WO2018214769A1

WO2018214769A1 - Image processing method, device and system

Info

Publication number: WO2018214769A1
Application number: PCT/CN2018/086648
Authority: WO
Inventors: 王东; 刘华平
Original assignee: 阿里巴巴集团控股有限公司
Priority date: 2017-05-24
Filing date: 2018-05-14
Publication date: 2018-11-29
Also published as: CN108961170B; TW201901616A; CN108961170A

Abstract

Disclosed in embodiments of the present application are an image processing method, device and system. The method comprises: obtaining a to-be-processed image, a to-be-processed row/column of the to-be-processed image comprising a filtered pixel and at least one to-be-filtered pixel at an end point; starting from the end point of the to-be-processed row/column of the to-be-processed image, performing first bilateral exponential filtering processing on the to-be-processed image, the first bilateral exponential filtering processing being partially based on a difference between an image parameter value of the filtered pixel and an image parameter value of the to-be-filtered pixel and a distance between the filtered pixel and the to-be-filtered pixel; and determining an output image of the to-be-processed image according to the result of the first bilateral exponential filtering processing. The solution in the embodiments of the present application can further improve the image denoising and edge preservation effects, and can improve the image quality after filtering processing.

Description

Image processing method, device and system

The present application claims the priority of the Japanese Patent Application Serial No. No. No. No. No. No. No. Publication No

Technical field

The present application relates to the field of image processing, and more particularly to an image processing method, apparatus and system.

Background technique

At this stage, there are many mature image denoising algorithms applied to real-time beauty. Simple denoising can not preserve the sharpness of the edges of the image while denoising, in order to achieve a better beauty effect.

In the existing bilateral filtering algorithm, edge perseving can be obtained by bilateral filtering, and image noise can be removed at the same time. However, after carefully studying the bilateral filtering algorithm of the prior art, the inventors found that only the influence of the gray-scale difference of adjacent pixel points on the filtered pixel is considered in the filtering process, and the edge-preserving effect and the denoising effect are still compared. Great room for improvement.

How to improve the image quality after the filtering process is a technical problem to be solved by the embodiment of the present application.

Summary of the invention

The main purpose of the present application is to provide an image processing method, apparatus and system for improving image denoising and edge preservation effects and improving image quality after filtering processing.

To solve the above technical problem, the embodiment of the present application is implemented as follows:

In a first aspect, an image processing method is proposed, the method comprising:

Obtaining a to-be-processed image, the to-be-processed row/column of the to-be-processed image includes a filtered pixel point at the endpoint and at least one pixel to be filtered;

Performing a first bilateral exponential filtering process on the to-be-processed image from the end of the to-be-processed row/column of the to-be-processed image, wherein the first bilateral exponential filtering processing portion is based on: image parameter values of the filtered pixel point and to be filtered The difference between the image parameter values of the pixel and the distance between the filtered pixel and the pixel to be filtered;

Based on the result of the first bilateral exponential filtering process, an output image of the image to be processed is determined.

In a second aspect, an image processing apparatus is proposed, the apparatus comprising:

Acquiring a unit to obtain an image to be processed, where the to-be-processed row/column of the image to be processed includes a filtered pixel point at the endpoint and at least one pixel to be filtered;

a processing unit that performs a first bilateral exponential filtering process on the to-be-processed image from an endpoint of the to-be-processed row/column of the to-be-processed image, wherein the first bilateral exponential filtering processing portion is based on: an image parameter value of the filtered pixel a difference from an image parameter value of a pixel to be filtered, and a distance between the filtered pixel and the pixel to be filtered;

The determining unit determines an output image of the image to be processed according to the result of the first bilateral exponential filtering process.

In a third aspect, an electronic device is proposed, the electronic device comprising:

Processor;

A memory arranged to store computer executable instructions that, when executed, cause the processor to perform the following operations:

In a fourth aspect, an image processing system is provided, the system comprising the image processing apparatus of the second aspect or the third aspect.

In a fifth aspect, a computer readable storage medium is presented, the computer readable storage medium storing one or more programs, the one or more programs comprising instructions that, when executed by an electronic device comprising a plurality of applications , enabling the electronic device to perform the following methods:

In a sixth aspect, an image processing method is proposed, the method comprising:

Obtaining a to-be-processed image, the to-be-processed row/column of the to-be-processed image includes a filtered pixel point and at least one pixel to be filtered;

Performing a first bilateral exponential filtering process on the to-be-processed row/column of the image to be processed, wherein the first bilateral exponential filtering processing portion is based on: a difference between an image parameter value of the filtered pixel point and an image parameter value of the pixel to be filtered And the distance between the filtered pixel and the pixel to be filtered;

As can be seen from the technical solutions provided by the embodiments of the present application, the embodiment of the present application performs bilateral exponential filtering processing according to the difference and distance of pixel points, which can improve image denoising and edge preservation effects, and improve image quality after filtering processing.

DRAWINGS

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings to be used in the embodiments or the prior art description will be briefly described below. Obviously, the drawings in the following description are only It is a few embodiments described in the present application, and other drawings can be obtained from those skilled in the art without any inventive labor.

1 is an impulse response diagram of an embodiment of the present application after bilateral exponential filtering.

2 is a schematic diagram of an image to be processed of an embodiment of the present application.

3 is a flow chart of a method of image processing in accordance with an embodiment of the present application.

4 is a comparison diagram of the effect of processing the number of frames in one embodiment of the present application.

FIG. 5 is a comparison diagram of another processing frame number effect of one embodiment of the present application.

FIG. 6 is a comparison diagram of another processing frame number effect according to an embodiment of the present application.

FIG. 7 is a comparison diagram of filtering effects under an optimization method of an embodiment of the present application.

Figure 8 is a schematic illustration of parallel image processing of one embodiment of the present application.

FIG. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

FIG. 10 is a schematic structural diagram of an image processing apparatus according to an embodiment of the present application.

11 is a flow chart of a method of image processing in another embodiment of the present application.

detailed description

An embodiment of the present application provides an image processing method, apparatus, and system.

The technical solutions in the embodiments of the present application are clearly and completely described in the following, in which the technical solutions in the embodiments of the present application are clearly and completely described. The embodiments are only a part of the embodiments of the present application, and not all of them. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present application without departing from the inventive scope shall fall within the scope of the application.

In the research process of the existing bilateral filtering processing technology, the inventor found that the closer the pixel points are to the filtering pixel point, the greater the influence on the filtering pixel point; on the contrary, the smaller the effect on the filtering pixel point. 1 is an impulse response diagram of an embodiment of the present application after bilateral exponential filtering. The abscissa of the curve function in the figure represents the distance between the pixel points, and the ordinate represents the influence factor of the pixel point. As can be seen from Figure 1, the curve decays rapidly after deviating from the centerline. After inventing the relationship between distance and filtering, the inventor improved the range filter kernel function of the double-index filter, which improved the image processing effect.

To facilitate understanding of the image processing method of the embodiment of the present application, FIG. 2 shows a schematic diagram of an image to be processed of one embodiment of the present application. As shown in FIG. 2, in the image processing method of the embodiment of the present application, the image to be processed may be subjected to bilateral filtering processing in the horizontal direction (the A and B directions shown in FIG. 2); or in the vertical direction (as shown in FIG. 2). In the C and D directions, the image to be processed is subjected to bilateral filtering processing; or the image to be processed may be bilaterally filtered in both the horizontal direction and the vertical direction.

3 is a flow chart of a method of image processing in accordance with an embodiment of the present application. The method of Figure 3 is performed by an image processing device. In the embodiment of the present application, the image processing device may be a processor, a graphics processor, or a filter such as a finite-length unit impulse response (FIR) filter. The method of Figure 3 can include:

S301. Acquire an image to be processed.

The pending row/column of the to-be-processed image includes filtered pixel points at the endpoint and at least one pixel to be filtered.

It should be understood that, in the embodiment of the present application, the first bilateral exponential filtering process includes a first one-sided exponential filtering process in a first direction from a first end to a second end of the to-be-processed row/column of the image to be processed, and A second one-sided exponential filtering process in a second direction from the second end of the to-be-processed row/column of the image to be processed to the first end.

It should be understood that, in the embodiment of the present application, the to-be-processed row/column includes the filtered pixel points located at the endpoint, and may specifically include: a pixel point located at the first end and filtered, and filtered at the second end. pixel. Of course, it should be understood that, in the embodiment of the present application, the filtered pixel points within a predetermined distance of the endpoint may be regarded as the filtered pixel points of the endpoint in the embodiment of the present application.

It should be understood that, in the embodiment of the present application, how to obtain the filtered pixel points located at the endpoints is not limited in this embodiment of the present application. For example, the pixel located at the endpoint in the row/column of the original image may be regarded as a filtered pixel to obtain a to-be-processed image; or, for example, a pending row/column of the original image may be adopted in some filtering manner. The pixel located at the endpoint is filtered to obtain a filtered pixel, thereby obtaining a to-be-processed image, and the like.

S302. Perform a first bilateral exponential filtering process on the to-be-processed image from an endpoint of the to-be-processed row/column of the to-be-processed image.

The first bilateral index filtering processing is based on: a difference between an image parameter value of the filtered pixel and an image parameter value of the pixel to be filtered, and a distance between the filtered pixel and the pixel to be filtered.

It should be understood that when the image to be processed is subjected to filtering processing, it may include filtering processing of rows, or filtering processing of columns, or filtering processing on rows and columns, respectively.

It should be understood that in the embodiment of the present application, the image parameter value may be one or more color space indicators in any one color space. For example, taking the YUV color space as an example, the image parameter value may be a Y parameter of the YUV color space, that is, a brightness (Luminance), or a chromaticity U parameter or a V parameter of the YUV color space, and the image parameter value may also be simultaneously Includes three parameters for the YUV color space and more. When the image parameter value includes a plurality of parameters, the image parameter value may be regarded as a multi-dimensional value, and the parameters in each dimension may be separately processed. For another example, in the RBG color space, the color is converted into a black and white image of 0-255, and a gray value can be obtained, and the image parameter value can also be a gray value.

It should be understood that the first bilateral index filtering processing portion is based on the difference between the image parameter value of the filtered pixel point and the image parameter value of the pixel to be filtered, and the distance between the filtered pixel point and the pixel to be filtered, which refers to the first bilateral index. The filtering process may perform filtering processing based only on the difference and the distance, or may perform filtering processing based on a plurality of parameters including the difference and the distance.

It should be understood that the first bilateral exponential filtering processing portion is based on: a difference between an image parameter value of the filtered pixel point and an image parameter value of the pixel to be filtered, and a distance between the filtered pixel point and the pixel to be filtered, and the specific implementation is: The range filtering kernel function of a bilateral exponential filtering process is based in part on the difference between the image parameter value of the filtered pixel and the image parameter value of the pixel to be filtered, and the distance between the filtered pixel and the pixel to be filtered.

It should be understood that the range filter function of the first bilateral exponential filter processing is based in part on the difference between the image parameter value of the filtered pixel and the image parameter value of the pixel to be filtered, and the distance between the filtered pixel and the pixel to be filtered. ,include:

The range filter function of the first one-sided exponential filter is partially based on: a difference between an image parameter value of the filtered pixel and an image parameter value of the pixel to be filtered, and a distance between the filtered pixel and the pixel to be filtered;

The range filter function of the second one-sided exponential filter is based in part on the difference between the image parameter value of the filtered pixel and the image parameter value of the pixel to be filtered, and the distance between the filtered pixel and the pixel to be filtered.

For the first one-sided exponential filtering process, the image parameter value of the pixel to be filtered refers to an image parameter value when the pixel to be filtered does not undergo any filtering process in the image to be processed; if the filtered pixel The point is not the initial filtered pixel point of the first one-sided exponential filtering process, and the image parameter value of the filtered pixel point refers to the image parameter value of the pixel of the image to be processed after the first one-sided exponential filtering process.

Similarly, for the second one-sided exponential filtering process, the image parameter value of the pixel to be filtered refers to an image parameter value when the pixel to be filtered does not undergo any filtering process in the image to be processed; if the filtered The pixel point is not the initial filtered pixel point of the second one-sided exponential filtering process, and the image parameter value of the filtered pixel point refers to the image parameter value of the pixel of the image to be processed after the second one-sided exponential filtering process.

It should be understood that, for the first one-sided exponential filtering process, the pixel to be filtered is the next pixel in the to-be-processed row/column where the filtered pixel is processed by the first one-sided exponential filtering; In the case of the one-sided exponential filtering process, the pixel to be filtered is the next pixel in the to-be-processed row/column in which the filtered pixel is subjected to the second one-sided exponential filtering.

For example, suppose a certain pending line of the image to be processed includes 3 pixels of A, B, and C from left to right. It is assumed that the first bilateral exponential filtering process includes a first one-sided exponential filtering process from left to right and a second one-sided exponential filtering process from right to left. Then the entire filtering process can include:

(1) processing pixel A to obtain a filtered image parameter value of pixel A, where A is the initial filtered pixel of the first one-sided exponential filtering process;

(2) According to the filtered image parameter value of the filtered pixel point A, the image parameter value of the pixel point B to be filtered, and the distance between the pixel points A and B, the filtering of the pixel point B after the first one-sided exponential filtering process is obtained. Image parameter value 2;

(3) According to the filtered image parameter value of the filtered pixel point B, the image parameter value of the pixel point C to be filtered, and the distance between the pixel points B and C, the filtering of the pixel point C after the first single-sided exponential filtering process is obtained. Image parameter value 3;

(4) processing the pixel point C to obtain a filtered image parameter value 4 of the pixel point C, where C is the initial filtered pixel point of the second one-sided exponential filtering process;

(5) According to the filtered image parameter value 4 of the filtered pixel point C, the image parameter value of the pixel point B to be filtered, and the distance between the pixel points B and C, the filtering of the pixel point B after the second one-sided exponential filtering process is obtained. Image parameter value 5;

(6) According to the filtered image parameter value 5 of the filtered pixel point B, the image parameter value of the pixel point A to be filtered, and the distance between the pixel points A and B, the filtering of the pixel point A after the second one-sided exponential filtering process is obtained. Image parameter value 6.

Of course, it should be understood that in the first single-sided exponential filtering process and the second one-sided exponential filtering process described above, the two do not interfere with each other and can be executed in parallel, that is, steps (1)-(3) and (4)-( 6) The two sets of steps can be performed in parallel.

It should be understood that, in step S302, performing a first bilateral exponential filtering process on the to-be-processed image may specifically include:

Determining, according to a difference between an image parameter value of the first pixel to be filtered and an image parameter value of the first filtered pixel, and a distance between the first pixel to be filtered and the first filtered pixel, determining that the first pixel to be filtered passes The image parameter value after the first one-sided exponential filtering, wherein the first pixel to be filtered is the next pixel to be filtered in which the first filtered pixel is subjected to the first one-sided exponential filtering in the first direction. .

It should be understood that if the first filtered pixel is the initial filtered pixel of the first one-sided exponential filtering process, the image parameter value of the first filtered pixel is the filtered image parameter value of the initial filtered pixel; When the filtered pixel is not the initial filtered pixel of the first one-sided exponential filtering process, the image parameter value of the first filtered pixel is the image parameter of the first filtered pixel after the first one-sided exponential filtering process. value.

It should be understood that, in step S302, the first bilateral exponential filtering process is performed on the image to be processed, and specifically, the method further includes:

Determining, according to a difference between an image parameter value of the second pixel to be filtered and an image parameter value of the second filtered pixel, and a distance between the second pixel to be filtered and the second filtered pixel, determining that the second pixel to be filtered passes a second single-sided exponentially filtered image parameter value, wherein the second pixel to be filtered is a next pixel to be filtered in which the second filtered pixel is subjected to the second one-sided exponential filtering in the second direction .

It should be understood that if the second filtered pixel is the initial filtered pixel of the second one-sided exponential filtering process, the image parameter value of the second filtered pixel is the filtered image parameter value of the initial filtered pixel; When the second filtered pixel is not the initial filtered pixel of the second one-sided exponential filtering process, the image parameter value of the second filtered pixel is the image parameter of the second filtered pixel after the second one-sided exponential filtering process. value.

Of course, it should be understood that, in step S302, performing the first bilateral exponential filtering process on the image to be processed may further include:

Determining, according to the image parameter value after the pixel is subjected to the first one-sided exponential filtering process, and the image parameter value of the pixel point after the second one-sided exponential filtering process, determining that the pixel point passes the first bilateral exponential filtering process Image parameter values after.

For example, according to the filtered image parameter value 2 of the pixel point B of the foregoing step (2) and the filtered image parameter value 5 of the pixel point B of the step (5), the image of the pixel point B after the first bilateral exponential filtering process can be determined. Parameter value.

S303. Determine an output image of the image to be processed according to a result of the first bilateral index filtering process.

In the embodiment of the present application, the bilateral exponential filtering process is performed on the image to be processed according to the pixel point distance and the image parameter value of the pixel point, and the influence of the distance and the image parameter value on the pixel point filtering is fully considered, thereby making the output image better. The edge protection effect and denoising effect improve the display quality of the output image.

For ease of understanding, the algorithm for the first bilateral exponential filtering is described below using a formula.

As described in step S302, the range filter function of the first one-sided exponential filter is partially based on: a difference between an image parameter value of the filtered pixel and an image parameter value of the pixel to be filtered, and a filtered pixel to be filtered. The distance of the pixel point; the range filter function of the second single-sided exponential filter is based on: the difference between the image parameter value of the filtered pixel and the image parameter value of the pixel to be filtered, and the filtered pixel and the pixel to be filtered The distance of the point. For ease of understanding, the present application provides a method for determining a range filter kernel function for bilateral exponential filtering, as shown in equation (1):

Where r(u,v) represents the range filter kernel function of the bilateral exponential filter, uv represents the difference in image parameter values between two pixel points, and σ represents the standard deviation of the range filter coefficient θ[k], dis(u , v) represents the distance between two pixel points.

For the first one-sided exponential filtering in the first direction, the range filter coefficient θ[k] can be expressed by the following formula (2):

among them,

The image parameter value of the pixel after the first one-sided exponential filtering process of the pixel point k is filtered.

Combining formula (1) and formula (2), according to the standard deviation σ of the range filter coefficient θ[k], the spatial relative delay coefficient α, and the intermediate coefficient

For the range filter coefficient θ[k], it can be expressed by the following formula (3):

Where d represents the spacing between pixel point k and pixel point k-1.

In addition, the image parameter value of the pixel point k after the first one-sided exponential filtering

The image parameter value of the image parameter value x[k] before the pixel point k filtering and the previous pixel point k-1 of the pixel point k in the first direction may be subjected to the first one-sided exponential filtering process.

And the range filter coefficient θ[k] of the first one-sided exponential filter processing is expressed as shown in the formula (4):

Of course, it should be understood that if pixel point k-1 is the initial filtered pixel of the first one-sided exponential filtering process, then

Indicates the image parameter value after initial filtering pixel filtering.

Combining the formulas (3) and (4), the image parameter value of the pixel point k after the first one-sided exponential filtering

It can be expressed by formula (5):

Of course, for the second one-sided exponential filtering in the second direction, the range filter coefficient ρ[k] can be expressed by the following formula (6):

ρ[k]=r(x[k],φ[k+1]) (6)

In addition, the image point value φ[k] of the pixel point k after the second one-sided exponential filtering may be the image parameter value x[k] before the pixel point k filtering, and the previous pixel of the pixel point k in the second direction. The point k+1 is represented by the image parameter value φ[k+1] after the second one-sided exponential filter processing and the range filter coefficient φ[k] of the second one-sided exponential filter, as shown in the formula (7):

Φ[k]=(1-ρ[k]λ)x[k]+ρ[k]λφ[k+1] (7)

Similarly, if pixel point k+1 is the initial filtered pixel of the second one-sided exponential filtering process, then

Indicates the image parameter value after initial filtering pixel filtering.

Combined with the formulas (1), (6), and (7), the image parameter value φ[k] of the pixel point k after the second one-sided exponential filtering can be expressed by the formula (8):

Of course, it can be seen from the above formulas (5) and (8) that the double-index filter processing involves multiple operations such as addition, subtraction, multiplication, division, and power operation when calculating each pixel to be filtered. Large, there is a large space for improvement in computing efficiency.

In the embodiment of the present application, the calculation efficiency can be optimized in various ways, the efficiency of image processing is improved, and a better image processing mode is provided for real-time beauty processing.

The following describes the first single-sided exponential filtering process in the first direction as an example. Of course, it should be understood that the second single-sided exponential filtering process in the second direction may also adopt the same or similar method.

Optionally, in an embodiment, in step S302, according to the difference between the image parameter value of the first pixel to be filtered and the image parameter value of the first filtered pixel, and the first pixel to be filtered and the first filtered The distance of the pixel determines the image parameter value of the first pixel to be filtered after the first one-sided exponential filtering process, which can be implemented as follows:

Determining the first pixel to be filtered according to the difference between the image parameter value of the first pixel to be filtered and the image parameter value of the first filtered pixel, and the distance between the first pixel to be filtered and the first filtered pixel The image parameter value after the first one-sided exponential filtering is processed.

In the embodiment of the present application, the image parameter value after filtering the pixel to be filtered is obtained by looking up the table, which can greatly improve the calculation efficiency of the bilateral exponential filtering process. The method of the embodiment of the present application can be applied to a real-time beauty scene, and can be applied to real-time video processing on the desktop or the mobile end to achieve real-time beauty effects.

Of course, it should be understood that there may be a difference in the accuracy requirements of the image parameter values of the pixels to be filtered, the image parameter values of the filtered pixels, and the accuracy requirements of the look-up table. For example, taking the gray value as an example, it is assumed that the image parameter value of the pixel to be filtered and the image parameter value of the filtered pixel point are both 0.01, and the table lookup precision is 0.25, then the filter to be further determined according to the table lookup precision is to be determined. The lookup image parameter value corresponding to the image parameter value of the pixel and the image parameter value of the filtered pixel.

In the embodiment of the present application, for the two table lookup parameters, there may be the following methods for table lookup:

Optionally, as an embodiment, the difference between the image parameter value of the first pixel to be filtered and the image parameter value of the first filtered pixel, and the distance between the first pixel to be filtered and the first filtered pixel The lookup table determines image parameter values of the first pixel to be filtered after the first one-sided exponential filtering process, which can be implemented as follows:

Determining, according to the first lookup table precision value and the image parameter value of the first pixel to be filtered, a first lookup table image parameter value;

Determining a second look-up table image parameter value according to the second look-up table precision value and the image parameter value of the first filtered pixel point;

And determining, according to the first look-up table image parameter value, the second look-up table image parameter value, and the distance, an image parameter value after the first single-sided exponential filtering process is performed on the first pixel to be filtered.

Optionally, as another embodiment, determining, according to an image parameter value of the first pixel to be filtered, an image parameter value of the first filtered pixel, and a distance between the pixel to be filtered and the filtered pixel, The image parameter value of the first pixel to be filtered after the first one-sided exponential filtering process can be implemented as follows:

And determining, according to the image parameter value of the first pixel to be filtered, the second look-up table image parameter value, and the distance, determining, by using a look-up table, the image parameter value of the first pixel to be filtered after the first one-sided exponential filtering process.

Optionally, as another embodiment, determining, according to the image parameter value of the first pixel to be filtered, the image parameter value of the first filtered pixel, and the distance between the pixel to be filtered and the filtered pixel, The image parameter value of the first pixel to be filtered after the first one-sided exponential filtering process can be implemented as follows:

And determining, according to the first look-up table image parameter value, the image parameter after the filtered pixel point is processed by the first one-sided exponential filter, and the distance between the pixel to be filtered and the filtered pixel, and determining the first pixel to be filtered by looking up the table The image parameter value after the first one-sided exponential filtering is processed.

Of course, it should be understood that the look-up process can be accelerated in different ways according to different accuracy requirements. The following is an example of determining the value of the second look-up table image parameter according to the second look-up table precision value and the image parameter value of the first filtered pixel point.

Optionally, as an embodiment, if the second table lookup precision value is 0.1 ⁿ , determining that the image parameter value of the first filtered pixel point is multiplied by an integer part of the image parameter value after 10 ⁿ is the second check. Table image parameter values. Where n is a positive integer.

Since the image parameter value of the first filtered pixel is a calculated value, it is usually expressed in floating point numbers. The precision of a single-precision floating-point number is 7 digits after the decimal point, which is 0.0000001. However, for image algorithms, such precision is often too high. Considering the resolution of the human eye to the color gradation, the accuracy of the algorithm can be appropriately reduced to improve the operation speed. Assume that the 3 digits after the decimal point are reserved, that is, the position to be positioned each time the table is looked up is

Ok, where

Stored as a single-precision floating point number. The improvement effect of the calculation efficiency can be as shown in FIG. 4.

4 is a comparison diagram of the effect of processing the number of frames in one embodiment of the present application. The histogram of the original algorithm represents the number of processing frames obtained by directly calculating the filtered values, and the histogram optimized by the table table indicates the number of processed frames obtained by the table matching optimization to obtain the filtered values. It can be seen from Fig. 4 that the calculation efficiency can be greatly optimized by looking up the table to improve the image processing efficiency and achieve the real-time beauty requirements.

Optionally, as another embodiment, if the second table lookup precision value is 0.5 ⁿ , determining that the image parameter value of the first filtered pixel point is shifted to the left by n bits is the second look-up table image parameter. value. Where n is a positive integer.

For reasons such as computer formation, multiplication and division by an integer of 2 requires only a simple shift. To this end, as described above

The accuracy of the second image parameter value can be further compressed. For example, you can take 0.25 precision, you only need to shift 2 bits to the left. Experiments have shown that such an accuracy range is sufficient to meet the accuracy requirements of the human eye for the resolution of the color gradation, which can satisfy the beauty effect and ensure the real-time beauty of the beauty.

Specifically, according to x[k]∈[0,255], and is an integer,

The precision is 0.25, so a 255*255*4 lookup table can be dynamically generated. In this way, each filtering result only needs one table lookup and several shifting and adding operations. Compared with the original algorithm, almost no operation is needed to obtain the result. If the left shift is 10 bits, it is equal to multiplying by 1024, which is almost the same as the previous 0.001 precision requirement, which not only ensures the accuracy requirement but also avoids the multiplication operation. The improvement effect of the calculation efficiency can be as shown in FIG. 5.

FIG. 5 is a comparison diagram of the effect of processing the number of frames in one embodiment of the present application. The meaning of the histogram corresponding to the original algorithm and table lookup optimization in Fig. 5 is the same as that of the corresponding histogram in Fig. 4. In addition, the floating-point integer optimization of FIG. 5 represents the number of processed frames obtained by the look-up operation after the shift operation. As can be seen from Figure 5, the direct shift operation is much faster than the multiplication operation. In the embodiment of the present application, by combining the table lookup and the shift operation, the image processing efficiency can be further improved, thereby further improving the real-time performance of the image beauty.

Optionally, as another embodiment, if the second table lookup precision value is 2 ⁿ , determining that the image parameter value of the first filtered pixel point is shifted right by n bits is the second look-up table image parameter. value. Where n is a positive integer.

For example, if the second lookup table accuracy value requirement is 4, then the second image parameter value needs to be shifted to the right by 2 bits.

By using the right shift method, the division operation can be avoided, and the calculation efficiency can be improved.

In addition, it should be understood that in the process of performing bilateral exponential filtering processing on the image to be processed, the image to be processed may also be subjected to gain filtering processing.

Optionally, before determining the output image of the image to be processed, the method further includes: determining, according to the image parameter value before filtering each pixel of the image to be processed, a gain filtering result of each pixel of the image to be processed;

Determining, according to the result of the first bilateral index filtering process, the output image of the image to be processed, according to the result of the first bilateral exponential filtering process, and the gain filtering result of each pixel of the image to be processed, determining the The output image of the image to be processed.

For example, for pixel k, the gain-filtered result g[k] can be expressed by the following formula (9):

g[k]=mu×x[k] (9)

Where mu represents the gain filter coefficient.

Finally, the filtered results are grouped to obtain the image parameter value a[k] which is finally output by the pixel point k. Specifically, as shown in formula (15):

Of course, it should be understood that for a given input parameter space relative delay, the gain filtered value is only a multiplication operation, and is also suitable for table lookup optimization.

Specifically, the gain filtering result of each pixel of the image to be processed is determined according to the image parameter value before filtering of each pixel of the image to be processed, and the specific implementation may be:

The gain filtering result of each pixel of the image to be processed is determined by looking up the table according to the image parameter value before filtering of each pixel of the image to be processed.

For example, in order to better integrate with the method of obtaining the filtered image parameter value after the one-sided exponential filtering process by looking up the table, the result of the lookup mapping table can be shifted by 10 bits to the left, which not only ensures the accuracy requirement but also avoids the multiplication operation. In the embodiment of the present application, the gain filtering process is performed by looking up the table, thereby further improving the image processing efficiency, thereby further improving the real-time performance of the image beauty.

FIG. 6 is a comparison diagram of the effect of processing the number of frames in still another embodiment of the present application. The meaning of the histogram corresponding to the original algorithm and the table lookup optimization in FIG. 6 is the same as that of the corresponding histogram in FIG. 4. The floating point integer optimization in FIG. 6 has the same meaning as the corresponding histogram in FIG. In addition, the optimization of FIG. 6 indicates that the table is looked up after the shift operation, and the number of processing frames of the filtered value is also obtained by looking up the table in the gain filtering stage. As can be seen from Figure 6, in the case of optimization, it is nearly 10 times higher than the original algorithm. The table below shows the time-to-time comparison of several algorithms for processing one frame of image on different operating platforms.

As can be seen from the above table, the time-of-use comparisons using different algorithms are extremely different.

Of course, it should be understood that the foregoing table lookup operation is only for the table lookup operation performed during the first one-sided exponential filter processing, but is also applicable to the second one-sided exponential filter processing. In addition, the look-up table method in the embodiment of the present application may also be used in other filtering algorithms such as Gaussian filtering, and details are not described herein again.

FIG. 7 is a comparison diagram of filtering effects under an optimization method of an embodiment of the present application. As can be seen from FIG. 7, the image processed by the image processing method of the embodiment of the present application has a very significant denoising and dermabrasion effect.

Optionally, the direction of the first bilateral exponential filtering process is parallel to the row of the image to be processed; or the direction of the first bilateral exponential filtering process is parallel to the column of the image to be processed.

It should be understood that by performing bilateral exponential filtering processing in the horizontal direction or the vertical direction, segmentation of an image to be processed is facilitated for parallel processing.

It should be understood that, in the embodiment of the present application, the above method may be performed by using an FIR filter. For the filtering process in the one-dimensional direction, a one-dimensional FIR filter can be used, and for the filtering process in the two-dimensional direction, a two-dimensional FIR filter can be used.

Of course, it should be understood that for images, the FIR filter is well suited for parallel processing. The image processing speed can be speeded up by simultaneously processing 2 or n image pixel rows or simultaneously processing 2 or n image pixel columns, thereby further improving the real-time performance of the image.

At this time, the step S301 is specifically implemented as: performing a fragmentation process on the input image according to the number of processors for image processing to obtain a plurality of the to-be-processed images, wherein the slice position of the slice processing of the input image is parallel to Processing direction when the first bilateral exponential filtering process is performed on the image to be processed;

After step S303, the method further comprises: synthesizing the output image filtered by the input image according to the output images of the plurality of images to be processed.

Figure 8 is a schematic illustration of parallel image processing of one embodiment of the present application. A specific implementation manner is shown in FIG. 8. The image processing system in the embodiment of the present application can be divided into an algorithm initialization module and an algorithm processing module.

In the algorithm initialization module, after the startup algorithm is initialized, the following steps may be included:

(1) Get the number of CPUs.

By taking the number of CPUs used for image processing, it can be determined that several parallel threads can be created.

(2) Create a parallel thread structure, etc.

One to n processing threads are created according to the number of CPUs used for image processing.

(3) Run the thread by running the module.

If there are multiple threads, run multiple parallel threads by running the module and summarize the output of each thread; if there is only one thread, run the module by running the module.

In the algorithm processing module, after inputting the image, the following steps may be included:

(1) Determine whether or not to use the parallel structure based on the initialization settings.

If the algorithm initialization module only creates one processing thread, then obviously no parallel structure is needed; if the algorithm initialization module creates multiple processing threads, then a parallel structure is needed.

(2) Image segmentation processing is performed depending on whether or not a parallel structure is used.

If there is only one thread, no fragmentation is required, or only one slice is divided; if there are n threads, the input image is divided into n slices.

(3) Send the fragmented image to the running module for processing.

(4) Receive the processing result of each thread and generate a processed image.

Step 4 is required if the initialization settings decide to use a parallel structure. The processor also needs to combine the processed results of the multiple parallel threads to generate a processed image;

If the initialization setting decides not to use the parallel structure, step 4 may not be performed.

(5) Output image

Of course, it should be understood that the method performed by each thread in the running module of FIG. 8 may refer to the method in the embodiment shown in FIG. 3, and details are not described herein again.

Of course, it should be understood that the above method is only filtering in one dimension direction. For two-dimensional images, it is often necessary to filter in two dimensions, that is, in addition to lateral filtering of the pixels, the pixels need to be longitudinally filtered. The specific algorithm of the longitudinal filtering can refer to the foregoing transverse filtering algorithm, and replace the horizontal coordinate parameter with the longitudinal coordinate parameter.

Optionally, the to-be-processed column/row in the image to be processed that is perpendicular to the direction of the first bilateral index filtering process includes the filtered pixel at the endpoint and the at least one pixel to be filtered; before the step S303, the method further includes:

And in a direction perpendicular to a direction of the first bilateral exponential filtering process, performing a second bilateral exponential filtering process on the to-be-processed image from an endpoint of the to-be-processed column/row of the image to be processed, wherein the second bilateral exponential filtering The processing part is based on: a difference between an image parameter value of the filtered pixel and an image parameter value of the pixel to be filtered, and a distance between the filtered pixel and the pixel to be filtered;

Determining the output image of the image to be processed according to the result of the first bilateral index filtering process comprises: determining an output of the image to be processed according to a result of the first bilateral exponential filtering process and a result of the second bilateral exponential filtering process image.

In the embodiment of the present application, by performing bilateral exponential filtering processing in two directions perpendicular to each other, the image can be filtered from two different dimensions, so that the output image has better edge-preserving effect and denoising effect, and further Improve the display quality of the output image.

FIG. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to FIG. 9, at the hardware level, the electronic device includes a processor, optionally including an internal bus, a network interface, and a memory. The memory may include a memory, such as a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory. Of course, the electronic device may also include hardware required for other services.

The processor, the network interface, and the memory may be interconnected by an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended) Industry Standard Architecture, extending the industry standard structure) bus. The bus can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, only one double-headed arrow is shown in Figure 9, but it does not mean that there is only one bus or one type of bus.

Memory for storing programs. In particular, the program can include program code, the program code including computer operating instructions. The memory can include both memory and non-volatile memory and provides instructions and data to the processor.

The processor reads the corresponding computer program from the non-volatile memory into memory and then operates to form an image processing device at a logical level. The processor executes the program stored in the memory and is specifically used to perform the following operations:

Obtaining a to-be-processed image, the to-be-processed row/column of the to-be-processed image includes the filtered pixel at the endpoint and at least one pixel to be filtered;

The method performed by the image processing apparatus disclosed in the embodiment shown in FIG. 3 of the present application may be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method may be completed by an integrated logic circuit of hardware in a processor or an instruction in a form of software. The above processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; or may be a digital signal processor (DSP), dedicated integration. Application Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component. The methods, steps, and logical block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general purpose processor may be a microprocessor or the processor or any conventional processor or the like. The steps of the method disclosed in the embodiments of the present application may be directly implemented by the hardware decoding processor, or may be performed by a combination of hardware and software modules in the decoding processor. The software module can be located in a conventional storage medium such as random access memory, flash memory, read only memory, programmable read only memory or electrically erasable programmable memory, registers, and the like. The storage medium is located in the memory, and the processor reads the information in the memory and combines the hardware to complete the steps of the above method.

The electronic device can also perform the method of FIG. 3 and implement the functions of the image processing apparatus in the embodiment shown in FIG. 3. The embodiments of the present application are not described herein again.

Of course, in addition to the software implementation, the electronic device of the present application does not exclude other implementation manners, such as a logic device or a combination of software and hardware, etc., that is, the execution body of the following processing flow is not limited to each logical unit. It can also be hardware or logic.

The embodiment of the present application further provides a computer readable storage medium storing one or more programs, the one or more programs including instructions that are executed by an electronic device including a plurality of applications The electronic device can be caused to perform the method of the embodiment shown in FIG.

FIG. 10 is a schematic structural diagram of an image processing apparatus 1000 according to an embodiment of the present application. Referring to FIG. 10, in a software implementation, the image processing apparatus may include:

The obtaining unit 1010 is configured to obtain an image to be processed, where the to-be-processed row/column of the image to be processed includes the filtered pixel at the endpoint and at least one pixel to be filtered;

The processing unit 1020 performs a first bilateral exponential filtering process on the to-be-processed image from the endpoint of the to-be-processed row/column of the to-be-processed image, where the first bilateral exponential filtering process is based on: image parameters of the filtered pixel The difference between the value and the image parameter value of the pixel to be filtered, and the distance between the filtered pixel and the pixel to be filtered;

The determining unit 1030 determines an output image of the image to be processed according to the result of the first bilateral index filtering process.

In the embodiment of the present application, the image processing apparatus 1000 performs bilateral exponential filtering processing on the image to be processed according to the pixel point distance and the image parameter value of the pixel point, fully considering the influence of the distance and the image parameter value on the pixel point filtering, thereby enabling the output to be made. The image has better edge protection and denoising effects, which improves the display quality of the output image.

It should be understood that, in the embodiment of the present application, when performing the first bilateral exponential filtering process, the image to be processed may be preprocessed such that both ends of each to-be-processed row/column of the to-be-processed image respectively include a first bilateral index. The initial filtered pixel point of the single-sided exponential filtering process starting from the end in the filtering process; or, in the image to be processed acquired by the acquiring unit, the two ends of each to-be-processed row/column of the image to be processed respectively include the first The initial filtered pixel of the one-sided exponential filtering process starting with the end in a bilateral exponential filtering process.

It should be understood that the first bilateral exponential filtering process includes a first one-sided exponential filtering process in a first direction from a first end to a second end of the to-be-processed row/column of the image to be processed, and from the image to be processed Processing a second one-sided exponential filtering process in a second direction from the second end of the row/column to the first end; the processing unit 1020 is specifically configured according to the image parameter value of the first pixel to be filtered and the image of the first filtered pixel a difference between the parameter values, and a distance between the first pixel to be filtered and the first filtered pixel, determining an image parameter value of the first pixel to be filtered after the first one-sided exponential filtering, wherein the first to be filtered The pixel is the next pixel to be filtered in the first direction of the first filtered pixel.

Further, the processing unit 1020 is specifically configured to: according to the difference between the image parameter value of the first pixel to be filtered and the image parameter value of the first filtered pixel, and the first pixel to be filtered and the first filtered pixel The distance, the image parameter value of the first pixel to be filtered after the first one-sided exponential filtering process is determined by looking up the table.

Optionally, in a specific implementation manner, the processing unit 1020 is configured to: according to the difference between the image parameter value of the first pixel to be filtered and the image parameter value of the first filtered pixel, and the first pixel to be filtered and the first The distance of a filtered pixel point is determined by looking up the image parameter value of the first pixel to be filtered after the first one-sided exponential filtering process, and the specific implementation is:

The processing unit 1020 determines a first look-up table image parameter value according to the first table lookup precision value and the image parameter value of the first pixel to be filtered;

The processing unit 1020 determines a second look-up table image parameter value according to the second table lookup precision value and the image parameter value of the first filtered pixel point;

The processing unit 1020 determines, according to the first look-up table image parameter value, the second look-up table image parameter value, and the distance, the image parameter value of the first pixel to be filtered after the first one-sided exponential filtering process.

Optionally, in another specific implementation manner, the processing unit 1020 is configured to: according to the difference between the image parameter value of the first pixel to be filtered and the image parameter value of the first filtered pixel, and the first pixel to be filtered and The distance of the first filtered pixel point is determined by looking up the image parameter value of the first pixel to be filtered after the first one-sided exponential filtering process, and the specific implementation is:

The processing unit 1020 determines, according to the image parameter value of the first pixel to be filtered, the second look-up table image parameter value, and the distance, the image parameter of the first pixel to be filtered after the first one-sided exponential filtering process is determined by looking up the table. value.

Optionally, in another specific implementation, the processing unit 1020 is configured to: according to the difference between the image parameter value of the first pixel to be filtered and the image parameter value of the first filtered pixel, and the first pixel to be filtered and The distance of the first filtered pixel point is determined by looking up the image parameter value of the first pixel to be filtered after the first one-sided exponential filtering process, and the specific implementation is:

The processing unit 1020 determines, according to the first look-up table image parameter value, the image parameter after the filtered pixel point passes the first one-sided exponential filtering process, and the distance between the pixel to be filtered and the filtered pixel point, and determines the first by looking up the table. The image parameter value after the first pixel is subjected to the first one-sided exponential filtering.

Further, the processing unit 1020 determines the second look-up table image parameter value according to the second table lookup precision value and the image parameter value of the first filtered pixel point, which may be specifically implemented as:

When the second lookup table precision value is 0.1 ⁿ , the processing unit 1020 determines that the image parameter value of the first filtered pixel point is multiplied by 10 ⁿ and the integer part of the image parameter value is the second look-up table image parameter value;

Alternatively, when the second table lookup precision value is 0.5 ⁿ , the processing unit 1020 determines that the integer part of the image parameter value of the first filtered pixel point is shifted to the left by n bits as the second look-up table image parameter value;

Alternatively, when the second table lookup precision value is 2 ⁿ , the processing unit 1020 determines that the integer part of the image parameter value of the first filtered pixel point is shifted to the right by n bits, and is the second look-up table image parameter value;

Where n is a positive integer.

It should be understood that the processing unit 1020 further determines, according to the difference between the image parameter value of the second pixel to be filtered and the image parameter value of the second filtered pixel, and the distance between the second pixel to be filtered and the second filtered pixel. The image parameter value after the second pixel to be filtered is subjected to the second one-sided exponential filtering; the image parameter value after the pixel is subjected to the first one-sided exponential filtering, and the pixel is subjected to the second one-sided exponential filtering process The image parameter value determines an image parameter value of the pixel after the first bilateral exponential filtering process.

It should be understood that the first bilateral index filtering processing is based on: a difference between an image parameter value of the filtered pixel point and an image parameter value of the pixel to be filtered, and a distance between the filtered pixel point and the pixel to be filtered, which may be specifically implemented as :

The range filter function of the first bilateral exponential filter processing is based in part on the difference between the image parameter value of the filtered pixel and the image parameter value of the pixel to be filtered, and the distance between the filtered pixel and the pixel to be filtered.

More specifically, the range filter function of the first one-sided exponential filter is partially based on: a difference between an image parameter value of the filtered pixel and an image parameter value of the pixel to be filtered, and a filtered pixel and a pixel to be filtered. The range of the second-sided exponential filter processing is based on: the difference between the image parameter value of the filtered pixel and the image parameter value of the pixel to be filtered, and the filtered pixel and the pixel to be filtered. distance.

Optionally, the processing unit 1020 further performs a second bilateral exponential filtering process on the image to be processed in a direction perpendicular to a direction of the first bilateral exponential filtering process, where the second bilateral exponential filtering process is partially based on: the filtered pixel The difference between the image parameter value of the point and the image parameter value of the pixel to be filtered, and the distance between the filtered pixel point and the pixel to be filtered;

The determining unit 1030 determines an output image of the image to be processed according to the result of the first bilateral exponential filtering process and the result of the second bilateral exponential filtering process.

Of course, it should be understood that the processing unit 1020 performs the second bilateral exponential filtering process, and may also perform preprocessing on the processing, so that both ends of each to-be-processed column/row of the to-be-processed image respectively include the second bilateral exponential filtering process. An initial filtered pixel that is processed by the one-sided exponential filtering that starts at the end; or, in the image to be processed acquired by the acquiring unit 1010, both ends of each to-be-processed column/row of the image to be processed include a second bilateral index The initial filtered pixel point of the filtering process that is processed by the one-sided exponential filtering starting at the end.

Alternatively, the image processing apparatus may further include a synthesizing unit 1040. The obtaining unit 1010 performs a fragmentation process on the input image according to the number of processors used for image processing to obtain a plurality of the to-be-processed images, wherein the sliced position of the sliced image of the input image is parallel to the image to be processed. The processing direction when the first bilateral exponential filtering process is performed; the synthesizing unit 1040 synthesizes the output image filtered by the input image according to the output images of the plurality of to-be-processed images.

Optionally, the determining unit 1030 further determines a gain filtering result of each pixel of the to-be-processed image according to the image parameter value before filtering the pixel of the image to be processed; wherein the determining unit 1030 is configured according to the first bilateral exponential filtering As a result, the output image of the image to be processed is determined by determining the output image of the image to be processed according to the result of the first bilateral index filtering process and the gain filtering result of each pixel of the image to be processed.

Further, the determining unit 1030 may determine, according to the image parameter value before filtering each pixel of the image to be processed, a gain filtering result of each pixel of the image to be processed by using a lookup table.

The embodiment of the present application further provides an image processing system including the image processing device 1000 in the embodiment shown in FIG. 10 or the image processing device stored in the electronic device in the embodiment shown in FIG.

11 is a flow chart of a method of image processing according to an embodiment of the present application. The method of Figure 11 is performed by an image processing device. In the embodiment of the present application, the image processing device may be a processor, a graphics processor, or a filter such as a finite-length unit impulse response (FIR) filter. The method of Figure 11 can include:

S1101: Acquire an image to be processed, where the to-be-processed row/column includes a filtered pixel point and at least one pixel to be processed;

S1102: Perform a first bilateral exponential filtering process on the to-be-processed row/column of the image to be processed, where the first bilateral exponential filtering process is partially based on: an image parameter value of the filtered pixel point and an image parameter value of the pixel to be filtered. Difference, and the distance between the filtered pixel and the pixel to be filtered;

S1103. Determine an output image of the image to be processed according to the result of the first bilateral index filtering process.

It should be understood that, in the embodiment of the present application, except that the filtered node in the image to be processed is not limited to the end position of the row/column to be processed, and the pixel position to be processed is not limited to the end position of the row/column to be processed, other execution steps are performed. For example, performing a first bilateral exponential filtering process on the to-be-processed row/column of the image to be processed, and determining an output image of the to-be-processed image according to the result of the first bilateral exponential filtering process, and referring to the embodiment shown in FIG. The embodiments of the present application are not described herein again.

An embodiment of the present application further provides an electronic device, including a processor;

A memory arranged to store computer executable instructions that, when executed, cause the processor to perform the method of the embodiment shown in FIG.

The embodiment of the present application further provides a computer readable storage medium storing one or more programs, the one or more programs, when executed by an electronic device, enable the electronic device to execute The method in the embodiment shown in FIG.

In summary, the above description is only the preferred embodiment of the present application, and is not intended to limit the scope of the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of this application are intended to be included within the scope of the present application.

The system, device, module or unit illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product having a certain function. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or A combination of any of these devices.

Computer readable media includes both permanent and non-persistent, removable and non-removable media. Information storage can be implemented by any method or technology. The information can be computer readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory. (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disk read only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, Magnetic tape cartridges, magnetic tape storage or other magnetic storage devices or any other non-transportable media can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary storage of computer readable media, such as modulated data signals and carrier waves.

It is also to be understood that the terms "comprises" or "comprising" or "comprising" or any other variations are intended to encompass a non-exclusive inclusion, such that a process, method, article, Other elements not explicitly listed, or elements that are inherent to such a process, method, commodity, or equipment. An element defined by the phrase "comprising a ...", without further limitation, does not exclude the presence of additional equivalent elements in the process, method, article, or device that comprises the element.

The various embodiments in the specification are described in a progressive manner, and the same or similar parts between the various embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description of the method embodiment.

Claims

An image processing method, comprising:

Obtaining a to-be-processed image, the to-be-processed row/column of the to-be-processed image includes a filtered pixel point at the endpoint and at least one pixel to be filtered;

Performing a first bilateral exponential filtering process on the to-be-processed image from an endpoint of the to-be-processed row/column of the to-be-processed image, wherein the first bilateral exponential filtering processing portion is based on: an image parameter value of the filtered pixel a difference from an image parameter value of a pixel to be filtered, and a distance between the filtered pixel and the pixel to be filtered;

And determining an output image of the image to be processed according to a result of the first bilateral index filtering process.
The method of claim 1 wherein

The first bilateral exponential filtering process includes a first one-sided exponential filtering process in a first direction from a first end to a second end of the to-be-processed row/column of the image to be processed, and a to-be-processed image from the to-be-processed image a second one-sided exponential filtering process in a second direction from the second end of the row/column to the first end;

Performing a first bilateral exponential filtering process on the image to be processed, including: a difference between an image parameter value of the first pixel to be filtered and an image parameter value of the first filtered pixel, and a first pixel to be filtered and the first Determining, by the distance of a filtered pixel, an image parameter value of the first pixel to be filtered after the first one-sided exponential filtering process, wherein the first pixel to be filtered is the first filtered pixel The next pixel to be filtered in one direction.
The method of claim 2 wherein

Performing a first bilateral exponential filtering process on the image to be processed, including: a difference between an image parameter value of the first pixel to be filtered and an image parameter value of the first filtered pixel, and a first pixel to be filtered and the first The distance of a filtered pixel point is determined by looking up a table to determine an image parameter value of the first pixel to be filtered after the first one-sided exponential filtering process.
The method of claim 3 wherein:

Determining, according to the image parameter value of the first pixel to be filtered, the image parameter value of the first filtered pixel, and the distance between the pixel to be filtered and the filtered pixel, determining, by using a table look, that the first pixel to be filtered passes the first single Image parameter values after edge index filtering, including:

Determining, according to the first lookup table precision value and the image parameter value of the first pixel to be filtered, a first lookup table image parameter value;

Determining a second look-up table image parameter value according to the second look-up table precision value and the image parameter value of the first filtered pixel point;

And determining, according to the first look-up table image parameter value, the second look-up table image parameter value, and the distance, an image parameter value after the first single-sided exponential filtering process is performed on the first pixel to be filtered.
The method of claim 3 wherein:

Determining, according to the image parameter value of the first pixel to be filtered, the image parameter value of the first filtered pixel, and the distance between the pixel to be filtered and the filtered pixel, determining, by using a table look, that the first pixel to be filtered passes the first single Image parameter values after edge index filtering, including:

Determining a second look-up table image parameter value according to the second look-up table precision value and the image parameter value of the first filtered pixel point;

Determining, according to an image parameter value of the first pixel to be filtered, the second table-view image parameter value, and the distance, determining, by using a look-up table, an image parameter value of the first pixel to be filtered after the first one-sided exponential filtering process .
The method of claim 3 wherein:

Determining, according to the image parameter value of the first pixel to be filtered, the image parameter value of the first filtered pixel, and the distance between the pixel to be filtered and the filtered pixel, determining, by using a table look, that the first pixel to be filtered passes the first single Image parameter values after edge index filtering, including:

Determining, according to the first lookup table precision value and the image parameter value of the first pixel to be filtered, a first lookup table image parameter value;

And determining, according to the first look-up table image parameter value, the image parameter after the filtered pixel point is processed by the first one-sided exponential filtering, and the distance between the pixel to be filtered and the filtered pixel, and determining the first waiting by searching the table The image parameter value after filtering the pixel point through the first one-sided exponential filtering process.
A method according to claim 5 or claim 6 wherein:

Determining the second look-up table image parameter value according to the second look-up table precision value and the image parameter value of the first filtered pixel point, including:

When the second table lookup precision value is 0.1n, determining an image parameter value of the first filtered pixel point multiplied by an integer part of the image parameter value after 10n, a second lookup table image parameter value; or

When the second table lookup precision value is 0.5n, determining that the image parameter value of the first filtered pixel point is shifted to the left by n bits is the second look-up table image parameter value; or

When the second table lookup precision value is 2n, determining that the image parameter value of the first filtered pixel point is shifted right by n bits is the second look-up table image parameter value;

Where n is a positive integer.
A method according to any of claims 2-6, wherein

Performing a first bilateral exponential filtering process on the to-be-processed image further includes:

Determining, according to a difference between an image parameter value of the second pixel to be filtered and an image parameter value of the second filtered pixel, and a distance between the second pixel to be filtered and the second filtered pixel, determining that the second pixel to be filtered passes Image parameter values after the second one-sided exponential filter processing;

Determining, according to the image parameter value after the pixel is subjected to the first one-sided exponential filtering process, and the image parameter value of the pixel point after the second one-sided exponential filtering process, determining that the pixel point passes the first bilateral exponential filtering process Image parameter values after.
The method of any of claims 1-6, wherein

The first bilateral index filtering processing part is based on: a difference between an image parameter value of the filtered pixel point and an image parameter value of the pixel to be filtered, and a distance between the filtered pixel point and the pixel to be filtered, and the specific implementation is:

The range filter function of the first bilateral exponential filter processing is based in part on a difference between an image parameter value of the filtered pixel and an image parameter value of the pixel to be filtered, and a distance between the filtered pixel and the pixel to be filtered.
The method of any of claims 1-6, wherein

The to-be-processed column/row in the image to be processed that is perpendicular to the first bilateral exponential filtering processing direction includes a filtered pixel located at the endpoint and at least one pixel to be filtered;

Before determining the output image of the image to be processed according to the result of the first bilateral index filtering process, the method further includes:

And performing, in a direction perpendicular to a direction of the first bilateral exponential filtering process, a second bilateral exponential filtering process on the image to be processed starting from an endpoint of the to-be-processed column/row of the image to be processed, wherein the second The bilateral index filtering processing is based in part on: a difference between an image parameter value of the filtered pixel and an image parameter value of the pixel to be filtered, and a distance between the filtered pixel and the pixel to be filtered;

Determining, according to a result of the first bilateral exponential filtering process, the output image of the image to be processed includes: determining, according to a result of the first bilateral exponential filtering process, and a result of the second bilateral exponential filtering process The output image of the image to be processed.
The method of any of claims 1-6, wherein

The direction of the first bilateral exponential filtering process is parallel to the row of the image to be processed; or

The direction of the first bilateral exponential filtering process is parallel to the column of the image to be processed.
The method of claim 11 wherein:

Acquiring the image to be processed includes: performing a fragmentation process on the input image according to the number of processors used for image processing to obtain a plurality of the to-be-processed images, wherein a slice position of the slice processing of the input image is parallel to the opposite Treating a processing direction when the processed image performs the first bilateral exponential filtering process;

The method further includes: after determining the output image of the image to be processed, the method further includes:

And outputting the output image filtered by the input image according to the output images of the plurality of the to-be-processed images.
The method of any of claims 1-6, wherein

Before determining the output image of the image to be processed, the method further includes: determining a gain filtering result of each pixel of the image to be processed according to the image parameter value before filtering of each pixel of the image to be processed;

Determining, according to a result of the first bilateral exponential filtering process, the output image of the image to be processed includes: determining, according to a result of the first bilateral exponential filtering process, and a gain filtering result of each pixel of the image to be processed, An output image of the image to be processed.
The method according to claim 13, wherein determining a gain filtering result of each pixel of the image to be processed according to the image parameter value before filtering of each pixel of the image to be processed comprises:

And determining, according to the image parameter value before filtering each pixel of the image to be processed, a gain filtering result of each pixel of the image to be processed by using a lookup table.
An image processing apparatus, comprising:

Acquiring a unit to obtain a to-be-processed image, where the to-be-processed row/column of the to-be-processed image includes a filtered pixel point at the endpoint and at least one pixel to be filtered;

a processing unit that performs a first bilateral exponential filtering process on the to-be-processed image from an endpoint of the to-be-processed row/column of the to-be-processed image, wherein the first bilateral exponential filtering processing portion is based on: a filtered pixel point a difference between an image parameter value and an image parameter value of the pixel to be filtered, and a distance between the filtered pixel point and the pixel to be filtered;

a determining unit that determines an output image of the image to be processed according to a result of the first bilateral index filtering process.
An electronic device, comprising:

Processor;

A memory arranged to store computer executable instructions that, when executed, cause the processor to perform the following operations:

Obtaining a to-be-processed image, the to-be-processed row/column of the to-be-processed image includes a filtered pixel point at the endpoint and at least one pixel to be filtered;

Performing a first bilateral exponential filtering process on the to-be-processed image from an endpoint of the to-be-processed row/column of the to-be-processed image, wherein the first bilateral exponential filtering processing portion is based on: an image parameter value of the filtered pixel a difference from an image parameter value of a pixel to be filtered, and a distance between the filtered pixel and the pixel to be filtered;

And determining an output image of the image to be processed according to a result of the first bilateral index filtering process.
A computer readable storage medium, wherein the computer readable storage medium stores one or more programs, the one or more programs comprising instructions that are executed by an electronic device that includes a plurality of applications When the electronic device is caused to perform the following operations:

Obtaining a to-be-processed image, the to-be-processed row/column of the to-be-processed image includes a filtered pixel point at the endpoint and at least one pixel to be filtered;

Performing a first bilateral exponential filtering process on the to-be-processed image from an endpoint of the to-be-processed row/column of the to-be-processed image, wherein the first bilateral exponential filtering processing portion is based on: an image parameter value of the filtered pixel a difference from an image parameter value of a pixel to be filtered, and a distance between the filtered pixel and the pixel to be filtered;

And determining an output image of the image to be processed according to a result of the first bilateral index filtering process.
An image processing method, comprising:

Obtaining a to-be-processed image, the to-be-processed row/column of the to-be-processed image includes a filtered pixel point and at least one pixel to be filtered;

Performing a first bilateral exponential filtering process on the to-be-processed row/column of the image to be processed, wherein the first bilateral exponential filtering process is partially based on: an image parameter value of the filtered pixel point and an image parameter value of the pixel to be filtered Difference, and the distance between the filtered pixel and the pixel to be filtered;

And determining an output image of the image to be processed according to a result of the first bilateral index filtering process.