WO2022021932A1 - 降噪方法及装置、电子设备、存储介质和计算机程序产品 - Google Patents

降噪方法及装置、电子设备、存储介质和计算机程序产品 Download PDF

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WO2022021932A1
WO2022021932A1 PCT/CN2021/086252 CN2021086252W WO2022021932A1 WO 2022021932 A1 WO2022021932 A1 WO 2022021932A1 CN 2021086252 W CN2021086252 W CN 2021086252W WO 2022021932 A1 WO2022021932 A1 WO 2022021932A1
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noise reduction
area
intensity value
image
denoised
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PCT/CN2021/086252
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English (en)
French (fr)
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肖雄
张帆
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深圳市慧鲤科技有限公司
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Publication of WO2022021932A1 publication Critical patent/WO2022021932A1/zh

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    • G06T5/70—
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics

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  • the present disclosure relates to the field of computer technology, and in particular, to a noise reduction method and apparatus, an electronic device, a storage medium, and a computer program product.
  • noise in the image is not uniform and the sensitivity of the human eye to noise is different in different areas, different areas of the image need to be denoised with different denoising strengths. For example, since human eyes are more sensitive to noise in flat areas and face areas, it is necessary to use larger noise reduction efforts for flat areas and face areas in the image, and smaller noise reduction for other areas in the image. noise reduction strength.
  • the present disclosure proposes a noise reduction method and device, an electronic device, a storage medium, and a computer program product.
  • a noise reduction method comprising:
  • the noise reduction mask map of the image to be denoised Converting the noise reduction mask map of the image to be denoised into a chrominance information map, wherein the noise reduction mask map includes the noise reduction intensity values of the pixels included in the image to be denoised;
  • the intensity of noise reduction is controlled by the intensity control module to perform noise reduction processing on the image to be denoised, so as to obtain a denoised image.
  • the converting the noise reduction mask map of the image to be denoised into a chrominance information map includes:
  • the chromaticity value corresponding to the pixel point is determined.
  • the intensity control module By converting the noise reduction intensity value of the pixel point to the chroma value, it is beneficial to use the intensity control module to realize the noise reduction of different noise reduction intensity in different areas.
  • the determining the chromaticity interval corresponding to the pixel point according to the noise reduction intensity value of the pixel point includes:
  • the chromaticity interval corresponding to the pixel point is determined.
  • the converted chromaticity interval is determined, which is beneficial to use the intensity control module to realize the noise reduction of different noise reduction intensity in different areas.
  • the method before converting the noise reduction mask map of the image to be denoised into a chrominance information map, the method further includes:
  • a noise reduction mask map of the image to be noise reduction is constructed.
  • the first noise reduction intensity value is set for the pixels included in the first area
  • the second noise reduction intensity value is set for the pixels included in the second area
  • the first noise reduction intensity value is determined according to the brightness information corresponding to the pixels included in the first area, and the first noise reduction intensity value is determined according to the The motion information corresponding to the pixels included in the second area is used to determine the second noise reduction intensity value.
  • the first noise reduction intensity value is set for the pixels included in the first area
  • the second noise reduction intensity value is set for the pixels included in the second area
  • the first area is a multi-frame fusion area and the second area is an unfused area
  • the noise intensity value; the second noise reduction intensity value is determined according to the brightness information corresponding to the pixels contained in the second area;
  • the multi-frame fusion area is used to represent an area containing information of multiple images
  • the unfused regions are used to represent regions that contain information from a single image.
  • the first noise reduction intensity value is set for the pixels included in the first area
  • the second noise reduction intensity value is set for the pixels included in the second area
  • the first drop is determined according to the brightness values corresponding to the pixels included in the first area and the second area, respectively.
  • Noise intensity value and second noise reduction intensity value, and the first noise reduction intensity value is greater than the second noise reduction intensity value;
  • the highlight area is used to represent the area composed of pixels whose brightness is greater than the brightness threshold in the image to be denoised;
  • the non-highlight area is used to represent the area other than the highlight area in the image to be denoised .
  • the first noise reduction intensity value is set for the pixels included in the first area
  • the second noise reduction intensity value is set for the pixels included in the second area
  • the first noise reduction intensity value is determined according to the feature map of the first area, and the first noise reduction intensity value is determined according to the pixel included in the second area.
  • the point corresponding to the brightness value determines the second noise reduction intensity value.
  • the noise of the target object can be effectively removed on the basis of reducing the influence on the background area.
  • a noise reduction device comprising:
  • a conversion module configured to convert the noise reduction mask map of the image to be denoised into a chrominance information map, wherein the noise reduction mask map includes the noise reduction intensity values of the pixels included in the image to be denoised;
  • an input module for inputting the chromaticity information graph into a strength control module
  • the control module is used for controlling the noise reduction strength of the noise reduction processing on the image to be noise reduction through the strength control module, so as to obtain a noise reduction image.
  • the conversion module is further used for:
  • the chromaticity value corresponding to the pixel point is determined.
  • the determining the chromaticity interval corresponding to the pixel point according to the noise reduction intensity value of the pixel point includes:
  • the chromaticity interval corresponding to the pixel point is determined.
  • the apparatus further includes:
  • a determining module configured to determine the first area and the second area in the image to be denoised
  • a setting module configured to set a first noise reduction intensity value for the pixels included in the first area, and set a second noise reduction intensity value for the pixels included in the second area;
  • a construction module configured to construct a noise reduction mask map of the image to be denoised according to the first noise reduction intensity value and the second noise reduction intensity value.
  • the setting module is further used for:
  • the first noise reduction intensity value is determined according to the brightness information corresponding to the pixels included in the first area, and the first noise reduction intensity value is determined according to the The motion information corresponding to the pixels included in the second area is used to determine the second noise reduction intensity value.
  • the setting module is further used for:
  • the first area is a multi-frame fusion area and the second area is an unfused area
  • the noise intensity value; the second noise reduction intensity value is determined according to the brightness information corresponding to the pixels contained in the second area;
  • the multi-frame fusion area is used to represent an area containing information of multiple images
  • the unfused regions are used to represent regions that contain information from a single image.
  • the setting module is further used for:
  • the first drop is determined according to the brightness values corresponding to the pixels included in the first area and the second area, respectively.
  • Noise intensity value and second noise reduction intensity value, and the first noise reduction intensity value is greater than the second noise reduction intensity value;
  • the highlight area is used to represent the area composed of pixels whose brightness is greater than the brightness threshold in the image to be denoised;
  • the non-highlight area is used to represent the area other than the highlight area in the image to be denoised .
  • the setting module is further used for:
  • the first noise reduction intensity value is determined according to the feature map of the first area, and the first noise reduction intensity value is determined according to the pixel included in the second area.
  • the point corresponding to the brightness value determines the second noise reduction intensity value.
  • an electronic device comprising: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to invoke the instructions stored in the memory to execute the above method.
  • a computer-readable storage medium having computer program instructions stored thereon, the computer program instructions implementing the above method when executed by a processor.
  • a computer program product comprising computer readable code, when the computer readable code is run in an electronic device, a processor in the electronic device for implementing the above method.
  • the noise reduction intensity value of the required pixel is converted into a chromaticity information map, and the chromaticity information map obtained by the conversion is used to control the noise reduction intensity, so as to realize the reduction of the noise reduction intensity according to the required noise reduction intensity value.
  • the noise intensity is controlled, which improves the flexibility of noise reduction and effectively improves the noise reduction effect.
  • FIG. 1 shows a schematic diagram of a CNR architecture in the related art
  • FIG. 2 shows a flowchart 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 present disclosure
  • FIG. 4 shows a block diagram of a noise reduction apparatus according to an embodiment of the present disclosure
  • FIG. 5 shows a block diagram of an electronic device 800 according to an embodiment of the present disclosure
  • FIG. 6 shows a block diagram of an electronic device 1900 according to an embodiment of the present disclosure.
  • FIG. 1 shows a schematic diagram of a CNR (Chromatic Noise Reduction, Color Noise Reduction) architecture in the related art.
  • the CNR architecture may include a CNR mapping relationship configuration module and an ISP (Image Signal Processing, image signal processing) module.
  • ISP Image Signal Processing, image signal processing
  • the CNR mapping relationship configuration module may be used to configure the mapping relationship between the chrominance interval and the noise reduction intensity value.
  • the mapping relationship between the chrominance interval and the noise reduction strength value can be set as required. For example, a mapping relationship may be established between a chromaticity interval representing red and a larger noise reduction intensity value, and a mapping relationship may be established between a chromaticity interval representing green and a smaller noise reduction intensity value.
  • the ISP module can perform noise reduction processing on the image according to the noise reduction intensity value determined by the configuration module according to the CNR mapping relationship.
  • noise reduction processing for larger velocity values can be achieved by filtering with a larger range of temporal samples (even globally); filtering with a smaller range of temporal samples (even without sampling) filter), which can realize noise reduction processing with smaller velocity values.
  • 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 V channel represent chrominance information.
  • the chromaticity information map of the image to be denoised includes the U channel and the V channel of the image to be denoised, and the chromaticity information map of the image to be denoised includes the chromaticity value of each pixel in the image to be denoised.
  • the denoised noise can be obtained.
  • the noise reduction intensity value corresponding to each pixel in the image After inputting the noise reduction intensity value corresponding to each pixel to the ISP module, the ISP module can control the noise reduction intensity of each pixel in the Y channel of the image to be denoised according to the noise reduction intensity value corresponding to each pixel. , and output the denoised Y channel.
  • the de-noised image to be de-noised can be obtained.
  • FIG. 2 shows a flowchart of a noise reduction method according to an embodiment of the present disclosure. As shown in Figure 2, the method may include:
  • Step S11 Convert the noise reduction mask map of the image to be denoised into a chrominance information map, wherein the noise reduction mask map includes the noise reduction intensity values of the pixels included in the image to be denoised.
  • Step S12 inputting the chromaticity information map into the strength control module.
  • Step S13 controlling the noise reduction intensity of the noise reduction processing on the image to be denoised by the intensity control module to obtain a denoised image.
  • the noise reduction intensity value of the required pixel is converted into a chromaticity information map, and the chromaticity information map obtained by the conversion is used to control the noise reduction intensity, so as to realize the reduction of the noise reduction intensity according to the required noise reduction intensity value.
  • the noise intensity is controlled, which improves the flexibility of noise reduction and effectively improves the noise reduction effect.
  • the noise reduction method may be performed by an electronic device such as a terminal device or a server
  • the terminal device may be a user equipment (User Equipment, UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless For telephones, personal digital assistants (PDAs), handheld devices, computing devices, vehicle-mounted devices, wearable devices, etc.
  • the method can be implemented by the processor calling computer-readable instructions stored in the memory.
  • the method may be performed by a server.
  • step S11 the noise reduction mask map of the image to be denoised may be converted into a chrominance information map.
  • the image to be denoised may be used to represent any image that needs to be denoised, and the embodiment of the present disclosure does not limit the denoised image.
  • the image to be denoised may be an image captured by a single camera, or may be a fused image obtained by processing multiple images through image fusion.
  • the noise reduction mask map of the image to be denoised may include noise reduction strength values of pixels included in the image to be denoised.
  • the noise reduction mask of the image to be denoised can be set as required.
  • a first area and a second area in the image to be denoised may be determined; a first denoising intensity value is set for the pixels included in the first area, and a A second noise reduction intensity value is set for the pixels included in the second area; according to the first noise reduction intensity value and the second noise reduction intensity value, a noise reduction mask map of the image to be denoised is constructed.
  • the first area and the second area may be determined as required, and the manner of determining the first noise reduction intensity value and the second noise reduction intensity value may be determined according to the characteristics of the first area and the second area.
  • the first area may be a static area and the second area may be a dynamic area.
  • the first noise reduction intensity value may be determined according to the brightness information corresponding to the pixels included in the first area.
  • the static area contains static objects and backgrounds.
  • the display effect is mainly affected by the brightness information, so the first noise reduction intensity value corresponding to each pixel point can be determined according to the brightness value of each pixel point. For example, for a pixel included in the static area, if the brightness value of the pixel is large, a larger first noise reduction intensity value is set for the pixel, and if the brightness value of the pixel is small, Set a smaller first noise reduction strength value for it.
  • the second noise reduction intensity value may be determined according to motion information corresponding to the pixels included in the second area.
  • the dynamic region contains moving objects, and the motion of the object tends to cause image blurring, that is, the noise in the dynamic region is caused by the motion of the object. Therefore, when a pixel belongs to a dynamic area, the motion information corresponding to the pixel can be obtained, and when the motion speed is fast or the motion range is large, a larger second noise reduction can be set for the pixel Intensity value; when the movement speed is slow or the movement amplitude is small, a smaller second noise reduction intensity value can be set for the pixel. In this way, the noise caused by motion can be effectively removed on the basis of reducing the impact on the static area.
  • the first area may be a multi-frame fusion area
  • the second area may be an unfused area.
  • the multi-frame fusion region is used to represent a region containing information of multiple images. Unfused regions are used to represent regions that contain information from a single image.
  • the first noise reduction intensity value may be determined according to the corresponding fusion degree and/or variance of the pixels included in the first area. Among them, the fusion degree and the noise reduction strength value are negatively correlated, and the variance and the noise reduction strength value are positively correlated.
  • the fusion degree corresponding to a pixel In the case where the fusion degree corresponding to a pixel is large or the variance is small, it indicates that the noise of the pixel is small, and the corresponding noise reduction requirement is small, so the value of the second noise reduction intensity value is small; in the fusion image In the case where the fusion degree corresponding to one pixel is small or the variance is large, it indicates that the noise of the pixel is large, and the corresponding noise reduction requirement is small, so the value of the second noise reduction intensity value is small. In this way, the noise caused by image fusion can be effectively removed on the basis of reducing the influence on the unfused area.
  • the second noise reduction intensity value may be determined according to the brightness information corresponding to the pixels included in the second area. For example, a larger second noise reduction intensity value is set for a pixel point with a larger luminance value, a smaller second noise reduction intensity value is set for a pixel point with a smaller luminance value, and the like.
  • the first area may be a highlight area
  • the second area may be a non-highlight area
  • the highlight area is used to represent the area composed of pixels whose brightness is greater than the brightness threshold in the image to be denoised; the non-highlight area is used to represent the area other than the highlight area in the image to be denoised.
  • the brightness threshold can be set as required, for example, it can be set to 180 or 210 and so on.
  • the first noise reduction intensity value and the second noise reduction intensity value may be determined respectively according to the brightness values corresponding to the pixels contained in the first area and the second area, And the first noise reduction intensity value is greater than the second noise reduction intensity value.
  • the image to be denoised is divided into a highlight area and a non-highlight area, a first noise reduction intensity value with a larger value is determined for the highlight area, and a first noise reduction intensity value with a smaller value is determined for the non-highlight area. 2. Noise reduction intensity value. In this way, the noise in the highlight area can be effectively removed on the basis of reducing the influence on the non-highlight area.
  • the first area may be the target object
  • the second area may be the background area.
  • the target object may represent an area that the user pays more attention to or is more sensitive to.
  • the target object may be a human face, a human body, an animal, a building object, or the like.
  • the first noise reduction intensity value may be determined according to the feature map of the first area.
  • a pixel belongs to the target object, it indicates the user's expected effect on it. Therefore, its noise reduction intensity value is set according to its characteristic map. For example, the position of the facial features and the skin of the human face is determined according to the feature map, and different first noise reduction intensity values are respectively set for the facial features and the skin. For example, a smaller first noise reduction intensity value may be set for the facial features, and a larger first noise reduction intensity value may be set for the skin.
  • the second noise reduction intensity value may be determined according to the brightness value corresponding to the pixel point included in the second area. This is similar to the unfused region and will not be repeated here.
  • the noise reduction mask map may also be obtained in other ways, such as a noise mask map customized by a user as required, and the embodiment of the present disclosure does not limit the acquisition method of the noise reduction mask map.
  • step S11 the noise reduction mask map of the image to be denoised can be converted into a chrominance information map, and then the converted chrominance information map can be input into the CNR mapping relationship configuration module shown in FIG. 1 .
  • the chromaticity values included in the chromaticity information map converted in S11 are set for controlling the noise reduction intensity, not the real chromaticity values of the pixels contained in the image to be denoised. Does not reflect the true color of the pixels contained in the image to be denoised.
  • step S11 may include: for a pixel included in the image to be denoised: determining a chromaticity interval corresponding to the pixel according to the noise reduction intensity value of the pixel; The chromaticity interval corresponding to the point, and the chromaticity value corresponding to the pixel is determined.
  • the mapping relationship between the user-defined noise reduction intensity value and the chrominance interval can be obtained; for each pixel included in the image to be denoised, the user-defined mapping relationship and the reduction of the pixel point can be obtained according to the user-defined mapping relationship. Noise intensity value to determine the chromaticity interval corresponding to the pixel.
  • a mapping relationship can be established between a larger noise reduction intensity value and a chroma interval corresponding to red; a mapping relationship can be established between a smaller noise reduction intensity value and a chroma interval corresponding to blue.
  • a mapping relationship in which the intensity control module converts the chrominance interval and the noise reduction intensity value may be obtained; based on the mapping relationship and the noise reduction intensity value of the pixel point, the chrominance interval corresponding to the pixel point is determined.
  • the strength control module may control the noise reduction strength of the noise reduction processing for the image to be denoised.
  • the force control module may include the CNR mapping relationship configuration module shown in FIG. 1 .
  • the CNR mapping relationship configuration module may include a mapping relationship for converting the chrominance interval and the noise reduction intensity value.
  • any chromaticity value can be taken from the chromaticity interval as the chromaticity value corresponding to the pixel point.
  • the chrominance value with the smallest U and V may be taken from the chromaticity interval as the chromaticity value corresponding to the pixel point.
  • the dimensions of the image to be denoised, the denoising mask map of the denoised image, the converted chrominance information map and the denoised image are consistent, and the pixels correspond one-to-one.
  • the image to be denoised includes a Y channel, a U channel and a V channel
  • the chrominance information map includes a U channel and a V channel
  • the intensity control module in step S13 can control the noise reduction intensity of the noise reduction processing on the image to be denoised based on the input chromaticity information map, and the chromaticity information map input to the intensity control module in step S12 reflects the noise reduction in the image to be denoised Noise reduction strength value for each pixel. Therefore, in step S13, the strength control module actually controls the noise reduction strength of each pixel in the image to be denoised according to the noise reduction strength value of the pixels included in the image to be denoised, and performs noise reduction processing for each pixel. , so as to obtain a denoised image.
  • the strength control module can control the noise reduction strength of the image to be denoised in the construction process, and perform noise reduction processing on the Y channel of the image to be denoised according to the noise reduction strength, and obtain a noise reduction after noise reduction.
  • the denoised image is determined according to the denoised Y channel, and the U channel and V channel of the image to be denoised.
  • Noise reduction is performed on the Y channel, and the U channel and V channel are kept unchanged, which not only realizes the noise reduction of the image, but also retains the color information of the image, which improves the noise reduction effect.
  • FIG. 3 shows a schematic diagram of a CNR architecture in an embodiment of the present disclosure.
  • the CNR architecture in the embodiment of the present disclosure may include a force conversion module, a CNR mapping relationship configuration module (ie, a force control module) and an ISP module.
  • the velocity conversion module can be used to convert the noise reduction mask map into a chrominance information map.
  • the mapping relationship between the noise reduction velocity value and the chromaticity interval can be configured.
  • the mapping relationship for converting the noise reduction intensity value and the chrominance interval in the intensity conversion module can be set according to the mapping relationship configured in the CNR mapping relationship configuration module for converting the chrominance interval and the noise reduction intensity value.
  • the intensity conversion module can be used in the larger value of the noise reduction intensity.
  • a mapping relationship for conversion is established between the value and the chroma interval representing red (ie, the noise reduction strength value and the chroma information).
  • the CNR mapping relationship configuration module and the ISP module can refer to the CNR architecture in the related art, and details are not described here.
  • 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 V channel represent chrominance information.
  • the noise mask of the image to be denoised includes the denoising strength values of the color pixels contained in the image to be denoised.
  • the noise reduction mask of the image to be denoised is obtained; after the noise reduction mask of the image to be denoised is input into the strength conversion module, the noise reduction strength value and chromaticity interval configured in the strength conversion module are By performing the conversion mapping relationship, the chromaticity value that controls the noise reduction intensity of each pixel in the image to be denoised can be obtained, that is, the converted chromaticity information map.
  • the pixels contained in the image to be denoised can be controlled. Click on the noise reduction strength for noise reduction processing.
  • the ISP module After the CNR mapping relationship configuration module inputs the noise reduction intensity that controls the noise reduction processing of the pixels contained in the image to be denoised to the ISP module, the ISP module can follow the received noise reduction intensity to the pixels contained in the Y channel of the denoised image. Click to perform noise reduction processing, and output the Y channel after noise reduction.
  • the de-noised image to be de-noised can be obtained.
  • the chromaticity information and the noise reduction strength of the strength control module in the prior art have a fixed mapping relationship, so the noise reduction strength of the image controlled by the strength control module cannot be changed as required.
  • the strength control module automatically calculates the noise reduction strength of each pixel in the original image according to the original image, it is a fixed transformation method in any scene, that is, the strength control module cannot flexibly meet the requirements. Toggles the noise reduction control scheme.
  • the chromaticity information map converted from the noise reduction intensity value is used, and then the chromaticity information map is input into the intensity control module to control the noise reduction intensity of the image to be denoised.
  • a mask map to be denoised can be generated according to the brightness, motion or custom information of the image to control the denoising of different strengths for different areas in the image.
  • the noise reduction mask map can be flexibly generated according to the noise reduction requirements of the image to be denoised, so that the image noise reduction can be more flexibly realized by converting the chrominance information map of the noise reduction mask map.
  • the present disclosure also provides noise reduction devices, electronic devices, computer-readable storage media, and programs, all of which can be used to implement any noise reduction method provided by the present disclosure.
  • noise reduction devices electronic devices, computer-readable storage media, and programs, all of which can be used to implement any noise reduction method provided by the present disclosure.
  • FIG. 4 shows a block diagram of a noise reduction apparatus according to an embodiment of the present disclosure.
  • the noise reduction device 40 includes:
  • the conversion module 41 is configured to convert the noise reduction mask map of the image to be denoised into a chrominance information map, wherein the noise reduction mask map includes the noise reduction intensity values of the pixels contained in the image to be denoised ;
  • the input module 42 is used for inputting the chromaticity information graph into the strength control module
  • the control module 43 is configured to control the noise reduction strength of the noise reduction processing on the image to be noise reduction through the strength control module, so as to obtain a noise reduction image.
  • the conversion module is further used for:
  • the chromaticity value corresponding to the pixel point is determined.
  • the determining the chromaticity interval corresponding to the pixel point according to the noise reduction intensity value of the pixel point includes:
  • the chromaticity interval corresponding to the pixel point is determined.
  • the apparatus further includes:
  • a determining module configured to determine the first area and the second area in the image to be denoised
  • a setting module configured to set a first noise reduction intensity value for the pixels included in the first area, and set a second noise reduction intensity value for the pixels included in the second area;
  • a construction module configured to construct a noise reduction mask map of the image to be denoised according to the first noise reduction intensity value and the second noise reduction intensity value.
  • the setting module is further used for:
  • the first noise reduction intensity value is determined according to the brightness information corresponding to the pixels included in the first area, and the first noise reduction intensity value is determined according to the The motion information corresponding to the pixels included in the second area is used to determine the second noise reduction intensity value.
  • the setting module is further used for:
  • the first area is a multi-frame fusion area and the second area is an unfused area
  • the noise intensity value; the second noise reduction intensity value is determined according to the brightness information corresponding to the pixels contained in the second area;
  • the multi-frame fusion area is used to represent an area containing information of multiple images
  • the unfused regions are used to represent regions that contain information from a single image.
  • the setting module is further used for:
  • the first drop is determined according to the brightness values corresponding to the pixels included in the first area and the second area, respectively.
  • Noise intensity value and second noise reduction intensity value, and the first noise reduction intensity value is greater than the second noise reduction intensity value;
  • the highlight area is used to represent the area composed of pixels whose brightness is greater than the brightness threshold in the image to be denoised;
  • the non-highlight area is used to represent the area other than the highlight area in the image to be denoised .
  • the setting module is further used for:
  • the first noise reduction intensity value is determined according to the feature map of the first area, and the first noise reduction intensity value is determined according to the pixel included in the second area.
  • the point corresponding to the brightness value determines the second noise reduction intensity value.
  • the functions or modules included in the apparatus provided by the embodiments of the present disclosure may be used to execute the methods described in the above method embodiments, and the specific implementation and technical effects may refer to the above method embodiments. It is concise and will not be repeated here.
  • Embodiments of the present disclosure further provide a computer-readable storage medium, on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the foregoing method is implemented.
  • the computer-readable storage medium may be a volatile storage medium or a non-volatile storage medium.
  • An embodiment of the present disclosure further provides an electronic device, including: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to invoke the instructions stored in the memory to execute the above method.
  • Embodiments of the present disclosure also provide a computer program product, including computer-readable codes.
  • a processor in the device executes a method for implementing the noise reduction method provided by any of the above embodiments. instruction.
  • An embodiment of the present disclosure further provides another computer program product, which is used to store computer-readable instructions, which, when executed, cause the computer to perform the operations of the noise reduction method provided by any of the foregoing embodiments.
  • the electronic device may be provided as a terminal, server or other form of device.
  • FIG. 5 shows a block diagram of an electronic device 800 according to an embodiment of the present disclosure.
  • electronic device 800 may be a mobile phone, computer, digital broadcast terminal, messaging device, game console, tablet device, medical device, fitness device, personal digital assistant, etc. terminal.
  • electronic device 800 may include one or more of the following components: processing component 802, memory 804, power supply component 806, multimedia component 808, audio component 810, input/output (I/O) interface 812, sensor component 814 , and the communication component 816 .
  • the processing component 802 generally controls the overall operation of the electronic device 800, such as operations associated with display, phone calls, data communications, camera operations, and recording operations.
  • the processing component 802 can include one or more processors 820 to execute instructions to perform all or some of the steps of the methods described above.
  • processing component 802 may include one or more modules that facilitate interaction between processing component 802 and other components.
  • processing component 802 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 802.
  • Memory 804 is configured to store various types of data to support operation at electronic device 800 . Examples of such data include instructions for any application or method operating on electronic device 800, contact data, phonebook data, messages, pictures, videos, and the like. Memory 804 may be implemented by any type of volatile or nonvolatile storage device or combination thereof, 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 Disk.
  • SRAM static random access memory
  • EEPROM electrically erasable programmable read only memory
  • EPROM erasable Programmable Read Only Memory
  • PROM Programmable Read Only Memory
  • ROM Read Only Memory
  • Magnetic Memory Flash Memory
  • Magnetic or Optical Disk Magnetic Disk
  • Power supply assembly 806 provides power to various components of electronic device 800 .
  • Power supply components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to electronic device 800 .
  • Multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user.
  • 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 input signals from a user.
  • the touch panel includes one or more touch sensors to sense touch, swipe, and gestures on the touch panel. The touch sensor may not only sense the boundaries of a touch or swipe action, but also detect the duration and pressure associated with the touch or swipe action.
  • the multimedia component 808 includes a front-facing camera and/or a rear-facing camera. When the electronic device 800 is in an operation mode, such as a shooting mode or a video mode, the front camera and/or the rear camera may receive external multimedia data. Each of the front and rear cameras can be a fixed optical lens system or have focal length and optical zoom capability.
  • Audio component 810 is configured to output and/or input audio signals.
  • audio component 810 includes a microphone (MIC) that is configured to receive external audio signals when electronic device 800 is in operating modes, such as calling mode, recording mode, and voice recognition mode.
  • the received audio signal may be further stored in memory 804 or transmitted via communication component 816 .
  • 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 a peripheral interface module, which may be a keyboard, a click wheel, a button, or the like. These buttons may include, but are not limited to: home button, volume buttons, start button, and lock button.
  • Sensor assembly 814 includes one or more sensors for providing status assessment of various aspects of electronic device 800 .
  • the sensor assembly 814 can detect the on/off state of the electronic device 800, the relative positioning of the components, such as the display and the keypad of the electronic device 800, the sensor assembly 814 can also detect the electronic device 800 or one of the electronic device 800 Changes in the position of components, presence or absence of user contact with the electronic device 800 , orientation or acceleration/deceleration of the electronic device 800 and changes in the temperature of the electronic device 800 .
  • Sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects in the absence of any physical contact.
  • 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.
  • CMOS complementary metal oxide semiconductor
  • CCD charge coupled device
  • the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
  • Communication component 816 is configured to facilitate wired or wireless communication between electronic device 800 and other devices.
  • the electronic device 800 may access a wireless network based on a communication standard, such as wireless network (WiFi), second generation mobile communication technology (2G) or third generation mobile communication technology (3G), or a combination thereof.
  • the communication component 816 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel.
  • the communication component 816 also includes a near field communication (NFC) module to facilitate short-range communication.
  • 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.
  • RFID radio frequency identification
  • IrDA infrared data association
  • UWB ultra-wideband
  • Bluetooth Bluetooth
  • 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 A programmed gate array (FPGA), controller, microcontroller, microprocessor or other electronic component implementation is used to perform the above method.
  • ASICs application specific integrated circuits
  • DSPs digital signal processors
  • DSPDs digital signal processing devices
  • PLDs programmable logic devices
  • FPGA field programmable A programmed gate array
  • controller microcontroller, microprocessor or other electronic component implementation is used to perform the above method.
  • a non-volatile computer-readable storage medium such as a memory 804 comprising computer program instructions executable by the processor 820 of the electronic device 800 to perform the above method is also provided.
  • FIG. 6 shows a block diagram of an electronic device 1900 according to an embodiment of the present disclosure.
  • the electronic device 1900 may be provided as a server.
  • electronic device 1900 includes processing component 1922, which further includes one or more processors, and a memory resource represented by memory 1932 for storing instructions executable by processing component 1922, such as applications.
  • An application program stored in memory 1932 may include one or more modules, each corresponding to a set of instructions.
  • the processing component 1922 is configured to execute instructions to perform the above-described methods.
  • the electronic device 1900 may also include a power supply assembly 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 can operate based on an operating system stored in the memory 1932, such as a Microsoft server operating system (Windows Server TM ), a graphical user interface based operating system (Mac OS X TM ) introduced by Apple, a multi-user multi-process computer operating system (Unix TM ), Free and Open Source Unix-like Operating System (Linux TM ), Open Source Unix-like Operating System (FreeBSD TM ) or the like.
  • Microsoft server operating system Windows Server TM
  • Mac OS X TM graphical user interface based operating system
  • Uniix TM multi-user multi-process computer operating system
  • Free and Open Source Unix-like Operating System Linux TM
  • FreeBSD TM Open Source Unix-like Operating System
  • a non-volatile computer-readable storage medium such as memory 1932 comprising computer program instructions executable by processing component 1922 of electronic device 1900 to perform the above-described method.
  • the present disclosure may be a system, method and/or computer program product.
  • the computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of the present disclosure.
  • a computer-readable storage medium may be a tangible device that can hold and store instructions for use by the instruction execution device.
  • the computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing.
  • Non-exhaustive list of computer readable storage media include: portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM) or flash memory), static random access memory (SRAM), portable compact disk read only memory (CD-ROM), digital versatile disk (DVD), memory sticks, floppy disks, mechanically coded devices, such as printers with instructions stored thereon Hole cards or raised structures in grooves, and any suitable combination of the above.
  • RAM random access memory
  • ROM read only memory
  • EPROM erasable programmable read only memory
  • flash memory static random access memory
  • SRAM static random access memory
  • CD-ROM compact disk read only memory
  • DVD digital versatile disk
  • memory sticks floppy disks
  • mechanically coded devices such as printers with instructions stored thereon Hole cards or raised structures in grooves, and any suitable combination of the above.
  • Computer-readable storage media are not to be construed as transient signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (eg, light pulses through fiber optic cables), or through electrical wires transmitted electrical signals.
  • the computer readable program instructions described herein may be downloaded to various computing/processing devices from a computer readable storage medium, or to an external computer or external storage device over 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.
  • a network adapter card or network interface in each computing/processing device receives computer-readable program instructions from a network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing/processing device .
  • Computer program instructions for carrying out operations of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or instructions in one or more programming languages.
  • Source or object code written in any combination, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as the "C" 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 implement.
  • the remote computer may be connected to the user's computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (eg, using an Internet service provider through the Internet connect).
  • LAN local area network
  • WAN wide area network
  • custom electronic circuits such as programmable logic circuits, field programmable gate arrays (FPGAs), or programmable logic arrays (PLAs) can be personalized by utilizing state information of computer readable program instructions.
  • Computer readable program instructions are executed to implement various aspects of the present disclosure.
  • 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 that causes the instructions when executed by the processor of the computer or other programmable data processing apparatus , resulting in means for implementing the functions/acts specified in one or more blocks of the flowchart and/or block diagrams.
  • These computer readable program instructions can also be stored in a computer readable storage medium, these instructions cause a computer, programmable data processing apparatus and/or other equipment to operate in a specific manner, so that the computer readable medium storing the instructions includes An article of manufacture comprising instructions for implementing various aspects of the functions/acts specified in one or more blocks of the flowchart and/or block diagrams.
  • Computer readable program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other equipment to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other equipment to produce a computer-implemented process , thereby causing instructions executing on a computer, other programmable data processing apparatus, or other device to implement the functions/acts specified in one or more blocks of the flowcharts and/or block diagrams.
  • each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more functions for implementing the specified logical function(s) executable instructions.
  • the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks 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.
  • each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations can be implemented in dedicated hardware-based systems that perform the specified functions or actions , or can be implemented in a combination of dedicated hardware and computer instructions.
  • the computer program product can be specifically implemented by hardware, software or a combination thereof.
  • the computer program product is embodied as a computer storage medium, and in another optional embodiment, the computer program product is embodied as a software product, such as a software development kit (Software Development Kit, SDK), etc. Wait.
  • a software development kit Software Development Kit, SDK

Abstract

本公开涉及一种降噪方法及装置、电子设备、存储介质和计算机程序产品，所述方法包括：将待降噪图像的降噪掩码图转换为色度信息图，其中，所述降噪掩码图包括所述待降噪图像中包含的像素点的降噪力度值；将所述色度信息图输入力度控制模块；通过所述力度控制模块控制对所述待降噪图像进行降噪处理的降噪力度，得到降噪后的图像。

Description

降噪方法及装置、电子设备、存储介质和计算机程序产品
本申请要求在2020年07月31日提交中国专利局、申请号为202010763077.X、申请名称为“一种降噪方法及装置、电子设备和存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本公开涉及计算机技术领域，尤其涉及一种降噪方法及装置、电子设备、存储介质和计算机程序产品。
背景技术
由于图像中噪声不均匀以及人眼对噪声的敏感度在不同区域不同，因此，对图像的不同区域需要采用不同的降噪力度进行降噪。例如，由于人眼对平坦区域和人脸区域的噪声更敏感，因此，对图像中的平坦区域和人脸区域需要采用较大的降噪力度进行降噪，对图像中的其他区域采用较小的降噪力度进行降噪。
发明内容
本公开提出了一种降噪方法及装置、电子设备、存储介质和计算机程序产品。
根据本公开的一方面，提供了一种降噪方法，包括：
将待降噪图像的降噪掩码图转换为色度信息图，其中，所述降噪掩码图包括所述待降噪图像中包含的像素点的降噪力度值；
将所述色度信息图输入力度控制模块；
通过所述力度控制模块控制对所述待降噪图像进行降噪处理的降噪力度，得到降噪后的图像。
在一种可能的实现方式中，所述将待降噪图像的降噪掩码图转换为色度信息图包括：
针对所述待降噪图像中包含的像素点：
根据所述像素点的降噪力度值，确定所述像素点对应的色度区间；
根据所述像素点对应的色度区间，确定所述像素点对应的色度值。
通过将像素点的降噪力度值转换为色度值，有利于利用力度控制模块实现不同区域不同降噪力度的降噪。
在一种可能的实现方式中，所述根据所述像素点的降噪力度值，确定所述像素点对应的色度区间包括：
获取所述力度控制模块对色度区间和降噪力度值进行转换的映射关系；
基于所述映射关系与所述像素点的降噪力度值，确定所述像素点对应的色度区间。
按照力度控制模块对色度区间和降噪力度值进行转换的映射关系，确定转换而来的色度区间，有利于利用力度控制模块实现不同区域不同降噪力度的降噪。
在一种可能的实现方式中，在所述将待降噪图像的降噪掩码图转换为色度信息图之前，所述方法还包括：
确定所述待降噪图像中的第一区域和第二区域；
对所述第一区域中包含的像素点设置第一降噪力度值，并对所述第二区域中包含的像素点设置第二降噪力度值；
根据所述第一降噪力度值和所述第二降噪力度值，构建所述待降噪图像的降噪掩码图。
通过对降噪图像划分区域，分别设置各个区域的降噪力度值，可以进一步提升降噪的灵活性。
在一种可能的实现方式中，所述对所述第一区域中包含的像素点设置第一降噪力度值，并对所述第二区域中包含的像素点设置第二降噪力度值，包括：
在所述第一区域为静态区域、所述第二区域为动态区域的情况下，根据所述第一区域中包含的像素点对应的亮度信息，确定所述第一降噪力度值，根据所述第二区域中包含的像素点对应的运动信息，确定所述第二降噪力度值。
这样可以在降低对静态区域影响的基础上，有效去除因运动而造成的噪声。
在一种可能的实现方式中，所述对所述第一区域中包含的像素点设置第一降噪力度值，并对所述第二区域中包含的像素点设置第二降噪力度值，包括：
在所述第一区域为多帧融合区域、所述第二区域为未融合区域的情况下，根据所述第一区域中包含的像素点对应融合度和/或方差，确定所述第一降噪力度值；根据所述第二区域中包含的像素点对应的亮度信息，确定所述第二降噪力度值；其中，所述多帧融合区域用于表示包含多个图像的信息的区域，所述未融合区域用于表示包含单一图像的信息的区域。
这样可以在降低对未融合区域的影响的基础上，有效去除因图像融合而造成的噪声。
在一种可能的实现方式中，所述对所述第一区域中包含的像素点设置第一降噪力度值，并对所述第二区域中包含的像素点设置第二降噪力度值，包括：
在所述第一区域为高光区域、所述第二区域为非高光区域的情况下，根据所述第一区域和所述第二区域包含的像素点对应亮度值，分别确定所述第一降噪力度值和第二降噪力度值，且所述第一降噪力度值大于所述第二降噪力度值；
其中，所述高光区域用于表示所述待降噪图像中亮度大于亮度阈值的像素点组成的区域；所述非高光区域用于表示所述待降噪图像中除所述高光区域以外的区域。
这样可以在降低对非高光区域的影响的基础上，有效去除高光区域的噪声。
在一种可能的实现方式中，所述对所述第一区域中包含的像素点设置第一降噪力度值，并对所述第二区域中包含的像素点设置第二降噪力度值，包括：
在所述第一区域为目标对象，所述第二区域为背景区域的情况下，根据所述第一区域的特征图确定所述第一降噪力度值，根据所述第二区域包含的像素点对应亮度值确定所述第二降噪力度值。
这样可以在降低对背景区域的影响的基础上，有效地去除目标对象的噪声。
根据本公开的一方面，提供了一种降噪装置，包括：
转换模块，用于将待降噪图像的降噪掩码图转换为色度信息图，其中，所述降噪掩码图包括所述待降噪图像中包含的像素点的降噪力度值；
输入模块，用于将所述色度信息图输入力度控制模块；
控制模块，用于通过所述力度控制模块控制对所述待降噪图像进行降噪处理的降噪力度，得到降噪后的图像。
在一种可能的实现方式中，所述转换模块还用于：
针对所述待降噪图像中包含的像素点：
根据所述像素点的降噪力度值，确定所述像素点对应的色度区间；
根据所述像素点对应的色度区间，确定所述像素点对应的色度值。
在一种可能的实现方式中，所述根据所述像素点的降噪力度值，确定所述像素点对应的色度区间包括：
获取所述力度控制模块对色度区间和降噪力度值进行转换的映射关系；
基于所述映射关系与所述像素点的降噪力度值，确定所述像素点对应的色度区间。
在一种可能的实现方式中，所述装置还包括：
确定模块，用于确定所述待降噪图像中的第一区域和第二区域；
设置模块，用于对所述第一区域中包含的像素点设置第一降噪力度值，并对所述第二区域中包含的像素点设置第二降噪力度值；
构建模块，用于根据所述第一降噪力度值和所述第二降噪力度值，构建所述待降噪图像的降噪掩码图。
在一种可能的实现方式中，所述设置模块还用于：
在所述第一区域为静态区域、所述第二区域为动态区域的情况下，根据所述第一区域中包含的像素点对应的亮度信息，确定所述第一降噪力度值，根据所述第二区域中包含的像素点对应的运动信息，确定所述第二降噪力度值。
在一种可能的实现方式中，所述设置模块还用于：
在所述第一区域为多帧融合区域、所述第二区域为未融合区域的情况下，根据所述第一区域中包含的像素点对应融合度和/或方差，确定所述第一降噪力度值；根据所述第二区域中包含的像素点对应的亮度信息，确定所述第二降噪力度值；其中，所述多帧融合区域用于表示包含多个图像的信息的区域，所述未融合区域用于表示包含单一图像的信息的区域。
在一种可能的实现方式中，所述设置模块还用于：
在所述第一区域为高光区域、所述第二区域为非高光区域的情况下，根据所述第一区域和所述第二区域包含的像素点对应亮度值，分别确定所述第一降噪力度值和第二降噪力度值，且所述第一降噪力度值大于所述第二降噪力度值；
其中，所述高光区域用于表示所述待降噪图像中亮度大于亮度阈值的像素点组成的 区域；所述非高光区域用于表示所述待降噪图像中除所述高光区域以外的区域。
在一种可能的实现方式中，所述设置模块还用于：
在所述第一区域为目标对象，所述第二区域为背景区域的情况下，根据所述第一区域的特征图确定所述第一降噪力度值，根据所述第二区域包含的像素点对应亮度值确定所述第二降噪力度值。
根据本公开的一方面，提供了一种电子设备，包括：处理器；用于存储处理器可执行指令的存储器；其中，所述处理器被配置为调用所述存储器存储的指令，以执行上述方法。
根据本公开的一方面，提供了一种计算机可读存储介质，其上存储有计算机程序指令，所述计算机程序指令被处理器执行时实现上述方法。
根据本公开的一方面，提供了计算机程序产品，包括计算机可读代码，当所述计算机可读代码在电子设备中运行时，所述电子设备中的处理器用于实现上述方法。
在本公开实施例中，将需要的像素点的降噪力度值转换成色度信息图，采用该转换得到的色度信息图对降噪力度进行控制，实现了按照需要的降噪力度值对降噪力度进行控制，提高了降噪的灵活性，有效提升了降噪效果。
应当理解的是，以上的一般描述和后文的细节描述仅是示例性和解释性的，而非限制本公开。根据下面参考附图对示例性实施例的详细说明，本公开的其它特征及方面将变得清楚。
附图说明
此处的附图被并入说明书中并构成本说明书的一部分，这些附图示出了符合本公开的实施例，并与说明书一起用于说明本公开的技术方案。
图1示出相关技术中CNR架构的示意图；
图2示出根据本公开实施例的降噪方法的流程图；
图3示出本公开实施例中CNR架构的示意图；
图4示出根据本公开实施例的降噪装置的框图；
图5示出根据本公开实施例的一种电子设备800的框图；
图6示出根据本公开实施例的一种电子设备1900的框图。
具体实施方式
以下将参考附图详细说明本公开的各种示例性实施例、特征和方面。附图中相同的附图标记表示功能相同或相似的元件。尽管在附图中示出了实施例的各种方面，但是除非特别指出，不必按比例绘制附图。
在这里专用的词“示例性”意为“用作例子、实施例或说明性”。这里作为“示例性”所说明的任何实施例不必解释为优于或好于其它实施例。
本文中术语“和/或”，仅仅是一种描述关联对象的关联关系，表示可以存在三种关 系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。另外，本文中术语“至少一种”表示多种中的任意一种或多种中的至少两种的任意组合，例如，包括A、B、C中的至少一种，可以表示包括从A、B和C构成的集合中选择的任意一个或多个元素。
另外，为了更好地说明本公开，在下文的具体实施方式中给出了众多的具体细节。本领域技术人员应当理解，没有某些具体细节，本公开同样可以实施。在一些实例中，对于本领域技术人员熟知的方法、手段、元件和电路未作详细描述，以便于凸显本公开的主旨。
图1示出相关技术中CNR(Chromatic Noise Reduction，彩色噪声抑制)架构的示意图。如图1所示，相关技术中，CNR架构可以包括CNR映射关系配置模块和ISP(Image Signal Processing，图像信号处理)模块。
其中，CNR映射关系配置模块可以用于配置色度区间和降噪力度值的映射关系。色度区间和降噪力度值的映射关系可以根据需要进行设置。例如，可以在代表红色的色度区间与较大的降噪力度值之间建立映射关系，在代表绿色的色度区间与较小的降噪力度值之间建立映射关系。
ISP模块可以根据CNR映射关系配置模块确定的降噪力度值，对图像进行降噪处理。在一个示例中，通过加大范围的时域采样滤波(甚至在全局范围内进行采样滤波)，可以实现较大力度值的降噪处理；通过较小范围的时域采样滤波(甚至不进行采样滤波)，可以实现较小力度值的降噪处理。
如图1所示，待降噪图像包括Y通道、U通道和V通道，其中，Y通道代表亮度信息，U通道和V通道代表色度信息。待降噪图像的色度信息图包括待降噪图像的U通道和V通道，待降噪图像的色度信息图包括了待降噪图像中每个像素点的色度值。
如图1所示，将待降噪图像的色度信息图输入CNR映射关系配置模块后，根据CNR映射关系配置模块中配置的色度区间和降噪力度值的映射关系，可以得到待降噪图像中各个像素点对应的降噪力度值。将各个像素点对应的降噪力度值输入至ISP模块后，ISP模块可以按照各个像素点对应的降噪力度值对待降噪图像的Y通道中各个像素点进行降噪处理的降噪力度进行控制，并输出降噪后的Y通道。根据待降噪图像降噪后的Y通道，和待降噪图像的U通道和V通道(未经降噪处理)，可以得到降噪后的待降噪图像。
由此可见，相关技术中可以基于图像的色度信息实现局部不同力度的降噪(即不同区域降噪力度不同)。在某些场景下，基于图像的色度信息实现局部不同力度的降噪，并不能达到预期的降噪效果。
在一个示例中，在夜景拍摄、极暗光拍摄或者屏下摄像头拍摄的场景下，由于进光量不足，需要拍摄多帧图像，并将拍摄到的多帧图像进行融合处理，得到图像质量较高的融合图像，但是欠曝光帧因为大幅提亮而放大噪声，导致了融合图像中高光区域的噪声较大。在又一示例中，在拍摄运动物体的场景下，对拍摄到的多帧图像进行融合处理 的过程中，为了抑制运动鬼影，会降低融合降噪的力度，从而导致融合图像中运动区域的噪声较大。
可见，融合图像中引入了不均匀噪声。由于融合图像中引入的不均匀的噪声与色度信息无明显的直接关系。因此，基于图像的色度信息实现局部不同力度的降噪后，不能有效的去除这些不均匀的噪声。
本公开实施例提供了一种降噪方法，能够基于降噪需求实现局部不同力度的降噪。图2示出根据本公开实施例的降噪方法的流程图。如图2所示，所述方法可以包括：
步骤S11，将待降噪图像的降噪掩码图转换为色度信息图，其中，所述降噪掩码图包括所述待降噪图像中包含的像素点的降噪力度值。
步骤S12，将所述色度信息图输入力度控制模块。
步骤S13，通过所述力度控制模块控制对所述待降噪图像进行降噪处理的降噪力度，得到降噪后的图像。
在本公开实施例中，将需要的像素点的降噪力度值转换成色度信息图，采用该转换得到的色度信息图对降噪力度进行控制，实现了按照需要的降噪力度值对降噪力度进行控制，提高了降噪的灵活性，有效提升了降噪效果。
在一种可能的实现方式中，所述降噪方法可以由终端设备或服务器等电子设备执行，终端设备可以为用户设备(User Equipment，UE)、移动设备、用户终端、终端、蜂窝电话、无绳电话、个人数字处理(Personal Digital Assistant，PDA)、手持设备、计算设备、车载设备、可穿戴设备等，所述方法可以通过处理器调用存储器中存储的计算机可读指令的方式来实现。或者，可通过服务器执行所述方法。
在步骤S11中，可以将待降噪图像的降噪掩码图转换为色度信息图。
其中，待降噪图像可以用于表示任何需要进行降噪处理的图像，本公开实施例对待降噪图像不做限制。在一个示例中，待降噪图像可以通过单个摄像头捕获的图像，也可以为多个图像经图像融合处理得到的融合图像。
待降噪图像的降噪掩码图可以包括待降噪图像中包含的像素点的降噪力度值。待降噪图像的降噪掩码图可以根据需要进行设置。
在一种可能的实现方式中，可以确定所述待降噪图像中的第一区域和第二区域；对所述第一区域中包含的像素点设置第一降噪力度值，并对所述第二区域中包含的像素点设置第二降噪力度值；根据所述第一降噪力度值和所述第二降噪力度值，构建所述待降噪图像的降噪掩码图。
通过对降噪图像划分区域，分别设置各个区域的降噪力度值，可以进一步提升降噪的灵活性。其中，第一区域和第二区域可以根据需要进行确定，确定第一降噪力度值和第二降噪力度值的方式可以根据第一区域和第二区域的特点进行确定。
在一个示例中，第一区域可以为静态区域，第二区域可以为动态区域。
在第一区域为静态区域的情况下，可以根据第一区域中包含的像素点对应的亮度信息，确定第一降噪力度值。
由于静态区域中包含的是静态的物体和背景。对于该区域中包含的像素而言，展示效果主要受到亮度信息影响，因此可以根据各像素点的亮度值确定各像素点对应的第一降噪力度值。例如，对于静态区域中包含的像素点，在该像素点的亮度值较大的情况下，为其设置较大的第一降噪力度值，在该像素点的亮度值较小的情况下，为其设置较小的第一降噪力度值。
在第二区域为动态区域的情况下，可以根据第二区域中包含的像素点对应的运动信息，确定第二降噪力度值。
由于动态区域中包含运动的对象，而对象的运动往往会造成图像模糊，也就是说，动态区域中的噪声是由对象的运动造成的。因此，在一个像素点属于动态区域的情况下，可以获取该像素点对应的运动信息，在运动速度较快或者运动幅度较大的情况下，可以为该像素点设置较大的第二降噪力度值；在运动速度较慢或者运动幅度较小的情况下，可以为该像素点设置较小的第二降噪力度值。这样可以在降低对静态区域影响的基础上，有效去除因运动而造成的噪声。
在一个示例中，第一区域可以为多帧融合区域，第二区域可以为未融合区域。其中，所述多帧融合区域用于表示包含多个图像的信息的区域。未融合区域用于表示包含单一图像的信息的区域。
在第一区域为多帧融合区域的情况下，可以根据第一区域中包含的像素点对应融合度和/或方差，确定第一降噪力度值。其中，融合度和降噪力度值呈负相关，方差和降噪力度值呈正相关。在一个像素对应的融合度较大或者方差较小的情况下，表明该像素点的噪声较小，相应的降噪需求较小，因此第二降噪力度值的取值较小；在融合图像中一个像素对应的融合度较小或者方差较大的情况下，表明该像素点的噪声较大，相应的降噪需求较小，因此第二降噪力度值的取值较小。这样可以在降低对未融合区域影响的基础上，有效去除因图像融合而造成的噪声。
在第二区域为未融合区域的情况下，可以根据第二区域中包含的像素点对应的亮度信息，确定所述第二降噪力度值。例如，为亮度值较大的像素点设置较大的第二降噪力度值，为亮度值较小的像素点设置较小的第二降噪力度值等。
在一个示例中，第一区域可以为高光区域，第二区域可以为非高光区域。
其中，高光区域用于表示所述待降噪图像中亮度大于亮度阈值的像素点组成的区域；非高光区域用于表示所述待降噪图像中除所述高光区域以外的区域。亮度阈值可以根据需要进行设置，例如可以设置为180或者210等。
在第一区域为高光区域的情况下，可以根据所述第一区域和所述第二区域包含的像素点对应亮度值，分别确定所述第一降噪力度值和第二降噪力度值，且所述第一降噪力度值大于所述第二降噪力度值。
考虑到人眼对亮度值较大的区域比较敏感，因此对于亮度值较大的像素点可以设置较大的降噪力度值，对于亮度较小的像素点可以设置较小的降噪力度值。因此，在本公开实施例中，将待降噪图像划分为高光区域和非高光区域，为高光区域确定取值较大的 第一降噪力度值，为非高光区域确定取值较小的第二降噪力度值。这样，可以在降低对非高光区域的影响的基础上，有效去除高光区域的噪声。
由此可见，对于上述提到的在欠曝光帧因为大幅提亮而放大噪声，导致了融合图像中高光区域的噪声较大情况，可以有效去除高亮区域的噪声。
在一个示例中，第一区域可以为目标对象，第二区域可以为背景区域。其中，目标对象可以代表用户较为关注或者较为敏感的区域。例如，目标对象可以为人脸、人体、一个动物、一个建筑物体等。
在第一区域为目标对象的情况下，可以根据第一区域的特征图确定第一降噪力度值。
在一个像素点属于目标对象的情况下，表明用户对其预期的效果。因此，依据其特征图设置其降噪力度值。例如，人脸根据特征图确定五官和皮肤的位置，对五官和皮肤分别设置不同第一降噪力度值。例如，可以为五官设置较小的第一降噪力度值，为皮肤设置较大的第一降噪力度值。
在第二区域为背景区域的情况下，可以根据第二区域包含的像素点对应亮度值确定所述第二降噪力度值。这与未融合区域相似，这里不再赘述。
需要说明的是，还可以通过其他方式获取降噪掩码图，例如用户根据需要自定义的噪声掩码图，本公开实施例对降噪掩码图的获取方式不做限定。
由于图1所示的CNR映射关系配置模块可以处理色度信息图，而无法处理降噪掩码图。因此，可以先在步骤S11中，将待降噪图像的降噪掩码图转换为色度信息图，再将转换得到的色度信息图输入图1所示的CNR映射关系配置模块。
可以理解的是，S11中转换得到的色度信息图中包含的色度值是用于对降噪力度进行控制而设置的，而不是待降噪图像中包含的像素点的真实色度值，不会反映待降噪图像中包含的像素点的真实颜色。
在一种可能的实现方式中，步骤S11可以包括：针对所述待降噪图像中包含的像素点：根据该像素点的降噪力度值，确定该像素点对应的色度区间；根据该像素点对应的色度区间，确定该像素点对应的色度值。
在一个示例中，可以获取用户定义的降噪力度值和色度区间之间的映射关系；针对待降噪图像中包含的每个像素点，根据该用户定义的映射关系和该像素点的降噪力度值，确定该像素点对应的色度区间。
例如，可以在较大的降噪力度值和红色对应的色度区间之间建立映射关系；在较小的降噪力度值和蓝色对应的色度区间之间建立映射关系。
在一个示例中，可以获取力度控制模块对色度区间和降噪力度值进行转换的映射关系；基于所述映射关系与该像素点的降噪力度值，确定该像素点对应的色度区间。
其中，力度控制模块可以控制模块控制对所述待降噪图像进行降噪处理的降噪力度。力度控制模块可以包括图1所示的CNR映射关系配置模块。且CNR映射关系配置模块中可以包括对色度区间和降噪力度值进行转换的映射关系。
在确定像素点对应的色度区间之后，可以从该色度区间中取任意一个色度值作为该 像素点对应的色度值。在一个示例中，可以从该色度区间中取U和V最小的色度值作为该像素点对应的色度值。
可以理解的是，待降噪图像、待降噪图像的降噪掩码图、转换得到的色度信息图和降噪后的图像的维度一致，且像素点一一对应。
在一个示例中，待降噪图像包括Y通道、U通道和V通道，所述色度信息图包括U通道和V通道。
由于步骤S13中力度控制模块可以基于输入的色度信息图，控制对待降噪图像进行降噪处理的降噪力度，而步骤S12中输入力度控制模块的色度信息图反映了待降噪图像中每个像素点的降噪力度值。因此，步骤S13中，力度控制模块实际是按照待降噪图像中包含的像素点的降噪力度值，控制待降噪图像中每个像素点的降噪力度，进行各个像素点的降噪处理，从而得到降噪后的图像。
在一种可能的实现方式中，力度控制模块可以控制对待降噪图像进行建造处理的降噪力度，按照该降噪力度对所述待降噪图像的Y通道进行降噪处理，得到降噪后的Y通道；根据降噪后的Y通道，和所述待降噪图像的U通道和V通道，确定所述降噪后的图像。
对Y通道进行降噪，对U通道和V通道保持不变，既实现了图像的降噪，又保留的图像的色彩信息，提升了降噪效果。
图3示出本公开实施例中CNR架构的示意图。如图3所示，本公开实施例中CNR架构可以包括力度转换模块、CNR映射关系配置模块(即力度控制模块)和ISP模块。
其中，力度转换模块可以用于将降噪掩码图转换为色度信息图。力度转换模块中可以配置降噪力度值和色度区间进行转换的映射关系。力度转换模块中降噪力度值和色度区间进行转换的映射关系可以根据CNR映射关系配置模块中配置的对色度区间和降噪力度值进行转换的映射关系进行设置。例如，在CNR映射关系配置模块中配置了代表红色的色度区间与较大的降噪力度之间建立了进行转换的映射关系的基础上，力度转换模块可以在取值较大的降噪力度值和代表红色的色度区间之间建立进行转换的映射关系(即降噪力度值和色度信息)。CNR映射关系配置模块和ISP模块可以参照相关技术中的CNR架构，这里不再赘述。
下面基于图3对本公开实施例的降噪方法进行说明。
如图3所示，待降噪图像包括Y通道、U通道和V通道，其中，Y通道代表亮度信息，U通道和V通道代表色度信息。待降噪图像的噪声掩码图包括待降噪图像中包含色像素点的降噪力度值。
如图3所示，获取待降噪图像的降噪掩码图；将待降噪图像的降噪掩码图输入力度转换模块后，根据力度转换模块中配置的降噪力度值和色度区间进行转换的映射关系，可以得到控制待降噪图像中每个像素点降噪力度的色度值，即转换得到的色度信息图。
将转换得到的色度信息图输入CNR映射关系配置模块后，根据CNR映射关系配置模块中配置的色度区间和降噪力度值进行转换的映射关系，可以得到控制待降噪图像中包含的像素点进行降噪处理的降噪力度。
CNR映射关系配置模块将控制待降噪图像中包含的像素点进行降噪处理的降噪力度输入至ISP模块后，ISP模块可以按照接收到的降噪力度对待降噪图像的Y通道包含的像素点进行降噪处理，并输出降噪后的Y通道。
根据待降噪图像降噪后的Y通道，和待降噪图像的U通道和V通道(未经降噪处理)，可以得到降噪后的待降噪图像。
由此可见，现有技术中的力度控制模块的色度信息和降噪力度是固定的映射关系，那么通过力度控制模块控制的图像的降噪力度就无法根据需求变换。例如，输入是原始图像，力度控制模块根据原始图像自动计算原始图像中各像素点的降噪力度，那么在任意场景下都是一种固定的变换方法，即该力度控制模块无法根据需求灵活地切换降噪控制方案。本公开实施例中，采用由降噪力度值转换而成的色度信息图，再将色度信息图输入力度控制模块对待降噪图像的降噪力度进行控制。例如，可以根据图像的亮度、运动或自定义信息生成待降噪掩码图，以控制对图像中不同区域实现不同力度的降噪。如此可以任意根据待降噪图像的降噪需求灵活地生成降噪掩码图，从而通过对降噪掩码图转换的色度信息图可以更加灵活的实现图像降噪。
可以理解，本公开提及的上述各个方法实施例，在不违背原理逻辑的情况下，均可以彼此相互结合形成结合后的实施例，限于篇幅，本公开不再赘述。本领域技术人员可以理解，在具体实施方式的上述方法中，各步骤的具体执行顺序应当以其功能和可能的内在逻辑确定。
此外，本公开还提供了降噪装置、电子设备、计算机可读存储介质、程序，上述均可用来实现本公开提供的任一种降噪方法，相应技术方案和描述和参见方法部分的相应记载，不再赘述。
图4示出根据本公开实施例的降噪装置的框图。如图4所示，所述降噪装置40包括：
转换模块41，用于将待降噪图像的降噪掩码图转换为色度信息图，其中，所述降噪掩码图包括所述待降噪图像中包含的像素点的降噪力度值；
输入模块42，用于将所述色度信息图输入力度控制模块；
控制模块43，用于通过所述力度控制模块控制对所述待降噪图像进行降噪处理的降噪力度，得到降噪后的图像。
在一种可能的实现方式中，所述转换模块还用于：
针对所述待降噪图像中包含的像素点：
根据所述像素点的降噪力度值，确定所述像素点对应的色度区间；
根据所述像素点对应的色度区间，确定所述像素点对应的色度值。
在一种可能的实现方式中，所述根据所述像素点的降噪力度值，确定所述像素点对应的色度区间包括：
获取所述力度控制模块对色度区间和降噪力度值进行转换的映射关系；
基于所述映射关系与所述像素点的降噪力度值，确定所述像素点对应的色度区间。
在一种可能的实现方式中，所述装置还包括：
确定模块，用于确定所述待降噪图像中的第一区域和第二区域；
设置模块，用于对所述第一区域中包含的像素点设置第一降噪力度值，并对所述第二区域中包含的像素点设置第二降噪力度值；
构建模块，用于根据所述第一降噪力度值和所述第二降噪力度值，构建所述待降噪图像的降噪掩码图。
在一种可能的实现方式中，所述设置模块还用于：
在所述第一区域为静态区域、所述第二区域为动态区域的情况下，根据所述第一区域中包含的像素点对应的亮度信息，确定所述第一降噪力度值，根据所述第二区域中包含的像素点对应的运动信息，确定所述第二降噪力度值。
在一种可能的实现方式中，所述设置模块还用于：
在所述第一区域为多帧融合区域、所述第二区域为未融合区域的情况下，根据所述第一区域中包含的像素点对应融合度和/或方差，确定所述第一降噪力度值；根据所述第二区域中包含的像素点对应的亮度信息，确定所述第二降噪力度值；其中，所述多帧融合区域用于表示包含多个图像的信息的区域，所述未融合区域用于表示包含单一图像的信息的区域。
在一种可能的实现方式中，所述设置模块还用于：
在所述第一区域为高光区域、所述第二区域为非高光区域的情况下，根据所述第一区域和所述第二区域包含的像素点对应亮度值，分别确定所述第一降噪力度值和第二降噪力度值，且所述第一降噪力度值大于所述第二降噪力度值；
其中，所述高光区域用于表示所述待降噪图像中亮度大于亮度阈值的像素点组成的区域；所述非高光区域用于表示所述待降噪图像中除所述高光区域以外的区域。
在一种可能的实现方式中，所述设置模块还用于：
在所述第一区域为目标对象，所述第二区域为背景区域的情况下，根据所述第一区域的特征图确定所述第一降噪力度值，根据所述第二区域包含的像素点对应亮度值确定所述第二降噪力度值。
在一些实施例中，本公开实施例提供的装置具有的功能或包含的模块可以用于执行上文方法实施例描述的方法，其具体实现和技术效果可以参照上文方法实施例的描述，为了简洁，这里不再赘述。
本公开实施例还提出一种计算机可读存储介质，其上存储有计算机程序指令，所述计算机程序指令被处理器执行时实现上述方法。计算机可读存储介质可以为易失性存储介质或非易失性存储介质。
本公开实施例还提出一种电子设备，包括：处理器；用于存储处理器可执行指令的存储器；其中，所述处理器被配置为调用所述存储器存储的指令，以执行上述方法。
本公开实施例还提供了一种计算机程序产品，包括计算机可读代码，当计算机可读代码在设备上运行时，设备中的处理器执行用于实现如上任一实施例提供的降噪方法的指令。
本公开实施例还提供了另一种计算机程序产品，用于存储计算机可读指令，指令被执行时使得计算机执行上述任一实施例提供的降噪方法的操作。
电子设备可以被提供为终端、服务器或其它形态的设备。
图5示出根据本公开实施例的一种电子设备800的框图。例如，电子设备800可以是移动电话，计算机，数字广播终端，消息收发设备，游戏控制台，平板设备，医疗设备，健身设备，个人数字助理等终端。
参照图5，电子设备800可以包括以下一个或多个组件：处理组件802，存储器804，电源组件806，多媒体组件808，音频组件810，输入/输出(I/O)的接口812，传感器组件814，以及通信组件816。
处理组件802通常控制电子设备800的整体操作，诸如与显示，电话呼叫，数据通信，相机操作和记录操作相关联的操作。处理组件802可以包括一个或多个处理器820来执行指令，以完成上述的方法的全部或部分步骤。此外，处理组件802可以包括一个或多个模块，便于处理组件802和其他组件之间的交互。例如，处理组件802可以包括多媒体模块，以方便多媒体组件808和处理组件802之间的交互。
存储器804被配置为存储各种类型的数据以支持在电子设备800的操作。这些数据的示例包括用于在电子设备800上操作的任何应用程序或方法的指令，联系人数据，电话簿数据，消息，图片，视频等。存储器804可以由任何类型的易失性或非易失性存储设备或者它们的组合实现，如静态随机存取存储器(SRAM)，电可擦除可编程只读存储器(EEPROM)，可擦除可编程只读存储器(EPROM)，可编程只读存储器(PROM)，只读存储器(ROM)，磁存储器，快闪存储器，磁盘或光盘。
电源组件806为电子设备800的各种组件提供电力。电源组件806可以包括电源管理系统，一个或多个电源，及其他与为电子设备800生成、管理和分配电力相关联的组件。
多媒体组件808包括在所述电子设备800和用户之间的提供一个输出接口的屏幕。在一些实施例中，屏幕可以包括液晶显示器(LCD)和触摸面板(TP)。如果屏幕包括触摸面板，屏幕可以被实现为触摸屏，以接收来自用户的输入信号。触摸面板包括一个或多个触摸传感器以感测触摸、滑动和触摸面板上的手势。所述触摸传感器可以不仅感测触摸或滑动动作的边界，而且还检测与所述触摸或滑动操作相关的持续时间和压力。在一些实施例中，多媒体组件808包括一个前置摄像头和/或后置摄像头。当电子设备800处于操作模式，如拍摄模式或视频模式时，前置摄像头和/或后置摄像头可以接收外部的多媒体数据。每个前置摄像头和后置摄像头可以是一个固定的光学透镜系统或具有焦距和光学变焦能力。
音频组件810被配置为输出和/或输入音频信号。例如，音频组件810包括一个麦克风(MIC)，当电子设备800处于操作模式，如呼叫模式、记录模式和语音识别模式时，麦克风被配置为接收外部音频信号。所接收的音频信号可以被进一步存储在存储器804或经由通信组件816发送。在一些实施例中，音频组件810还包括一个扬声器，用于输出音频信号。
I/O接口812为处理组件802和外围接口模块之间提供接口，上述外围接口模块可以是键盘，点击轮，按钮等。这些按钮可包括但不限于：主页按钮、音量按钮、启动按钮和锁定按钮。
传感器组件814包括一个或多个传感器，用于为电子设备800提供各个方面的状态评估。例如，传感器组件814可以检测到电子设备800的打开/关闭状态，组件的相对定位，例如所述组件为电子设备800的显示器和小键盘，传感器组件814还可以检测电子设备800或电子设备800一个组件的位置改变，用户与电子设备800接触的存在或不存在，电子设备800方位或加速/减速和电子设备800的温度变化。传感器组件814可以包括接近传感器，被配置用来在没有任何的物理接触时检测附近物体的存在。传感器组件814还可以包括光传感器，如互补金属氧化物半导体(CMOS)或电荷耦合装置(CCD)图像传感器，用于在成像应用中使用。在一些实施例中，该传感器组件814还可以包括加速度传感器，陀螺仪传感器，磁传感器，压力传感器或温度传感器。
通信组件816被配置为便于电子设备800和其他设备之间有线或无线方式的通信。电子设备800可以接入基于通信标准的无线网络，如无线网络(WiFi)，第二代移动通信技术(2G)或第三代移动通信技术(3G)，或它们的组合。在一个示例性实施例中，通信组件816经由广播信道接收来自外部广播管理系统的广播信号或广播相关信息。在一个示例性实施例中，所述通信组件816还包括近场通信(NFC)模块，以促进短程通信。例如，在NFC模块可基于射频识别(RFID)技术，红外数据协会(IrDA)技术，超宽带(UWB)技术，蓝牙(BT)技术和其他技术来实现。
在示例性实施例中，电子设备800可以被一个或多个应用专用集成电路(ASIC)、数字信号处理器(DSP)、数字信号处理设备(DSPD)、可编程逻辑器件(PLD)、现场可编程门阵列(FPGA)、控制器、微控制器、微处理器或其他电子元件实现，用于执行上述方法。
在示例性实施例中，还提供了一种非易失性计算机可读存储介质，例如包括计算机程序指令的存储器804，上述计算机程序指令可由电子设备800的处理器820执行以完成上述方法。
图6示出根据本公开实施例的一种电子设备1900的框图。例如，电子设备1900可以被提供为一服务器。参照图6，电子设备1900包括处理组件1922，其进一步包括一个或多个处理器，以及由存储器1932所代表的存储器资源，用于存储可由处理组件1922的执行的指令，例如应用程序。存储器1932中存储的应用程序可以包括一个或一个以上的每一个对应于一组指令的模块。此外，处理组件1922被配置为执行指令，以执行上述方法。
电子设备1900还可以包括一个电源组件1926被配置为执行电子设备1900的电源管理，一个有线或无线网络接口1950被配置为将电子设备1900连接到网络，和一个输入输出(I/O)接口1958。电子设备1900可以操作基于存储在存储器1932的操作系统，例如微软服务器操作系统(Windows Server TM)，苹果公司推出的基于图形用户界面操作系统(Mac OS X TM)，多用户多进程的计算机操作系统(Unix TM),自由和开放原代码的类Unix操作 系统(Linux TM)，开放原代码的类Unix操作系统(FreeBSD TM)或类似。
在示例性实施例中，还提供了一种非易失性计算机可读存储介质，例如包括计算机程序指令的存储器1932，上述计算机程序指令可由电子设备1900的处理组件1922执行以完成上述方法。
本公开可以是系统、方法和/或计算机程序产品。计算机程序产品可以包括计算机可读存储介质，其上载有用于使处理器实现本公开的各个方面的计算机可读程序指令。
计算机可读存储介质可以是可以保持和存储由指令执行设备使用的指令的有形设备。计算机可读存储介质例如可以是(但不限于)电存储设备、磁存储设备、光存储设备、电磁存储设备、半导体存储设备或者上述的任意合适的组合。计算机可读存储介质的更具体的例子(非穷举的列表)包括：便携式计算机盘、硬盘、随机存取存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、静态随机存取存储器(SRAM)、便携式压缩盘只读存储器(CD-ROM)、数字多功能盘(DVD)、记忆棒、软盘、机械编码设备、例如其上存储有指令的打孔卡或凹槽内凸起结构、以及上述的任意合适的组合。这里所使用的计算机可读存储介质不被解释为瞬时信号本身，诸如无线电波或者其他自由传播的电磁波、通过波导或其他传输媒介传播的电磁波(例如，通过光纤电缆的光脉冲)、或者通过电线传输的电信号。
这里所描述的计算机可读程序指令可以从计算机可读存储介质下载到各个计算/处理设备，或者通过网络、例如因特网、局域网、广域网和/或无线网下载到外部计算机或外部存储设备。网络可以包括铜传输电缆、光纤传输、无线传输、路由器、防火墙、交换机、网关计算机和/或边缘服务器。每个计算/处理设备中的网络适配卡或者网络接口从网络接收计算机可读程序指令，并转发该计算机可读程序指令，以供存储在各个计算/处理设备中的计算机可读存储介质中。
用于执行本公开操作的计算机程序指令可以是汇编指令、指令集架构(ISA)指令、机器指令、机器相关指令、微代码、固件指令、状态设置数据、或者以一种或多种编程语言的任意组合编写的源代码或目标代码，所述编程语言包括面向对象的编程语言—诸如Smalltalk、C++等，以及常规的过程式编程语言—诸如“C”语言或类似的编程语言。计算机可读程序指令可以完全地在用户计算机上执行、部分地在用户计算机上执行、作为一个独立的软件包执行、部分在用户计算机上部分在远程计算机上执行、或者完全在远程计算机或服务器上执行。在涉及远程计算机的情形中，远程计算机可以通过任意种类的网络—包括局域网(LAN)或广域网(WAN)—连接到用户计算机，或者，可以连接到外部计算机(例如利用因特网服务提供商来通过因特网连接)。在一些实施例中，通过利用计算机可读程序指令的状态信息来个性化定制电子电路，例如可编程逻辑电路、现场可编程门阵列(FPGA)或可编程逻辑阵列(PLA)，该电子电路可以执行计算机可读程序指令，从而实现本公开的各个方面。
这里参照根据本公开实施例的方法、装置(系统)和计算机程序产品的流程图和/或框图描述了本公开的各个方面。应当理解，流程图和/或框图的每个方框以及流程图和/ 或框图中各方框的组合，都可以由计算机可读程序指令实现。
这些计算机可读程序指令可以提供给通用计算机、专用计算机或其它可编程数据处理装置的处理器，从而生产出一种机器，使得这些指令在通过计算机或其它可编程数据处理装置的处理器执行时，产生了实现流程图和/或框图中的一个或多个方框中规定的功能/动作的装置。也可以把这些计算机可读程序指令存储在计算机可读存储介质中，这些指令使得计算机、可编程数据处理装置和/或其他设备以特定方式工作，从而，存储有指令的计算机可读介质则包括一个制造品，其包括实现流程图和/或框图中的一个或多个方框中规定的功能/动作的各个方面的指令。
也可以把计算机可读程序指令加载到计算机、其它可编程数据处理装置、或其它设备上，使得在计算机、其它可编程数据处理装置或其它设备上执行一系列操作步骤，以产生计算机实现的过程，从而使得在计算机、其它可编程数据处理装置、或其它设备上执行的指令实现流程图和/或框图中的一个或多个方框中规定的功能/动作。
附图中的流程图和框图显示了根据本公开的多个实施例的系统、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段或指令的一部分，所述模块、程序段或指令的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个连续的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，框图和/或流程图中的每个方框、以及框图和/或流程图中的方框的组合，可以用执行规定的功能或动作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。
该计算机程序产品可以具体通过硬件、软件或其结合的方式实现。在一个可选实施例中，所述计算机程序产品具体体现为计算机存储介质，在另一个可选实施例中，计算机程序产品具体体现为软件产品，例如软件开发包(Software Development Kit，SDK)等等。
以上已经描述了本公开的各实施例，上述说明是示例性的，并非穷尽性的，并且也不限于所披露的各实施例。在不偏离所说明的各实施例的范围和精神的情况下，对于本技术领域的普通技术人员来说许多修改和变更都是显而易见的。本文中所用术语的选择，旨在最好地解释各实施例的原理、实际应用或对市场中的技术的改进，或者使本技术领域的其它普通技术人员能理解本文披露的各实施例。

Claims (12)

  1. 一种降噪方法，所述方法包括：
    将待降噪图像的降噪掩码图转换为色度信息图，其中，所述降噪掩码图包括所述待降噪图像中包含的像素点的降噪力度值；
    将所述色度信息图输入力度控制模块；
    通过所述力度控制模块控制对所述待降噪图像进行降噪处理的降噪力度，得到降噪后的图像。
  2. 根据权利要求1所述的方法，其中，所述将待降噪图像的降噪掩码图转换为色度信息图包括：
    针对所述待降噪图像中包含的像素点：
    根据所述像素点的降噪力度值，确定所述像素点对应的色度区间；
    根据所述像素点对应的色度区间，确定所述像素点对应的色度值。
  3. 根据权利要求2所述的方法，其中，所述根据所述像素点的降噪力度值，确定所述像素点对应的色度区间包括：
    获取所述力度控制模块对色度区间和降噪力度值进行转换的映射关系；
    基于所述映射关系与所述像素点的降噪力度值，确定所述像素点对应的色度区间。
  4. 根据权利要求1至3中任一项所述的方法，其中，在所述将待降噪图像的降噪掩码图转换为色度信息图之前，所述方法还包括：
    确定所述待降噪图像中的第一区域和第二区域；
    对所述第一区域中包含的像素点设置第一降噪力度值，并对所述第二区域中包含的像素点设置第二降噪力度值；
    根据所述第一降噪力度值和所述第二降噪力度值，构建所述待降噪图像的降噪掩码图。
  5. 根据权利要求4所述的方法，其中，所述对所述第一区域中包含的像素点设置第一降噪力度值，并对所述第二区域中包含的像素点设置第二降噪力度值，包括：
    在所述第一区域为静态区域、所述第二区域为动态区域的情况下，根据所述第一区域中包含的像素点对应的亮度信息，确定所述第一降噪力度值，根据所述第二区域中包含的像素点对应的运动信息，确定所述第二降噪力度值。
  6. 根据权利要求4所述的方法，其中，所述对所述第一区域中包含的像素点设置第一降噪力度值，并对所述第二区域中包含的像素点设置第二降噪力度值，包括：
    在所述第一区域为多帧融合区域、所述第二区域为未融合区域的情况下，根据所述第一区域中包含的像素点对应融合度和/或方差，确定所述第一降噪力度值；根据所述第二区域中包含的像素点对应的亮度信息，确定所述第二降噪力度值；其中，所述多帧融合区域用于表示包含多个图像的信息的区域，所述未融合区域用于表示包含单一图像的信息的区域。
  7. 根据权利要求4所述的方法，其中，所述对所述第一区域中包含的像素点设置第一降噪力度值，并对所述第二区域中包含的像素点设置第二降噪力度值，包括：
    在所述第一区域为高光区域、所述第二区域为非高光区域的情况下，根据所述第一区域和所述第二区域包含的像素点对应亮度值，分别确定所述第一降噪力度值和第二降噪力度值，且所述第一降噪力度值大于所述第二降噪力度值；
    其中，所述高光区域用于表示所述待降噪图像中亮度大于亮度阈值的像素点组成的区域；所述非高光区域用于表示所述待降噪图像中除所述高光区域以外的区域。
  8. 根据权利要求4所述的方法，其中，所述对所述第一区域中包含的像素点设置第一降噪力度值，并对所述第二区域中包含的像素点设置第二降噪力度值，包括：
    在所述第一区域为目标对象，所述第二区域为背景区域的情况下，根据所述第一区域的特征图确定所述第一降噪力度值，根据所述第二区域包含的像素点对应亮度值确定所述第二降噪力度值。
  9. 一种降噪装置，包括：
    转换模块，用于将待降噪图像的降噪掩码图转换为色度信息图，其中，所述降噪掩码图包括所述待降噪图像中包含的像素点的降噪力度值；
    输入模块，用于将所述色度信息图输入力度控制模块；
    控制模块，用于通过所述力度控制模块控制对所述待降噪图像进行降噪处理的降噪力度，得到降噪后的图像。
  10. 一种电子设备，包括：
    处理器；
    用于存储处理器可执行指令的存储器；
    其中，所述处理器被配置为调用所述存储器存储的指令，以执行权利要求1至8中任意一项所述的方法。
  11. 一种计算机可读存储介质，其上存储有计算机程序指令，所述计算机程序指令被处理器执行时实现权利要求1至8中任意一项所述的方法。
  12. 一种计算机程序产品，包括计算机可读代码，当所述计算机可读代码在电子设备中运行时，所述电子设备中的处理器执行用于实现权利要求1至8中的任一项权利要求所述的方法。
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