CN111861942A

CN111861942A - Noise reduction method and device, electronic equipment and storage medium

Info

Publication number: CN111861942A
Application number: CN202010763077.XA
Authority: CN
Inventors: 肖雄; 张帆
Original assignee: Shenzhen TetrasAI Technology Co Ltd
Current assignee: Shenzhen TetrasAI Technology Co Ltd
Priority date: 2020-07-31
Filing date: 2020-07-31
Publication date: 2020-10-30
Also published as: WO2022021932A1

Abstract

The present disclosure relates to a noise reduction method and apparatus, an electronic device, and a storage medium, the method including: converting a noise reduction mask map of an image to be subjected to noise reduction into a chrominance information map, wherein the noise reduction mask map comprises noise reduction force values of pixel points contained in the image to be subjected to noise reduction; inputting the chromaticity information diagram into a strength control module; and controlling the noise reduction strength for carrying out noise reduction treatment on the image to be subjected to noise reduction through the strength control module to obtain the image subjected to noise reduction. The disclosed embodiments may enable flexible image noise reduction.

Description

Noise reduction method and device, electronic equipment and storage medium

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a noise reduction method and apparatus, an electronic device, and a storage medium.

Background

Because the noise in the image is not uniform and the sensitivity of human eyes to the noise is different in different areas, different noise reduction degrees are required to be adopted for noise reduction in different areas of the image. For example, because human eyes are more sensitive to noise in a flat region and a face region, the flat region and the face region in an image need to be denoised with a higher denoising strength, and other regions in the image need to be denoised with a lower denoising strength.

Disclosure of Invention

The disclosure provides a noise reduction method and device, an electronic device and a storage medium.

According to an aspect of the present disclosure, there is provided a noise reduction method including:

converting a noise reduction mask map of an image to be subjected to noise reduction into a chrominance information map, wherein the noise reduction mask map comprises noise reduction force values of pixel points contained in the image to be subjected to noise reduction;

inputting the chromaticity information diagram into a strength control module;

and controlling the noise reduction strength for carrying out noise reduction treatment on the image to be subjected to noise reduction through the strength control module to obtain the image subjected to noise reduction.

In a possible implementation manner, the converting the noise reduction mask map of the image to be noise reduced into the chrominance information map includes:

aiming at each pixel point contained in the image to be denoised:

determining a chromaticity interval corresponding to the pixel point according to the noise reduction degree value of the pixel point;

and determining the chromatic value corresponding to the pixel point according to the chromatic interval corresponding to the pixel point.

The noise reduction value of the pixel point is converted into a chromatic value, so that the noise reduction of different noise reduction forces in different areas is realized by utilizing the force control module.

In a possible implementation manner, the determining, according to the noise reduction degree value of the pixel point, a chromaticity interval corresponding to the pixel point includes:

acquiring a mapping relation of the chrominance interval and the noise reduction degree value converted by the strength control module;

and determining the chromaticity interval corresponding to the pixel point based on the mapping relation and the noise reduction degree value of the pixel point.

And determining the converted chromaticity interval according to the mapping relation of the chromaticity interval and the noise reduction degree value converted by the strength control module, so that the strength control module is favorable for realizing noise reduction of different noise reduction degrees in different regions.

In one possible implementation, before converting the noise reduction mask map of the image to be noise reduced into the chrominance information map, the method further includes:

determining a first region and a second region in the image to be denoised;

respectively setting a first noise reduction degree value and a second noise reduction degree value for pixel points contained in the first region and the second region;

and constructing a noise reduction mask image of the image to be subjected to noise reduction according to the first noise reduction strength value and the second noise reduction strength value.

The flexibility of noise reduction can be further improved by dividing the noise reduction image into regions and respectively setting the noise reduction power value of each region.

In a possible implementation manner, the setting a first noise reduction value and a second noise reduction value for pixel points included in the first region and the second region respectively includes:

and under the condition that the first area is a static area and the second area is a dynamic area, determining the first noise reduction power value according to brightness information corresponding to pixel points contained in the first area, and determining the second noise reduction power value according to motion information corresponding to pixel points contained in the second area.

Therefore, on the basis of reducing the influence on the static area, the noise caused by the movement can be effectively removed.

under the condition that the first area is a multi-frame fusion area and the second area is an unfused area, determining the first noise reduction degree value according to the corresponding fusion degree and/or variance of pixel points contained in the first area; determining the second noise reduction power value according to brightness information corresponding to pixel points contained in the second region; the multi-frame fusion area is used for representing an area containing information of a plurality of images, and the non-fusion area is used for representing an area containing information of a single image.

Therefore, on the basis of reducing the influence on the unfused area, the noise caused by image fusion can be effectively removed.

under the condition that the first region is a highlight region and the second region is a non-highlight region, respectively determining a first noise reduction strength value and a second noise reduction strength value according to corresponding brightness values of pixel points contained in the first region and the second region, wherein the first noise reduction strength value is greater than the second noise reduction strength value;

the highlight area is used for representing an area formed by pixel points with brightness larger than a brightness threshold value in the image to be denoised; the non-highlight region is used for representing the region except the highlight region in the image to be denoised.

Thus, the noise in the high light region can be effectively removed while reducing the influence on the non-high light region.

and under the condition that the first area is a target object and the second area is a background area, determining the first noise reduction power value according to the feature map of the first area, and determining the second noise reduction power value according to the corresponding brightness value of the pixel points contained in the second area.

Thus, the noise of the target object can be effectively removed on the basis of reducing the influence on the background area.

According to an aspect of the present disclosure, there is provided a noise reduction apparatus including:

the conversion module is used for converting a noise reduction mask map of an image to be subjected to noise reduction into a chrominance information map, wherein the noise reduction mask map comprises noise reduction force values of pixel points contained in the image to be subjected to noise reduction;

the input module is used for inputting the chromaticity information diagram into the strength control module;

and the control module is used for controlling the noise reduction strength for carrying out noise reduction treatment on the image to be subjected to noise reduction through the strength control module to obtain the image subjected to noise reduction.

In one possible implementation, the conversion module is further configured to:

aiming at each pixel point contained in the image to be denoised:

In one possible implementation, the apparatus further includes:

the determining module is used for determining a first region and a second region in the image to be subjected to noise reduction;

the setting module is used for respectively setting a first noise reduction degree value and a second noise reduction degree value for pixel points contained in the first area and the second area;

and the construction module is used for constructing a noise reduction mask map of the image to be subjected to noise reduction according to the first noise reduction strength value and the second noise reduction strength value.

In one possible implementation, the setting module is further configured to:

According to an aspect of the present disclosure, there is provided an electronic device including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the memory-stored instructions to perform the above-described method.

According to an aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the above-described method.

In the embodiment of the present disclosure, the noise reduction degree value of the required pixel point is converted into the chrominance information map, and the chrominance information map obtained by this conversion is used to control the noise reduction degree, so that the noise reduction degree is controlled according to the required noise reduction degree value, the flexibility of noise reduction is improved, and the noise reduction effect is effectively improved.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. Other features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the disclosure.

Fig. 1 shows a schematic diagram of a CNR architecture in the related art;

FIG. 2 shows a flow diagram of a noise reduction method according to an embodiment of the present disclosure;

FIG. 3 shows a schematic diagram of a CNR architecture in an embodiment of the disclosure;

FIG. 4 illustrates a block diagram of a noise reducer according to an embodiment of the present disclosure;

FIG. 5 shows a block diagram of an electronic device 800 in accordance with an embodiment of the disclosure;

fig. 6 illustrates a block diagram of an electronic device 1900 in accordance with an embodiment of the disclosure.

Detailed Description

Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, C, and may mean including any one or more elements selected from the group consisting of A, B and C.

Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present disclosure may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present disclosure.

Fig. 1 shows a schematic diagram of a CNR (Chromatic Noise Reduction) architecture in the related art. As shown in fig. 1, in the related art, the CNR architecture may include a CNR mapping relationship configuration module and an ISP (image signal Processing) module.

The CNR mapping relationship configuration module may be configured to configure a mapping relationship between the chrominance interval and the noise reduction capability value. The mapping relation between the chromaticity interval and the noise reduction power value can be set according to requirements. For example, a mapping relationship may be established between a chromaticity interval representing red and a larger noise reduction power value, and a mapping relationship may be established between a chromaticity interval representing green and a smaller noise reduction power value.

The ISP module may perform noise reduction processing on the image according to the noise reduction power value determined by the CNR mapping relationship configuration module. In one example, by adding a large range of time-domain sample filtering (even sample filtering in the global range), noise reduction processing for large force values can be achieved; by time-domain sampling filtering of a smaller range (even without sampling filtering), noise reduction processing of a smaller magnitude of force can be achieved.

As shown in fig. 1, the image to be denoised includes a Y channel, a U channel, and a V channel, wherein the Y channel represents luminance information, and the U channel and the V channel represent chrominance information. The chrominance information map of the image to be denoised comprises a U channel and a V channel of the image to be denoised, and the chrominance information map of the image to be denoised comprises the chrominance value of each pixel point in the image to be denoised.

As shown in fig. 1, after the chromaticity information diagram of the image to be denoised is input into the CNR mapping relationship configuration module, the denoising strength value corresponding to each pixel point in the image to be denoised can be obtained according to the mapping relationship between the chromaticity interval and the denoising strength value configured in the CNR mapping relationship configuration module. After the noise reduction degree value corresponding to each pixel point is input to the ISP module, the ISP module may control the noise reduction degree of the noise reduction processing performed on each pixel point in the Y channel of the image to be noise reduced according to the noise reduction degree value corresponding to each pixel point, and output the Y channel after noise reduction. And according to the Y channel after the noise of the image to be subjected to noise reduction, and the U channel and the V channel (without noise reduction processing) of the image to be subjected to noise reduction, the image to be subjected to noise reduction after the noise reduction can be obtained.

Therefore, in the related art, the noise reduction with locally different strengths (i.e., different noise reduction strengths in different regions) can be realized based on the chrominance information of the image. In some scenes, the local noise reduction with different strengths is realized based on the chrominance information of the image, and the expected noise reduction effect cannot be achieved.

In one example, in a scene shot by a night scene, an extremely dark light or an off-screen camera, due to insufficient light input, multiple frames of images need to be shot, and the shot multiple frames of images are subjected to fusion processing to obtain a fused image with high image quality, but noise is amplified due to the fact that an underexposed frame is greatly brightened, and noise in a highlight area in the fused image is high. In another example, in a scene where a moving object is captured, during the process of performing fusion processing on captured multi-frame images, in order to suppress motion ghost, the degree of fusion noise reduction is reduced, which results in a large noise in a motion region in a fusion image.

It can be seen that non-uniform noise is introduced into the fused image. There is no obvious direct relationship between the noise and the chrominance information due to the non-uniformity introduced in the fused image. Therefore, after the noise reduction with locally different strengths is realized based on the chrominance information of the image, the uneven noise cannot be effectively removed.

The embodiment of the disclosure provides a noise reduction method, which can realize noise reduction with locally different strengths based on noise reduction requirements. Fig. 2 shows a flow chart of a noise reduction method according to an embodiment of the present disclosure. As shown in fig. 2, the method may include:

step S11, converting a noise reduction mask map of the image to be noise reduced into a chrominance information map, where the noise reduction mask map includes noise reduction power values of pixel points included in the image to be noise reduced.

And step S12, inputting the chromaticity information diagram into a strength control module.

And step S13, controlling the noise reduction strength of the noise reduction processing on the image to be subjected to noise reduction through the strength control module to obtain the image subjected to noise reduction.

In one possible implementation, the noise reduction method may be performed by an electronic device such as a terminal device or a server, where the terminal device may be a User Equipment (UE), a mobile device, a User terminal, a cellular phone, a cordless phone, a Personal Digital Assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, or the like, and the method may be implemented by a processor calling a computer readable instruction stored in a memory. Alternatively, the method may be performed by a server.

In step S11, the noise reduction mask map of the image to be noise reduced may be converted into a chrominance information map.

The image to be denoised can be used to represent any image that needs to be denoised, and the embodiment of the disclosure does not limit the image to be denoised. In one example, the image to be denoised may be an image captured by a single camera, or may be a fused image obtained by fusing a plurality of images.

The noise reduction mask map of the image to be noise reduced may include noise reduction power values of pixel points included in the image to be noise reduced. The noise reduction mask map of the image to be noise reduced can be set as required.

In one possible implementation manner, a first region and a second region in the image to be denoised can be determined; respectively setting a first noise reduction degree value and a second noise reduction degree value for pixel points contained in the first region and the second region; and constructing a noise reduction mask image of the image to be subjected to noise reduction according to the first noise reduction strength value and the second noise reduction strength value.

The flexibility of noise reduction can be further improved by dividing the noise reduction image into regions and respectively setting the noise reduction power value of each region. The first region and the second region may be determined as needed, and the manner of determining the first noise reduction power value and the second noise reduction power value may be determined according to the characteristics of the first region and the second region.

In one example, the first region may be a static region and the second region may be a dynamic region.

In the case where the first region is a static region, the first noise reduction level value may be determined based on luminance information corresponding to pixel points included in the first region.

Because the static area contains static objects and background. For the pixels contained in the region, the display effect is mainly influenced by the brightness information, so that the first noise reduction degree value corresponding to each pixel point can be determined according to the brightness value of each pixel point. For example, for a pixel point included in the static region, a larger first noise reduction value is set for the pixel point when the luminance value of the pixel point is larger, and a smaller first noise reduction value is set for the pixel point when the luminance value of the pixel point is smaller.

When the second region is a dynamic region, the second noise reduction power value may be determined according to motion information corresponding to a pixel point included in the second region.

Since a dynamic region includes a moving object, the motion of the object tends to blur an image, that is, noise in the dynamic region is caused by the motion of the object. Therefore, under the condition that one pixel belongs to the dynamic region, the motion information corresponding to the pixel can be obtained, and under the condition that the motion speed is high or the motion amplitude is large, a second large noise reduction degree value can be set for the pixel; and under the condition of low motion speed or small motion amplitude, setting a small second noise reduction value for the pixel point. Therefore, on the basis of reducing the influence on the static area, the noise caused by the movement can be effectively removed.

In one example, the first region may be a multi-frame fusion region and the second region may be an unfused region. Wherein the multi-frame fusion region is used for representing a region containing information of a plurality of images. The unfused region is used to indicate a region containing information of a single image.

Under the condition that the first region is a multi-frame fusion region, the first noise reduction degree value can be determined according to the corresponding fusion degree and/or variance of the pixel points contained in the first region. Wherein, the fusion degree and the noise reduction power value are in negative correlation, and the variance and the noise reduction power value are in positive correlation. Under the condition that the corresponding fusion degree of one pixel is large or the corresponding variance is small, the noise of the pixel point is small, the corresponding noise reduction requirement is small, and therefore the value of the second noise reduction degree value is small; under the condition that the corresponding fusion degree of one pixel in the fusion image is small or the variance is large, the noise of the pixel point is large, the corresponding noise reduction requirement is small, and therefore the value of the second noise reduction degree value is small. Therefore, on the basis of reducing the influence on the unfused area, the noise caused by image fusion can be effectively removed.

When the second region is an unfused region, the second noise reduction power value may be determined according to luminance information corresponding to a pixel point included in the second region. For example, a larger second noise reduction value is set for a pixel point with a larger brightness value, and a smaller second noise reduction value is set for a pixel point with a smaller brightness value.

In one example, the first region may be a highlight region and the second region may be a non-highlight region.

The highlight area is used for representing an area formed by pixel points with brightness larger than a brightness threshold value in the image to be denoised; and the non-highlight area is used for representing the area except the highlight area in the image to be denoised. The brightness threshold may be set as desired, for example, may be set to 180 or 210, etc.

Under the condition that the first region is a highlight region, the first noise reduction strength value and the second noise reduction strength value can be respectively determined according to the corresponding brightness values of the pixels contained in the first region and the second region, and the first noise reduction strength value is greater than the second noise reduction strength value.

Considering that human eyes are sensitive to the region with larger brightness value, larger noise reduction value can be set for the pixel point with larger brightness value, and smaller noise reduction value can be set for the pixel point with smaller brightness value. Therefore, in the embodiment of the present disclosure, an image to be noise-reduced is divided into a highlight region and a non-highlight region, a first noise reduction degree value with a larger value is determined for the highlight region, and a second noise reduction degree value with a smaller value is determined for the non-highlight region. Thus, it is possible to effectively remove noise in the high light region while reducing the influence on the non-high light region.

Therefore, for the above-mentioned case that the noise is amplified due to the large brightening in the underexposed frame, which results in the noise in the highlight area in the fused image being large, the noise in the highlight area can be effectively removed.

In one example, the first region may be a target object and the second region may be a background region. Wherein the target object may represent a region of greater interest or greater sensitivity to the user. For example, the target object may be a human face, a human body, an animal, a building object, or the like.

In the case where the first region is the target object, the first noise reduction power value may be determined from the feature map of the first region.

In the case where a pixel belongs to the target object, the effect intended by the user is indicated. Therefore, the noise reduction power value is set according to the characteristic diagram. For example, the human face determines the positions of the five sense organs and the skin according to the feature map, and different first noise reduction power values are respectively set for the five sense organs and the skin. For example, a smaller first noise reduction power value may be set for the five sense organs and a larger first noise reduction power value may be set for the skin.

And under the condition that the second area is a background area, determining the second noise reduction degree value according to the corresponding brightness value of the pixel points contained in the second area. This is similar to the unfused region and will not be described in detail here.

It should be noted that the noise reduction mask map may also be obtained in other manners, for example, a noise mask map customized by a user as needed.

Since the CNR mapping relationship configuration module shown in fig. 1 can process the chrominance information map, it cannot process the noise reduction mask map. Therefore, in step S11, the noise reduction mask map of the image to be noise reduced may be converted into a chrominance information map, and then the chrominance information map obtained through the conversion may be input into the CNR mapping relationship configuration module shown in fig. 1.

It can be understood that the chrominance values included in the chrominance information map obtained by conversion in S11 are set for controlling the noise reduction degree, and are not the true chrominance values of the pixel points included in the image to be noise-reduced, and do not reflect the true colors of the pixel points included in the image to be noise-reduced.

In one possible implementation, step S11 may include: aiming at each pixel point contained in the image to be denoised: determining a chromaticity interval corresponding to the pixel point according to the noise reduction degree value of the pixel point; and determining the chromatic value corresponding to the pixel point according to the chromatic interval corresponding to the pixel point.

In one example, a mapping relationship between a user-defined noise reduction power value and a chromaticity interval may be obtained; and determining a chromaticity interval corresponding to each pixel point according to the mapping relation defined by the user and the noise reduction degree value of the pixel point aiming at each pixel point contained in the image to be subjected to noise reduction.

For example, a mapping relationship may be established between a larger noise reduction power value and a chromaticity interval corresponding to red; and establishing a mapping relation between the smaller noise reduction power value and the chromaticity interval corresponding to blue.

In one example, a mapping relationship of the chrominance interval and the noise reduction value converted by the strength control module may be obtained; and determining the chromaticity interval corresponding to the pixel point based on the mapping relation and the noise reduction degree value of the pixel point.

The strength control module can control the noise reduction strength for performing noise reduction processing on the image to be subjected to noise reduction by the control module. The force control module may include a CNR mapping configuration module shown in fig. 1. And the CNR mapping relationship configuration module may include a mapping relationship for converting the chroma interval and the noise reduction power value.

After the chromaticity interval corresponding to the pixel point is determined, any chromaticity value can be taken from the chromaticity interval as the chromaticity value corresponding to the pixel point. In an example, the chroma value with the smallest U and V may be taken from the chroma interval as the chroma value corresponding to the pixel point.

It can be understood that the dimensions of the image to be denoised, the denoising mask map of the image to be denoised, the chrominance information map obtained by conversion and the image after denoising are consistent, and the pixel points are in one-to-one correspondence.

In one example, the image to be denoised comprises a Y channel, a U channel and a V channel, and the chrominance information map comprises the U channel and the V channel.

Since the strength control module in step S13 can control the noise reduction strength of the noise reduction processing performed on the image to be noise reduced based on the input chromaticity information map, the chromaticity information map of the strength control module in step S12 reflects the noise reduction strength of each pixel point in the image to be noise reduced. Therefore, in step S13, the strength control module actually controls the noise reduction strength of each pixel point in the image to be noise-reduced according to the noise reduction strength value of the pixel point included in the image to be noise-reduced, and performs noise reduction processing on each pixel point, thereby obtaining the image after noise reduction.

In a possible implementation manner, the strength control module can control the noise reduction strength of the image to be subjected to noise reduction in the building process, and perform noise reduction on the Y channel of the image to be subjected to noise reduction according to the noise reduction strength to obtain a noise-reduced Y channel; and determining the image subjected to noise reduction according to the Y channel subjected to noise reduction and the U channel and the V channel of the image to be subjected to noise reduction.

The noise reduction is carried out on the Y channel, the U channel and the V channel are kept unchanged, the noise reduction of the image is realized, the color information of the image is kept, and the noise reduction effect is improved.

Fig. 3 shows a schematic diagram of a CNR architecture in an embodiment of the present disclosure. As shown in fig. 3, the CNR architecture in the embodiment of the present disclosure may include a strength conversion module, a CNR mapping relationship configuration module (i.e., a strength control module), and an ISP module.

The strength conversion module may be configured to convert the noise reduction mask map into a chrominance information map. The force conversion module can be configured with a mapping relation for converting the noise reduction force value and the chromaticity interval. The mapping relationship for converting the noise reduction power value and the chrominance interval in the power conversion module may be set according to the mapping relationship for converting the chrominance interval and the noise reduction power value configured in the CNR mapping relationship configuration module. For example, on the basis that the CNR mapping configuration module configures a mapping relationship for conversion between a chrominance interval representing red and a large noise reduction degree, the degree conversion module may establish a mapping relationship for conversion (i.e., a noise reduction degree value and chrominance information) between a large noise reduction degree value and a chrominance interval representing red. The CNR mapping relationship configuration module and the ISP module may refer to a CNR architecture in the related art, which is not described herein again.

The noise reduction method according to the embodiment of the present disclosure is explained below with reference to fig. 3.

As shown in fig. 3, the image to be denoised includes a Y channel, a U channel, and a V channel, wherein the Y channel represents luminance information, and the U channel and the V channel represent chrominance information. The noise mask image of the image to be denoised comprises the denoising strength value of the image to be denoised, which contains color pixel points.

As shown in fig. 3, a noise reduction mask map of an image to be noise reduced is obtained; after the noise reduction mask map of the image to be noise reduced is input into the strength conversion module, according to the mapping relationship between the noise reduction strength value and the chromaticity interval configured in the strength conversion module, the chromaticity value for controlling the noise reduction strength of each pixel point in the image to be noise reduced, that is, the chromaticity information map obtained by conversion, can be obtained.

After the chroma information graph obtained by conversion is input into the CNR mapping relation configuration module, the mapping relation is converted according to the chroma interval and the noise reduction degree value configured in the CNR mapping relation configuration module, so that the noise reduction degree for controlling the noise reduction treatment of the pixel points contained in the image to be subjected to noise reduction can be obtained.

After the CNR mapping relationship configuration module inputs the noise reduction degree for controlling the pixel points contained in the image to be subjected to noise reduction processing to the ISP module, the ISP module can perform noise reduction processing on the pixel points contained in the Y channel of the image to be subjected to noise reduction according to the received noise reduction degree and output the Y channel subjected to noise reduction.

And according to the Y channel after the noise of the image to be subjected to noise reduction, and the U channel and the V channel (without noise reduction processing) of the image to be subjected to noise reduction, the image to be subjected to noise reduction after the noise reduction can be obtained.

Therefore, in the prior art, the chrominance information and the noise reduction strength of the strength control module are in a fixed mapping relation, so that the noise reduction strength of the image controlled by the strength control module cannot be changed according to requirements. For example, the input is an original image, and the strength control module automatically calculates the noise reduction strength of each pixel point in the original image according to the original image, so that the method is a fixed transformation method in any scene, that is, the strength control module cannot flexibly switch the noise reduction control scheme according to the requirements. In the embodiment of the present disclosure, a chrominance information map converted from a noise reduction value is adopted, and then the chrominance information map is input to a strength control module to control the noise reduction strength of an image to be subjected to noise reduction. For example, a mask map to be denoised can be generated according to the brightness, motion or custom information of the image, so as to control denoising with different strengths for different areas in the image. Therefore, the noise reduction mask image can be flexibly generated according to the noise reduction requirement of the image to be subjected to noise reduction, and the image noise reduction can be more flexibly realized through the chrominance information image converted from the noise reduction mask image.

It is understood that the above-mentioned method embodiments of the present disclosure can be combined with each other to form a combined embodiment without departing from the logic of the principle, which is limited by the space, and the detailed description of the present disclosure is omitted. Those skilled in the art will appreciate that in the above methods of the specific embodiments, the specific order of execution of the steps should be determined by their function and possibly their inherent logic.

In addition, the present disclosure also provides a noise reduction apparatus, an electronic device, a computer-readable storage medium, and a program, which can be used to implement any one of the noise reduction methods provided by the present disclosure, and the corresponding technical solutions and descriptions and corresponding descriptions of the method portions are referred to, and are not described again.

Fig. 4 shows a block diagram of a noise reduction apparatus according to an embodiment of the present disclosure. As shown in fig. 4, the noise reducing device 40 includes:

a converting module 41, configured to convert a noise reduction mask map of an image to be noise reduced into a chrominance information map, where the noise reduction mask map includes noise reduction power values of pixel points included in the image to be noise reduced;

an input module 42, configured to input the chromaticity information diagram into the strength control module;

and the control module 43 is configured to control the noise reduction strength for performing noise reduction processing on the image to be noise reduced through the strength control module, so as to obtain a noise-reduced image.

In one possible implementation, the conversion module is further configured to:

aiming at each pixel point contained in the image to be denoised:

In one possible implementation, the apparatus further includes:

In one possible implementation, the setting module is further configured to:

In some embodiments, functions or modules included in the apparatus provided in the embodiments of the present disclosure may be used to execute the method described in the above method embodiments, and specific implementations and technical effects thereof may refer to the description of the above method embodiments, which are not described herein again for brevity.

Embodiments of the present disclosure also provide a computer-readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the above-mentioned method. The computer readable storage medium may be a non-volatile computer readable storage medium.

An embodiment of the present disclosure further provides an electronic device, including: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to invoke the memory-stored instructions to perform the above-described method.

The embodiments of the present disclosure also provide a computer program product, which includes computer readable code, and when the computer readable code is run on a device, a processor in the device executes instructions for implementing the noise reduction method provided in any of the above embodiments.

The embodiments of the present disclosure also provide another computer program product for storing computer readable instructions, which when executed cause a computer to perform the operations of the noise reduction method provided in any of the above embodiments.

The electronic device may be provided as a terminal, server, or other form of device.

Fig. 5 illustrates a block diagram of an electronic device 800 in accordance with an embodiment of the disclosure. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, or the like terminal.

Referring to fig. 5, electronic device 800 may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input/output (I/O) interface 812, sensor component 814, and communication component 816.

The processing component 802 generally controls overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing components 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.

The memory 804 is configured to store various types of data to support operations at the electronic device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.

The power supply component 806 provides power to the various components of the electronic device 800. The power components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.

The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front camera and/or the rear camera may receive external multimedia data when the electronic device 800 is in an operation mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.

The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.

The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the electronic device 800. For example, the sensor assembly 814 may detect an open/closed state of the electronic device 800, the relative positioning of components, such as a display and keypad of the electronic device 800, the sensor assembly 814 may also detect a change in the position of the electronic device 800 or a component of the electronic device 800, the presence or absence of user contact with the electronic device 800, orientation or acceleration/deceleration of the electronic device 800, and a change in the temperature of the electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a Complementary Metal Oxide Semiconductor (CMOS) or Charge Coupled Device (CCD) image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 may access a wireless network based on a communication standard, such as a wireless network (WiFi), a second generation mobile communication technology (2G) or a third generation mobile communication technology (3G), or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

In an exemplary embodiment, the electronic device 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.

In an exemplary embodiment, a non-transitory computer-readable storage medium, such as the memory 804, is also provided that includes computer program instructions executable by the processor 820 of the electronic device 800 to perform the above-described methods.

Fig. 6 illustrates a block diagram of an electronic device 1900 in accordance with an embodiment of the disclosure. For example, the electronic device 1900 may be provided as a server. Referring to fig. 6, electronic device 1900 includes a processing component 1922 further including one or more processors and memory resources, represented by memory 1932, for storing instructions, e.g., applications, executable by processing component 1922. The application programs stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processing component 1922 is configured to execute instructions to perform the above-described method.

The electronic device 1900 may also include a power component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input/output (I/O) interface 1958. The electronic device 1900 may operate based on an operating system, such as the Microsoft Server operating system (Windows Server), stored in the memory 1932^TM) Apple Inc. of the present invention^TM) Multi-user, multi-process computer operating system (Unix)^TM) Free and open native code Unix-like operating System (Linux)^TM) Open native code Unix-like operating System (FreeBSD)^TM) Or the like.

In an exemplary embodiment, a non-transitory computer readable storage medium, such as the memory 1932, is also provided that includes computer program instructions executable by the processing component 1922 of the electronic device 1900 to perform the above-described methods.

The present disclosure may be systems, methods, and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for causing a processor to implement various aspects of the present disclosure.

The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.

The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.

The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).

Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.

These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The computer program product may be embodied in hardware, software or a combination thereof. In an alternative embodiment, the computer program product is embodied in a computer storage medium, and in another alternative embodiment, the computer program product is embodied in a Software product, such as a Software Development Kit (SDK), or the like.

Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A method of noise reduction, the method comprising:

inputting the chromaticity information diagram into a strength control module;

2. The method according to claim 1, wherein converting the noise reduction mask map of the image to be noise reduced into the chrominance information map comprises:

aiming at pixel points contained in the image to be denoised:

3. The method of claim 2, wherein determining the chrominance interval corresponding to the pixel point according to the noise reduction value of the pixel point comprises:

4. A method according to any one of claims 1 to 3, characterized in that, before converting the noise reduction mask map of the image to be noise reduced into the chrominance information map, the method further comprises:

determining a first region and a second region in the image to be denoised;

5. The method according to claim 4, wherein the setting of the first and second noise reduction degree values for the pixels included in the first and second regions respectively comprises:

6. The method according to claim 4, wherein the setting of the first and second noise reduction degree values for the pixels included in the first and second regions respectively comprises:

7. The method according to claim 4, wherein the setting of the first and second noise reduction degree values for the pixels included in the first and second regions respectively comprises:

8. The method according to claim 4, wherein the setting of the first and second noise reduction degree values for the pixels included in the first and second regions respectively comprises:

9. A noise reducing device, comprising:

10. An electronic device, comprising:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to invoke the memory-stored instructions to perform the method of any one of claims 1 to 8.

11. A computer readable storage medium having computer program instructions stored thereon, which when executed by a processor implement the method of any one of claims 1 to 8.