135-degree detection operator int k4_5x5_l [ ] subsequently, and further, the direction information of the local area of the pixel can be determined based on the first inclination detection value and the second inclination detection value, and the vertical edge detection value and the horizontal edge detection value.
Wherein, the first angle judgment value refers to each value in the first angle judgment operator, for example, the first angle judgment value includes each value in the detection operator int k3_5x5_l [ ] in the 45 degree direction, and the detection operator in the 45 degree direction can be set as follows:
int K3_5x5_L[] = { 0，0，0，-2，4，
0，-4，-4，8，-2，
0，-4，8，-4，0，
-2，8，-4，-4，0，
4，-2，0，0，0 }；
the second angle judgment value refers to each value in the second angle judgment operator, for example, the second angle judgment value includes each value in the detection operator int k4_5x5_l [ ] in the 135-degree direction, and the detection operator in the 135-degree direction can be set as follows:
int K4_5x5_L[] = { 4，-2，0，0，0，
-2，8，-4，-4，0，
0，-4，8，-4，0，
0，-4，-4，8，-2，
0，0，0，-2，4 }。
in an embodiment of the present application, after determining the direction of the local area corresponding to the pixel position, the pixel position may be determined to be an edge pixel position by determining whether the direction of the local area corresponding to the pixel position is an edge direction, so that a slit area that may generate a false color may be determined based on the edge pixel position, for example, in a case that the direction of the local area corresponding to a certain pixel position is the edge direction, the pixel position may be determined to be the edge pixel position, so that the slit area that may generate the false color may be determined based on the edge pixel position subsequently. The edge direction may refer to the direction of the image edge, for example, the direction of the image vertical edge or the direction of the image horizontal edge, which is not limited in this embodiment.
In an optional embodiment of the present application, after determining that the direction of the local area corresponding to a certain pixel position is an edge direction, it may be considered that the local area of the pixel to which the pixel position belongs may belong to a slit area generating a pseudo color, and then the green G channel data of the local area of the pixel may be used to perform convolution calculation to obtain a second-order gradient value of the G channel, so as to determine whether the pixel position is an edge pixel position according to the second-order gradient value of the G channel. Optionally, the image conversion method provided in this embodiment may further include the following steps after determining the local area direction corresponding to the pixel position by using the local area pixel information: judging whether the local area direction is an edge direction or not; if the direction of the local area is the edge direction, determining a second-order gradient value of a G channel by adopting green G channel data of the pixel local area; and if the absolute value of the second-order gradient value is larger than a preset gradient threshold value, the step of determining the pixel position corresponding to the local area direction as the edge pixel position is executed. The second order gradient value of the G channel may refer to a second order differential value of the G channel at a certain pixel point, and the larger the absolute value of this value, the greater the likelihood that the G channel is a slit region here.
As an example of the present application, a second order differential convolution kernel may be used as a second order operator, and convolved with the G channel data to obtain a second order differential value of the G channel, as a second order gradient value of the G channel. Specifically, determining the second-order gradient value of the G channel by using the green G channel data of the pixel local area may specifically include: acquiring a second-order differential convolution kernel; and carrying out convolution calculation by utilizing the second-order differential convolution kernel and the G channel data to obtain a second-order gradient value of the G channel. For example, in the case where the obtained second-order differential convolution kernel is a convolution kernel as shown in fig. 10, the convolution kernel may be used to convolve the G-channel data as shown in fig. 11, that is, to dot-multiply the G-channel data with the data in the convolution kernel, and as shown in fig. 12, the resulting value 20 is the second-order differential value of the G-channel at a certain pixel point, as the second-order gradient value of the G-channel at that pixel point.
Considering that the second order differential value has a negative number, that is, the second order gradient value of the G channel may be a negative number, after determining the second order gradient value of the G channel, it may be determined whether the pixel position is determined to be an edge pixel position by determining whether the absolute value of the second order gradient value of the G channel is greater than a preset gradient threshold value, and then the pixel position may be determined to be an edge pixel position when the absolute value of the second order gradient value of the G channel is greater than the gradient threshold value, so that the pixel region to which the edge pixel position belongs may be directly determined to be a slit region of the image. The gradient threshold can be set according to the image enhancement requirement, for example, a certain threshold T can be set as a preset gradient threshold, so that when the absolute value of the second-order gradient value of the G channel is larger than the threshold T, the G channel information is adopted to enhance the image, and the pixel value of the R, B channel is close to that of the G channel, so that the aims of aligning channels with different colors and eliminating false colors are achieved.
In an optional embodiment of the present application, when it is determined that a local area direction corresponding to a certain pixel position is an edge direction, an area pixel distribution condition corresponding to the pixel position may be determined by acquiring an image pixel of a local area of a pixel to which the pixel position belongs, so as to determine whether a display color corresponding to the pixel position belongs to a target color to be processed according to the area pixel distribution condition. Optionally, when the local area pixel information includes an image pixel of a local area of a pixel to which the pixel position belongs, determining, for each pixel position, a local area direction corresponding to the pixel position and a display color corresponding to the pixel position using the local area pixel information may specifically include: determining the local area direction corresponding to each pixel position by adopting the local area pixel information corresponding to each pixel position; judging whether the local area direction is an edge direction or not according to each pixel position; and if the local area direction is the edge direction, determining the display color by using the image pixels of the pixel local area.
For example, in the case where it is determined that the direction of the local area corresponding to a certain pixel position is the edge direction, an image pixel of the local area of the pixel to which the pixel position belongs may be acquired, so as to determine area pixel distribution information by using the acquired image pixel, and then a display color corresponding to the pixel position may be determined according to the area pixel distribution information, so that whether or not to determine a pixel point corresponding to the pixel position as a pixel point to be processed may be determined by determining whether or not the display color corresponding to the pixel position belongs to a target color to be processed.
For example, after a pixel point corresponding to a certain pixel position is determined as a pixel point to be processed, other channels of the pixel point to be processed can be corrected by using a channel with stronger information in the RGB channels based on the initial RGB image data so as to align different color channels, thereby reducing the pseudo color of the RGB image finally generated and enhancing the visual effect of the image. Optionally, in this embodiment of the present application, image enhancement is performed by using green G channel information of the pixel to be processed based on the initial RGB image data to obtain an RGB image corresponding to the Pentile image, which may specifically include: extracting green G channel information and channel information to be enhanced of the pixel points to be processed from the initial RGB image data; correcting the channel information to be enhanced by adopting the green G channel information to obtain corrected image information; and generating an RGB image corresponding to the Pentille image by combining the initial RGB image data by utilizing the corrected image information.
The channel information to be enhanced comprises pixel values of a channel to be enhanced, wherein the channel to be enhanced comprises a red R channel and a blue B channel. For example, after determining a pixel point corresponding to a certain pixel position as a pixel point to be processed, second derivative information of a G channel of the pixel point to be processed may be calculated by using initial RGB image data for the pixel point to be processed, so as to enhance or reduce a pixel value of a R, B channel of the pixel point to be processed through the second derivative information of the G channel, so that the pixel value of the R, B channel is close to the G channel, so as to achieve the effect of reducing the false color.
In an alternative embodiment of the present application, the second derivative information of the G channel may include an absolute value of a second order gradient value of the G channel and a second order operator maximum value. Optionally, in this embodiment of the present application, the correcting the channel information to be enhanced by using the green G channel information to obtain corrected image information may specifically include: determining second derivative information of the green G channel by using the green G channel information; comparing the pixel value with a channel pixel average value corresponding to a target pixel area for each channel to be enhanced, wherein the target pixel area is a pixel area to which the pixel point to be processed belongs; if the pixel value is larger than the average value of the channel pixels, the pixel value is enhanced by utilizing the maximum pixel value of the channel to be enhanced and combining the second derivative information, so as to obtain a pixel enhancement value; if the pixel value is smaller than the average value of the channel pixels, the pixel value is reduced by utilizing the minimum pixel value of the channel to be enhanced and combining the second derivative information, so as to obtain a pixel reduction value; the pixel enhancement value and the pixel reduction value are determined as the modified image information.
Specifically, after determining the pixel point to be processed, the embodiment of the application may implement image enhancement by traversing respective original values of the R/B channels for the pixel point to be processed, so as to separately calculate pixel values of the R, B channels. Specifically, after extracting the pixel value of the R channel or the B channel from the initial RGB data, the maximum pixel value max, the minimum pixel value min, and the average mean of the local area to which the pixel point to be processed belongs can be calculated based on the pixel value of the R channel or the B channel, and the average mean can be used as the average value of the channel pixels, so that the maximum pixel value is utilized to combine with the absolute value S of the second order gradient value of the G channel and the maximum value of the second order operator according to the image enhancement formula based on the average value of the channel pixels, and the correction image information is obtained, so that the RGB image corresponding to the Pentile image can be generated by utilizing the correction image information, the false color of the RGB image can be effectively generated, and the visual effect of the image is enhanced.
For example, in the case where the original value of the channel to be enhanced is V and the correction value is v_out, a specific image enhancement formula is: if V > mean, v_out=v+ (max-V) S/s_max; if V < mean, v_out=v- (V-min) S/s_max. The original value V of the channel to be enhanced may be the original value of the R channel of the pixel to be processed, or the original value of the B channel. It can be seen that this example can determine whether to enhance or reduce the pixel value of the R, B channel by determining whether the original value V of the channel to be enhanced is smaller than the average value mean, so that the pixel value of the R, B channel is close to the G channel, so as to achieve the purpose of aligning the channels with different colors and eliminating the false color.
To sum up, in order to reduce the false color after recovering the RGB image from the Pentile image, especially at the edge and slit details, the embodiment obtains RGB three-channel data sampled at the same position by linearly resampling the Pentile image after obtaining the Pentile image as initial RGB image data, then determines a pixel local area and a display color to which each pixel position belongs based on the initial RGB image data, so as to determine a pixel point corresponding to the pixel position as a pixel point to be processed when the pixel local area belongs to the slit area of the image and the display color belongs to the target color to be processed, then uses green G-channel information of the pixel point to be processed to perform image enhancement, actively correct the edge positions of the RGB three channels, align the three channels, and remove the false color of the generated RGB image.
It should be noted that, for simplicity of description, the method embodiments are shown as a series of acts, but it should be understood by those skilled in the art that the embodiments are not limited by the order of acts described, as some steps may occur in other orders or concurrently in accordance with the embodiments.
As shown in fig. 13, an embodiment of the present application further provides an image conversion apparatus, including:
a linear resampling module 1301, configured to obtain initial RGB image data by performing linear resampling on the obtained Pentile image;
a local area and color determination module 1302 configured to determine, based on the initial RGB image data, a local area and a display color of a pixel to which each pixel position belongs;
a pixel point to be processed module 1303, configured to determine a pixel point corresponding to the pixel position as a pixel point to be processed if the local pixel region belongs to a slit region of an image and the display color belongs to a preset target color to be processed;
and an image enhancement module 1304, configured to perform image enhancement by using the green G channel information of the pixel to be processed based on the initial RGB image data, so as to obtain an RGB image corresponding to the Pentile image.
Optionally, the initial RGB image data includes RGB three-channel data, and the local area and color determining module 1302 includes:
an initial RGB image generation sub-module for generating an initial RGB image using the RGB three-channel data;
the traversal detection sub-module is used for traversal detection of each pixel in the initial RGB image to obtain the pixel position of each pixel and the local area pixel information corresponding to each pixel position;
And the first determining submodule is used for determining the local area direction corresponding to the pixel position and the display color corresponding to the pixel position by adopting the local area pixel information for each pixel position.
And the second determining submodule is used for determining the pixel position with the corresponding local area direction being the edge direction as an edge pixel position and determining the pixel local area to which the edge pixel position belongs as a slit area.
Optionally, the local area pixel information includes an image pixel of a local area of a pixel to which the pixel position belongs, and the first determining submodule includes:
the convolution unit is used for convolving the image pixels of the pixel local area with a preset direction judgment operator aiming at each pixel position to obtain a convolution result, wherein the convolution result comprises detection values corresponding to all detection directions;
a detection value selecting unit, configured to select a maximum detection value from the convolution result;
and the direction determining unit is used for determining the detection direction corresponding to the maximum detection value as the local area direction.
Optionally, the first determining submodule includes:
a direction judging unit for judging whether the local area direction is an edge direction;
The second-order gradient value unit is used for determining a second-order gradient value of a G channel by adopting green G channel data of the local area of the pixel if the direction of the local area is the edge direction;
and the triggering unit is used for triggering the second determination submodule to execute the step of determining the pixel position corresponding to the local area direction as the edge pixel position if the absolute value of the second-order gradient value is larger than a preset gradient threshold value.
Optionally, the local area pixel information includes an image pixel of a local area of a pixel to which the pixel position belongs, and the first determining submodule includes:
a local area direction determining unit, configured to determine a local area direction corresponding to each pixel position by using local area pixel information corresponding to each pixel position;
an edge direction judging unit for judging whether the local area direction is an edge direction for each pixel position;
and the display color determining unit is used for determining the display color by utilizing the image pixels of the pixel local area if the local area direction is the edge direction.
Optionally, the image enhancement module 1304 includes:
the extraction sub-module is used for extracting green G channel information and channel information to be enhanced of the pixel points to be processed from the initial RGB image data;
The correction submodule is used for correcting the channel information to be enhanced by adopting the green G channel information to obtain corrected image information;
and the image generation sub-module is used for generating the RGB image corresponding to the Pentille image by combining the initial RGB image data by utilizing the corrected image information.
Optionally, the channel information to be enhanced includes a pixel value of a channel to be enhanced, the channel to be enhanced includes a red R channel and a blue B channel, and the correction submodule is specifically configured to: determining second derivative information of the green G channel by using the green G channel information; comparing the pixel value with a channel pixel average value corresponding to a target pixel area for each channel to be enhanced, wherein the target pixel area is a pixel area to which the pixel point to be processed belongs; if the pixel value is larger than the average value of the channel pixels, the pixel value is enhanced by utilizing the maximum pixel value of the channel to be enhanced and combining the second derivative information, so as to obtain a pixel enhancement value; if the pixel value is smaller than the average value of the channel pixels, the pixel value is reduced by utilizing the minimum pixel value of the channel to be enhanced and combining the second derivative information, so as to obtain a pixel reduction value; the pixel enhancement value and the pixel reduction value are determined as the modified image information.
In a specific implementation, the image conversion device can be applied to an electronic device, so that the electronic device is used as the image conversion device, initial RGB image data is obtained by linearly resampling the acquired Pentille image, and then a pixel local area and a display color to which each pixel position belongs are determined based on the initial RGB image data; if the pixel local area belongs to a slit area of an image and the display color belongs to a preset target color to be processed, determining a pixel point corresponding to the pixel position as the pixel point to be processed, so that image enhancement can be performed by adopting green G channel information of the pixel point to be processed based on the initial RGB image data to obtain an RGB image corresponding to the Pentille image, thereby effectively reducing the pseudo color of the RGB image, and solving the pseudo color problem of the RGB image generated from the Pentille image. The image conversion apparatus may be constituted by two or more physical entities or may be constituted by one physical entity, for example, the image conversion apparatus may be a personal computer (Personal Computer, PC), a computer, a server, or the like, which is not particularly limited in the embodiment of the present application.
As shown in fig. 14, an embodiment of the present application provides an image conversion apparatus, including a processor 111, a communication interface 112, a memory 113, and a communication bus 114, where the processor 111, the communication interface 112, and the memory 113 perform communication with each other through the communication bus 114, and the memory 113 is used for storing a computer program; in one embodiment of the present application, the processor 111 is configured to implement the steps of the image conversion method provided in any one of the foregoing method embodiments when executing the program stored in the memory 113. The image conversion method comprises the following steps: obtaining initial RGB image data by linearly resampling the acquired Pentille image; determining a pixel local area and a display color to which each pixel position belongs based on the initial RGB image data; if the pixel local area belongs to a slit area of the image and the display color belongs to a preset target color to be processed, determining a pixel point corresponding to the pixel position as a pixel point to be processed; and carrying out image enhancement by adopting green G channel information of the pixel points to be processed based on the initial RGB image data to obtain an RGB image corresponding to the Pentille image.
The present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the image conversion method provided by any one of the method embodiments described above.
The present application also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of the image conversion method provided by any of the method embodiments described above.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
From the above description of embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus a general purpose hardware platform, or may be implemented by hardware. Based on such understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the related art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the method described in the respective embodiments or some parts of the embodiments.
It is to be understood that the terminology used herein is for the purpose of describing particular example embodiments only, and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. The terms "comprises," "comprising," "includes," "including," and "having" are inclusive and therefore specify the presence of stated features, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, and/or groups thereof. The method steps, processes, and operations described herein are not to be construed as necessarily requiring their performance in the particular order described or illustrated, unless an order of performance is explicitly stated. It should also be appreciated that additional or alternative steps may be used.
The foregoing is only a specific embodiment of the invention to enable those skilled in the art to understand or practice the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (11)
1. An image conversion method, comprising:
obtaining initial RGB image data by linearly resampling the acquired Pentille image;
determining a pixel local area and a display color to which each pixel position belongs based on the initial RGB image data;
if the pixel local area belongs to a slit area of the image and the display color belongs to a preset target color to be processed, determining a pixel point corresponding to the pixel position as a pixel point to be processed;
and carrying out image enhancement by adopting green G channel information of the pixel points to be processed based on the initial RGB image data to obtain an RGB image corresponding to the Pentille image.
2. The image conversion method according to claim 1, wherein the initial RGB image data contains RGB three-channel data, and the determining a pixel partial area and a display color to which each pixel position belongs based on the initial RGB image data includes:
generating an initial RGB image by adopting the RGB three-channel data;
traversing and detecting each pixel in the initial RGB image to obtain the pixel position of each pixel and the local area pixel information corresponding to each pixel position;
For each pixel position, determining a local area direction corresponding to the pixel position and a display color corresponding to the pixel position by adopting the local area pixel information;
and determining the pixel position corresponding to the local area direction as the edge direction as an edge pixel position, and determining the pixel local area to which the edge pixel position belongs as a slit area.
3. The image conversion method according to claim 2, wherein the local area pixel information includes an image pixel of a local area of a pixel to which the pixel position belongs, and the determining the local area direction corresponding to the pixel position using the local area pixel information includes:
for each pixel position, convoluting the image pixels of the pixel local area with a preset direction judgment operator to obtain a convolution result, wherein the convolution result comprises detection values corresponding to all detection directions;
selecting the largest detection value from the convolution result;
and determining the detection direction corresponding to the maximum detection value as the local area direction.
4. The image conversion method according to claim 2, wherein after determining the local area direction corresponding to the pixel position using the local area pixel information, further comprising:
Judging whether the local area direction is an edge direction or not;
if the direction of the local area is the edge direction, determining a second-order gradient value of a G channel by adopting green G channel data of the pixel local area;
and if the absolute value of the second-order gradient value is larger than a preset gradient threshold value, the step of determining the pixel position corresponding to the local area direction as the edge pixel position is executed.
5. The image conversion method according to claim 2, wherein the local area pixel information includes image pixels of a local area of a pixel to which the pixel position belongs, and the determining, for each pixel position, a local area direction corresponding to the pixel position and a display color corresponding to the pixel position using the local area pixel information includes:
determining the local area direction corresponding to each pixel position by adopting the local area pixel information corresponding to each pixel position;
judging whether the local area direction is an edge direction or not according to each pixel position;
and if the local area direction is the edge direction, determining the display color by using the image pixels of the pixel local area.
6. The image conversion method according to any one of claims 1 to 5, wherein performing image enhancement using green G channel information of the pixel to be processed based on the initial RGB image data to obtain an RGB image corresponding to the Pentile image, includes:
extracting green G channel information and channel information to be enhanced of the pixel points to be processed from the initial RGB image data;
correcting the channel information to be enhanced by adopting the green G channel information to obtain corrected image information;
and generating an RGB image corresponding to the Pentille image by combining the initial RGB image data by utilizing the corrected image information.
7. The image conversion method according to claim 6, wherein the channel information to be enhanced includes pixel values of channels to be enhanced, the channels to be enhanced include a red R channel and a blue B channel, the modifying the channel information to be enhanced by using the green G channel information to obtain modified image information includes:
determining second derivative information of the green G channel by using the green G channel information;
comparing the pixel value with a channel pixel average value corresponding to a target pixel area for each channel to be enhanced, wherein the target pixel area is a pixel area to which the pixel point to be processed belongs;
If the pixel value is larger than the average value of the channel pixels, the pixel value is enhanced by utilizing the maximum pixel value of the channel to be enhanced and combining the second derivative information, so as to obtain a pixel enhancement value;
if the pixel value is smaller than the average value of the channel pixels, the pixel value is reduced by utilizing the minimum pixel value of the channel to be enhanced and combining the second derivative information, so as to obtain a pixel reduction value;
the pixel enhancement value and the pixel reduction value are determined as the modified image information.
8. An image conversion apparatus, comprising:
the linear resampling module is used for obtaining initial RGB image data by linearly resampling the acquired Pentille image;
a local area and color determining module, configured to determine, based on the initial RGB image data, a local area of a pixel and a display color to which each pixel position belongs;
a pixel point to be processed module, configured to determine a pixel point corresponding to the pixel position as a pixel point to be processed if the pixel local area belongs to a slit area of an image and the display color belongs to a preset target color to be processed;
and the image enhancement module is used for carrying out image enhancement by adopting the green G channel information of the pixel points to be processed based on the initial RGB image data to obtain an RGB image corresponding to the Pentille image.
9. An image conversion apparatus, characterized by comprising: the device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;
a memory for storing a computer program;
a processor for implementing the steps of the image conversion method according to any one of claims 1 to 7 when executing a program stored on a memory.
10. A computer storage medium storing computer executable instructions for performing the steps of the image conversion method according to any one of claims 1-7.
11. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the image conversion method according to any one of claims 1-7.
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