WO2017101137A1 - 一种高动态范围图像的处理方法、装置及终端设备 - Google Patents

一种高动态范围图像的处理方法、装置及终端设备 Download PDF

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Publication number
WO2017101137A1
WO2017101137A1 PCT/CN2015/098502 CN2015098502W WO2017101137A1 WO 2017101137 A1 WO2017101137 A1 WO 2017101137A1 CN 2015098502 W CN2015098502 W CN 2015098502W WO 2017101137 A1 WO2017101137 A1 WO 2017101137A1
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Prior art keywords
image
information
image information
brightness
processing
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PCT/CN2015/098502
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English (en)
French (fr)
Inventor
李蒙
陈海
郑萧桢
郑建铧
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华为技术有限公司
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Priority to CN201580085179.8A priority Critical patent/CN108370442B/zh
Priority to EP15910606.1A priority patent/EP3364654B1/en
Publication of WO2017101137A1 publication Critical patent/WO2017101137A1/zh
Priority to US15/986,184 priority patent/US10783621B2/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/90—Dynamic range modification of images or parts thereof
    • G06T5/92—Dynamic range modification of images or parts thereof based on global image properties
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/85—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/124—Quantisation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/44—Decoders specially adapted therefor, e.g. video decoders which are asymmetric with respect to the encoder
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/70—Circuitry for compensating brightness variation in the scene
    • H04N23/71—Circuitry for evaluating the brightness variation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/80—Camera processing pipelines; Components thereof
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20172—Image enhancement details
    • G06T2207/20208—High dynamic range [HDR] image processing

Definitions

  • the present invention relates to the field of image processing technologies, and in particular, to a method, an apparatus, and a terminal device for processing a high dynamic range image.
  • the dynamic range represents the ratio between the maximum gray value and the minimum gray value within the range in which the image can be displayed.
  • the brightness ranges from 10 -3 nits to 10 4 nits, and the real world brightness range can reach 10 7 , which is called high dynamic range (HDR). ).
  • HDR high dynamic range
  • each of the R, G, and B channels is stored with one byte and 8 bits, that is, the representation range of each channel is 0 to 255 gray levels, that is, the dynamic range of the color digital image. It is 0 to 255 and is called low dynamic range (LDR).
  • LDR low dynamic range
  • the imaging process of a digital camera is actually a mapping of the high dynamic range of the real world to the low dynamic range of the image.
  • a conventional HDR image processing method includes an encoding and decoding process of an HDR image, wherein the encoding process of the HDR image is: non-linear mapping of stored RGB information (RGB information is real-world luminance information) by a photoelectric transfer function, The RGB information obtained by the linear mapping is quantized to obtain 10-bit data, and the 10-bit data is encoded.
  • the decoding process of the HDR image is: decoding the encoded data to obtain 10 bit data, inversely quantizing the 10 bit data to obtain the nonlinearly mapped RGB information, and transferring the nonlinearly mapped RGB information into the real world through the electro-optical transfer function. Brightness information, and output the transferred RGB information.
  • the Weber score is the main index used to measure the quality of curve quantization.
  • the luminance value in each interval is obtained by the photoelectric transfer function. If the luminance score of each interval is quantized, the smaller the Weber score is calculated, indicating that the quantization quality of the luminance is higher. High; if the resulting Weber score is above the limit value, there will be banding noise that the human eye can perceive.
  • the brightness information of the image is a real-world light signal, which may be represented by “L” or “E”, and generally records a value corresponding to a specific color component (for example, R, G, B, or Y, etc.), usually with light intensity. In direct proportion.
  • the optical signal image information is obtained by photoelectrically converting the luminance information of the image by a photoelectric transfer function, and the converted electrical signal image information can be represented by "L'" and "E", and represents a digital expression value of an image luminance signal.
  • the electrical signal obtained by the photoelectric transfer function conversion may include primary colors such as R, G, B, and Y.
  • the brightness information of the image can be expressed by the true brightness (such as 10000 nits), or by the normalized brightness, for example, according to the maximum brightness of 10,000 nits, normalized to a maximum brightness of 1.
  • the input image information (electrical signal) is electro-optically converted by an electro-optical transfer function to obtain brightness information of the image, and the image brightness information is a restored real-world optical signal.
  • the photoelectric transfer function in the conventional scheme 1 is proposed based on the brightness perception model of the human eye.
  • the photoelectric transfer function can be:
  • the Weber score is the main indicator used to measure the quality of curve quantization. Take the Weber score shown in Figure 1A as an example.
  • the first curve is the Schreiber Threshold in the ITU Report BT.2246 standard file, which is obtained by the photoelectric transfer function.
  • the brightness value of each interval the smaller the Weber score calculated by quantifying the luminance value curve of each interval, indicates that the quantization quality of the brightness is higher; if the obtained Weber score is above the Schreiber Threshold, human vision will appear. Can detect the banding noise.
  • the second curve is the Weber score obtained by the photoelectric transfer function in the first scheme. The second curve has a Weber score below 0.1 nits exceeding the Schreiber Threshold, and the output HDR image produces band noise that can be perceived by the human eye. Can not meet the quality requirements.
  • the present application provides a method, an apparatus, and a terminal device for processing a high dynamic range image, which can improve the quantization quality.
  • the first aspect provides a method for processing a high dynamic range image, the method comprising:
  • the terminal device acquires brightness information of the image.
  • the terminal device processes the brightness information as follows to obtain processed image information:
  • a, b, m, and p are rational numbers
  • L is luminance information of an image
  • L' is image information after processing.
  • the terminal device quantizes the processed image information to obtain quantized image information.
  • the terminal device encodes the quantized image information to obtain encoded image information.
  • the dynamic range of the display device is 0 to 255 gray levels, and the dynamic range of the real world reaches 10 7 . Since the dynamic range focuses on the brightness information, the brightness range of the display device is insufficient to express the brightness of the real world. The domain, if the entire brightness field of the real world is simply compressed linearly into the brightness field that the display device can express, more details will be lost at both ends of the light and dark. In order to overcome this situation, a photoelectric transfer function is proposed.
  • the conventional photoelectric transfer function can be the photoelectric transfer function in the first scheme, as shown in FIG. 1A, the second curve is the Weber score obtained by the photoelectric transfer function in the first scheme, and the fourth curve is obtained by the photoelectric transfer function of the present application. Weber score.
  • the Weber score of the second curve below the brightness value of 0.1 nits exceeds the Schreiber Threshold, and the output HDR image will produce banding noise that the human eye can detect, which cannot meet the quality requirements.
  • the fourth curve satisfies the Schreiber Threshold, the brightness value can reach 10000 nits, so the processing method of the high dynamic range image provided by the present application can improve the quantization quality.
  • the unit of the luminance information is nits.
  • the brightness information of the image may include brightness information of each channel, for example, when the image is an RGB image, the brightness information may include brightness information of the R, G, and B channels; when the image is an image of the Lab mode, the brightness The information may include luminance information of the L, a, and b channels.
  • the brightness information may include a normalized brightness, for example, dividing the brightness of the real world by 10 4 to obtain a normalized brightness, and the normalized brightness is in the range of 0 to 1.
  • a, b, m, and p are rational numbers.
  • the terminal device may process the brightness information as follows to obtain the processed image information: Among them, a, b, and m are rational numbers, L is luminance information of an image, and L' is image information after processing.
  • a, b, m, and p are preset rational numbers, and may be empirical values determined by the researcher, or may be values derived by Weber scores during the experiment, which are not specifically in the embodiment of the present invention. limits.
  • a conventional HDR video stream coding framework may include a photoelectric transfer module, a space conversion module, a quantization module, and an encoding module.
  • the photoelectric transfer module is configured to photoelectrically transfer the brightness information of the image through a photoelectric transfer function to obtain an electrical signal after photoelectric transfer.
  • the space transfer module is configured to transfer the photoelectrically transferred electrical signal to the YCBCR space to obtain image information after spatial transfer.
  • the quantization module is configured to quantize the image information after spatial transfer in the YCBCR space, and convert it into 8/10-bit data by a quantization operation.
  • the encoding module is configured to encode the quantized image information to obtain encoded image information. Then the terminal device passes the After photoelectrically transferring the brightness information of the image to obtain an electrical signal after photoelectric transfer, the photoelectrically transferred electrical signal can be transferred to the YCBCR space through a preset space transfer function to obtain image information after spatial transfer, in the YCBCR space pair.
  • the image information after the spatial transfer is quantized to obtain the quantized image information, and the quantized image information is encoded to obtain the encoded image information.
  • the YCBCR space is a color space, and the YCBCR space is used to effectively transmit an image by compressing the brightness information.
  • the terminal device can combine the processing method of the high dynamic range image provided by the present application with the traditional ISO standard HDR video coding framework to improve the resource utilization while improving the quantization quality.
  • a conventional HDR video coding framework may include a photoelectric transfer module, a quantization module, a format conversion module, and an encoding module.
  • the photoelectric transfer module is configured to photoelectrically transfer the brightness information of the image through a photoelectric transfer function to obtain an electrical signal after photoelectric transfer.
  • the quantization module is configured to quantize the electrical signal after photoelectric transfer, and convert to a 10-bit fixed point number by a quantization operation.
  • a format conversion module for converting the format of the quantized image information from 4:4:4 to 4:2:0.
  • the encoding module is configured to encode the formatted image information to obtain encoded image information. Then the terminal device passes the After photoelectrically transferring the brightness information of the image to obtain an electrical signal after photoelectric transfer, the photoelectric signal can be quantized to obtain quantized image information, and the quantized image information is format converted to obtain a format conversion. The image information is encoded by the formatted image information to obtain the encoded image information.
  • the second aspect provides a method for processing a high dynamic range image, the method comprising:
  • the terminal device acquires the encoded image information.
  • the terminal device decodes the encoded image information to obtain decoded image information.
  • the terminal device inversely quantizes the decoded image information to obtain inverse quantized image information.
  • the terminal device processes the inverse quantized image information as follows to obtain processed image information.
  • a, b, m, and p are rational numbers
  • L' is inverse quantized image information
  • L is processed image information
  • the processing method of the high dynamic range image of the second aspect is the inverse of the processing method of the high dynamic range image of the first aspect.
  • a, b, m, and p are rational numbers.
  • the terminal device may perform the following processing on the inverse quantized image information to obtain the processed image information:
  • a, b, and m are rational numbers
  • L' is inverse quantized image information
  • L is processed image information.
  • a, b, m, and p are preset rational numbers, and may be empirical values determined by the researcher, or may be values derived by Weber scores during the experiment, which are not specifically in the embodiment of the present invention. limits.
  • the terminal device can combine the processing method of the high dynamic range image provided by the present application with the traditional HDR video stream decoding framework, and improve the resource utilization rate while improving the quantization quality.
  • a conventional HDR video stream decoding framework may include a decoding module, an inverse quantization module, a spatial conversion module, and an electro-optic transfer module. And a decoding module, configured to decode the encoded image information.
  • An inverse quantization module is configured to inverse quantize the decoded image information to obtain floating point data of [0, 1].
  • the space transfer module is configured to transfer the inverse quantized image information from the YCBCR space to the RGB space or the Lab space to obtain an electrical signal.
  • the electro-optic transfer module is configured to perform electro-optical transfer on the electrical signal to obtain luminance information of a 16-bit half floating point number or a 32-bit floating point number after the electro-optical transfer.
  • the terminal device can obtain the encoded image information, decode the encoded image information, obtain the decoded image information, and inversely quantize the decoded image information to obtain the inverse quantized image information, and pass the preset space.
  • the transfer function transfers the inverse quantized image information from the YCBCR space to the RGB space or the Lab space to obtain an electrical signal, which is passed through the present application.
  • the electrical signal is electro-optically transferred to obtain luminance information.
  • the terminal device can combine the processing method of the high dynamic range image provided by the present application with the traditional ISO standard HDR video decoding framework to improve the resource utilization rate while improving the quantization quality.
  • a conventional HDR video decoding framework may include a decoding module, a format conversion module, an inverse quantization module, and an electro-optic transfer module. And a decoding module, configured to decode the encoded image information.
  • a format conversion module for converting the format of the decoded image information from 4:2:0 to 4:4:4.
  • the inverse quantization module is configured to inverse quantize the image information after the format conversion to obtain an electrical signal.
  • the electro-optical transfer module is configured to perform electro-optical transfer on the electrical signal to obtain brightness information after electro-optical transfer.
  • the terminal device can obtain the encoded image information, decode the encoded image information, obtain the decoded image information, perform format conversion on the decoded image information, obtain format-converted image information, and convert the formatted image.
  • Image information is inverse quantized to obtain an electrical signal, by the present application
  • the electrical signal is electro-optically transferred to obtain luminance information.
  • a third aspect provides a computer storage medium, wherein the computer storage medium can store a program that, when executed, includes some or all of the steps of the first aspect.
  • a fourth aspect provides a computer storage medium, wherein the computer storage medium can store a program that, when executed, includes some or all of the steps of the second aspect.
  • a fifth aspect provides a processing apparatus for a high dynamic range image, the apparatus comprising modules operable to implement some or all of the steps in connection with the first aspect.
  • a sixth aspect provides a processing apparatus for a high dynamic range image, the apparatus comprising modules operable to implement some or all of the steps in connection with the second aspect.
  • a seventh aspect provides a terminal device, the terminal device comprising a processor and a memory, wherein the memory is configured to store instructions, and the processor is configured to execute instructions, when the processor is executing the instructions, can be used to implement the part in combination with the first aspect Or all steps.
  • An eighth aspect provides a terminal device including a processor and a memory, wherein the memory is configured to store an instruction, and the processor is configured to execute an instruction, when the processor is executing the instruction, may be used to implement a part combining the second aspect Or all steps.
  • FIG. 1A is a schematic diagram of an interface of a Weber score provided in an embodiment of the present invention.
  • 1B is a schematic diagram of an interface of a quantization curve of a rational quantization function provided in an embodiment of the present invention
  • 1C is a schematic diagram of an interface of a luminance statistical curve provided in an embodiment of the present invention.
  • FIG. 2 is a schematic flowchart of a method for processing a high dynamic range image according to an embodiment of the present invention
  • FIG. 3 is a schematic flow chart of a method for processing a high dynamic range image according to another embodiment of the present invention.
  • FIG. 4 is a schematic structural diagram of a terminal device according to an embodiment of the present invention.
  • FIG. 5 is a schematic structural diagram of a processing apparatus for a high dynamic range image according to an embodiment of the present invention.
  • FIG. 6 is a diagram of a processing apparatus for a high dynamic range image provided in another embodiment of the present invention. Schematic diagram.
  • FIG. 2 is a schematic flowchart of a method for processing a high dynamic range image according to an embodiment of the present invention.
  • the method for processing a high dynamic range image in the embodiment of the present invention may include at least:
  • the first terminal device performs photoelectric transfer on the brightness information of the image by using a preset photoelectric transfer function to obtain an electrical signal after photoelectric transfer.
  • the first terminal device can perform photoelectric transfer on the brightness information of the image through a preset photoelectric transfer function to obtain an electrical signal after photoelectric transfer.
  • the first terminal device may be a satellite, a personal computer (PC), or a smart phone.
  • the quantization curve is a variation that simulates the perception details of the human eye for different brightnesses.
  • the real world brightness distribution curve is significantly different from the human eye's brightness perception curve.
  • dynamic range statistics are performed on the existing CT2020HDR HD sequence, and the statistics are divided into six sections according to the luminance interval. The statistical results are shown in Table 1:
  • the HDR sequence has a high dynamic range
  • the main brightness is distributed from 0 to 2000 nits.
  • the brightness distribution from 0 to 1000 nits accounts for 80%-99%
  • the brightness distribution between 0 and 2000 nits accounts for 97%-99%. Therefore, considering the sensitivity of the human eye to brightness, from the perspective of human visual characteristics, the range of luminance from 0 to 10000 nits is used as the luminance segment to which the quantization curve is mainly protected.
  • the traditional rational quantization function is: Where p is the preset parameter, L is the real world luminance information, and F(L) is the quantization value.
  • p is the preset parameter
  • L is the real world luminance information
  • F(L) is the quantization value.
  • the curve form is simpler and has better adaptive characteristics, which can satisfy the brightness perception characteristics of the human eye, but the Weber score of the rational quantization curve is poor and low.
  • the dynamic range of the Schreiber Threshold is very narrow and cannot be completely distributed under the Schreiber Threshold.
  • the gamma function is defined in the ITU-R Recommendation BT.1886 standard.
  • the Gamma function is an early photoelectric transfer function.
  • the Gamma function is as follows:
  • L is the electrical signal after photoelectric transfer
  • V is the brightness information of the real world
  • r 2.4.
  • the quality of the image displayed on a display device having a brightness of 100 nits by the Gamma function is good.
  • the image output by the Gamma function cannot be normally displayed on the display device.
  • the embodiment of the present invention combines the rational quantization function and the gamma function, and proposes the photoelectric transfer function in the present application.
  • the Weber score calculated by the photoelectric transfer function conforms to the distribution characteristics of the scene brightness statistics, so that the quantization curve is more in line with the human eye perception.
  • the first curve is the luminance statistical curve of the first scheme
  • the second curve is the luminance statistical curve of the present application
  • the second curve is raised relative to the first curve in the range of 0 to 1000 nits. Fast, it means better strip noise suppression in the low brightness part.
  • the photoelectric transfer function applies the traditional Gamma function at the low end, and the log curve is applied at the high end.
  • the Hybrid Log-Gamma transfer function is proposed, and the Hybrid Log-Gamma function is used. Can be as follows:
  • E' is the electrical signal after photoelectric transfer
  • E is the real world brightness information
  • a, b, c and r are preset parameters.
  • the dynamic range of Option 2 is only 0-2000 nits, and the part over 2000 nits will be intercepted to 2000 nits.
  • the first curve is the Schreiber Threshold in the ITU Report BT.2246 standard file
  • the second curve is the Weber score obtained by the photoelectric transfer function in the first scheme
  • the third curve is the pass scheme.
  • the fourth curve is the Weber score obtained by the photoelectric transfer function of the present application.
  • the second curve does not satisfy the Schreiber Threshold below 0.1 nits.
  • the curve of the third curve has a small quantization range of 0.01 nits to 2000 nits
  • the fourth curve has a quantization range of 10,000 nits, which is more in line with the human eye perception.
  • the first terminal device transfers the photoelectrically transferred electrical signal from the RGB space or the Lab space to the YCBCR space by using a preset first space transfer function to obtain image information.
  • the first terminal device quantizes the image information in the YCBCR space to obtain the quantized image information.
  • the first terminal device encodes the quantized image information to obtain encoded image information.
  • the first terminal device sends the encoded image information to the second terminal device.
  • the second terminal device decodes the encoded image information to obtain decoded image information.
  • the second terminal device may decode the encoded image information to obtain decoded image information.
  • the second terminal device may be a digital television receiving terminal, a PC or a smart phone.
  • the second terminal device inversely quantizes the decoded image information to obtain an inverse quantized image. Like information.
  • the second terminal device transfers the inverse quantized image information from the YCBCR space to the RGB space or the Lab space by using a preset second space transfer function to obtain an electrical signal.
  • the second terminal device performs electro-optical transfer on the electrical signal that needs to be electrically transferred by using a preset electro-optical transfer function to obtain luminance information.
  • the second terminal device outputs the brightness information.
  • the original photoelectric conversion module is updated to the photoelectric transfer function of the present application
  • the original electro-optic transfer module is updated to the electro-optic transfer function of the present application.
  • the processing method of the high dynamic range image saves 18.8% of the code rate and the peak signal to noise ratio (Masked Peak Signal) of the Peak Signal to Noise Ratio (PSNR) compared with the original video stream coding and decoding method.
  • To Noise Ratio (MPSNR) saves 20.3% of the code rate and saves 9% of the code rate for Delta-E ( ⁇ E, the test unit for human eye perception chromatic aberration).
  • the first terminal device performs photoelectric transfer on the brightness information of the image through a preset photoelectric transfer function to obtain an electrical signal after photoelectric transfer, and passes through the preset first space.
  • the transfer function transfers the photoelectrically transferred electrical signal from the RGB space or the Lab space to the YCBCR space to obtain image information, quantizes the image information in the YCBCR space, obtains the quantized image information, and encodes the quantized image information, and Transmitting the encoded image information to the second terminal device, and the second terminal device decodes the encoded image information to obtain decoded image information, and inversely quantizes the decoded image information to obtain inverse quantized image information.
  • the inverse quantized image information is transferred from the YCBCR space to the RGB space or the Lab space through a preset second spatial transfer function to obtain an electrical signal, and the electrical signal currently required to be electro-optically transferred is electro-optically transmitted through a preset electro-optic transfer function. Transfer, get brightness information, and output brightness information, which can improve the quality of quantization and improve Resource utilization.
  • FIG. 3 is a schematic flowchart of a method for processing a high dynamic range image according to another embodiment of the present invention.
  • the method for processing a high dynamic range image in the embodiment of the present invention may include at least :
  • the terminal device performs photoelectric transfer on the brightness information of the image by using a preset photoelectric transfer function.
  • the electrical signal after photoelectric transfer is obtained.
  • the terminal device can perform photoelectric transfer on the brightness information of the image through a preset photoelectric transfer function to obtain an electrical signal after photoelectric transfer.
  • the terminal device may be a smart phone, a camera or a tablet computer.
  • the image may be captured by a camera or pre-stored locally.
  • the terminal device quantizes the electrical signal after the photoelectric transfer to obtain the quantized image information.
  • the terminal device performs format conversion on the quantized image information to obtain format-converted image information.
  • the terminal device encodes the format-converted image information to obtain encoded image information.
  • the terminal device decodes the encoded image information to obtain decoded image information.
  • the terminal device performs format conversion on the decoded image information to obtain format-converted image information.
  • the terminal device inversely quantizes the image information after the format conversion to obtain an electrical signal.
  • the terminal device performs electro-optical transfer on the electrical signal that needs to be electrically and optically transferred through a preset electro-optical transfer function to obtain luminance information.
  • the terminal device outputs brightness information.
  • the terminal device photoelectrically transfers the luminance information of the image through a preset photoelectric transfer function to obtain an electrical signal after photoelectric transfer, and quantizes the electrical signal after photoelectric transfer.
  • Obtaining the quantized image information performing format conversion on the quantized image information, obtaining format-converted image information, encoding the format-converted image information, decoding the encoded image information, and obtaining the decoded image
  • the information is formatted by the decoded image information to obtain the image information after the format conversion, and the image information after the format conversion is inverse quantized to obtain an electrical signal, and the current electro-optical transfer current is required through a preset electro-optic transfer function.
  • the signal is subjected to electro-optical transfer to obtain luminance information, thereby outputting luminance information, which can improve the quantization quality and improve resource utilization.
  • FIG. 4 is a schematic structural diagram of a terminal device according to an embodiment of the present invention.
  • the terminal device may include a processor 401, a memory 402, an input device 403, and an output device 404.
  • the processor 401 is connected to the memory 402, the input device 403, and the output device 404, for example, processor 401 can be coupled to memory 402, input device 403, and output device 404 via a bus.
  • the processor 401 may be a central processing unit (CPU), a network processor (NP), or the like.
  • the memory 402 can be specifically used for luminance information of an image or the like.
  • the memory 402 may include a volatile memory such as a random-access memory (RAM); the memory may also include a non-volatile memory such as a read-only memory (read- Only memory, ROM), flash memory, hard disk drive (HDD) or solid-state drive (SSD); the memory may also include a combination of the above types of memory.
  • RAM random-access memory
  • ROM read-only memory
  • flash memory flash memory
  • HDD hard disk drive
  • SSD solid-state drive
  • the output device 404 is configured to output brightness information, such as a wireless interface or a wired interface.
  • the processor 401 calls the program stored in the memory 402, and can perform the following operations:
  • the processor 401 is configured to acquire brightness information of an image.
  • the processor 401 is further configured to process the brightness information by the following processing to obtain processed image information.
  • a, b, m, and p are rational numbers
  • L is luminance information of an image
  • L' is image information after processing.
  • the processor 401 is further configured to quantize the processed image information to obtain quantized image information.
  • the processor 401 is further configured to encode the quantized image information to obtain encoded image information.
  • the terminal device introduced in the embodiment of the present invention may be used to implement some or all of the processes in the embodiment of the method for processing a high dynamic range image introduced in conjunction with FIG. 2 or FIG.
  • FIG. 4 is a schematic structural diagram of a terminal device according to an embodiment of the present invention.
  • the terminal device may include a processor 401, a memory 402, an input device 403, and an output device 404.
  • the processor 401 is connected to the memory 402, the input device 403, and the output device 404.
  • the processor 401 can be connected to the memory 402, the input device 403, and the bus through a bus.
  • Output device 404 can be connected to the memory 402, the input device 403, and the bus through a bus.
  • the processor 401 can be a central processing unit, a network processor, or the like.
  • the memory 402 can be specifically used to store brightness information of an image or the like.
  • the memory 402 can include volatile memory, such as random access memory; the memory can also include non-volatile memory, such as read only memory, flash memory, hard disk or solid state hard disk; the memory can also include a combination of the above types of memory.
  • the input device 403 is configured to obtain encoded image information, such as a wireless interface or a wired interface.
  • the output device 404 is configured to output brightness information, such as a display screen.
  • the processor 401 calls the program stored in the memory 402, and can perform the following operations:
  • the processor 401 is configured to obtain encoded image information.
  • the processor 401 is further configured to decode the encoded image information to obtain decoded image information.
  • the processor 401 is further configured to perform inverse quantization on the decoded image information to obtain inverse quantized image information.
  • the processor 401 is further configured to perform the following processing on the inverse quantized image information to obtain processed image information:
  • a, b, m, and p are rational numbers
  • L' is inverse quantized image information
  • L is processed image information
  • the terminal device introduced in the embodiment of the present invention may be used to implement some or all of the processes in the embodiment of the method for processing a high dynamic range image introduced in conjunction with FIG. 2 or FIG.
  • FIG. 5 is a schematic structural diagram of a processing apparatus for a high dynamic range image according to an embodiment of the present invention.
  • the apparatus for processing a high dynamic range image according to an embodiment of the present invention may be used to implement the combination of the present invention. 2 or part or all of the processes in the embodiment of the processing method of the high dynamic range image introduced in FIG.
  • the processing device of the high dynamic range image in the embodiment of the present invention may include at least a brightness information acquiring module 501, a brightness information processing module 502, a quantization module 503, and Encoding module 504, wherein:
  • the brightness information acquiring module 501 is configured to acquire brightness information of the image.
  • the brightness information processing module 502 is configured to process the brightness information by performing the following processing to obtain the processed image information:
  • a, b, m, and p are rational numbers
  • L is luminance information of an image
  • L' is image information after processing.
  • the quantization module 503 is configured to quantize the processed image information to obtain quantized image information.
  • the encoding module 504 is configured to encode the quantized image information to obtain encoded image information.
  • the luminance information acquiring module 501 acquires the luminance information of the image
  • the luminance information processing module 502 processes the luminance information to obtain the processed image information
  • the quantization module 503 processes the processed image.
  • the image information is quantized to obtain the quantized image information
  • the encoding module 504 encodes the quantized image information to obtain the encoded image information, thereby improving the quantization quality.
  • FIG. 6 is a schematic structural diagram of a high dynamic range image processing apparatus according to another embodiment of the present invention, where a high dynamic range image processing apparatus according to an embodiment of the present invention can be used to implement the present invention.
  • the processing apparatus of the high dynamic range image in the embodiment of the present invention may include at least an image information acquiring module 601, a decoding module 602, an inverse quantization module 603, and an image information processing module 604, wherein:
  • the image information obtaining module 601 is configured to obtain the encoded image information.
  • the decoding module 602 is configured to decode the encoded image information to obtain decoded image information.
  • the inverse quantization module 603 is configured to inverse quantize the decoded image information to obtain inverse quantized image information.
  • the image information processing module 604 is configured to perform the following processing on the inverse quantized image information, Get processed image information:
  • a, b, m, and p are rational numbers
  • L' is inverse quantized image information
  • L is processed image information
  • the image information acquiring module 601 acquires the encoded image information
  • the decoding module 602 decodes the encoded image information to obtain decoded image information
  • the inverse quantization module 603 The decoded image information is inverse quantized to obtain inverse quantized image information
  • the image information processing module 604 performs the following processing on the inverse quantized image information to obtain processed image information, thereby improving the quantization quality.
  • a, b, m, and p are rational numbers.
  • first and second are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated.
  • features defining “first” or “second” may include at least one of the features, either explicitly or implicitly.
  • the meaning of "a plurality” is at least two, such as two, three, etc., unless specifically defined otherwise.
  • a "computer-readable medium” can be any apparatus that can include, store, communicate, propagate, or transport a program for use in an instruction execution system, apparatus, or device, or in conjunction with such an instruction execution system, apparatus, or device.
  • computer readable media include the following: electrical connections (electronic devices) having one or more wires, portable computer disk cartridges (magnetic devices), random access memory, read only memory , erasable editable read-only memory, fiber optic devices, and portable optical disk read-only memory.
  • the computer readable medium may even be a paper or other suitable medium on which the program can be printed, as it may be optically scanned, for example by paper or other medium, followed by editing, interpretation or, if appropriate, other suitable The method is processed to obtain the program electronically and then stored in computer memory.
  • portions of the invention may be implemented in hardware, software, firmware or a combination thereof.
  • multiple steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system.
  • a suitable instruction execution system For example, if implemented in hardware, as in another embodiment, it can be implemented by any one or combination of the following techniques well known in the art: having logic gates for implementing logic functions on data signals. Discrete logic circuits, application specific integrated circuits with suitable combinational logic gates, programmable gate arrays, field programmable gate arrays, and the like.
  • modules in various embodiments of the present invention may be implemented in the form of hardware or It is implemented in the form of a software function module.
  • An integrated module can also be stored in a computer readable storage medium if it is implemented as a software functional module and sold or used as a standalone product.

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Abstract

本发明实施例公开了一种高动态范围图像的处理方法、装置及终端设备，所述方法包括：获取图像的亮度信息；将亮度信息经过处理，得到处理后的图像信息；对处理后的图像信息进行量化，得到量化后的图像信息；对量化后的图像信息进行编码，得到编码后的图像信息。采用本发明实施例，可提高量化质量。

Description

一种高动态范围图像的处理方法、装置及终端设备 技术领域
本发明涉及图像处理技术领域，尤其涉及一种高动态范围图像的处理方法、装置及终端设备。
背景技术
在数字图像中，动态范围表示在图像可显示的范围内最大灰度值和最小灰度值之间的比率。对真实世界中的自然场景来说，亮度在10-3尼特(nits)到104nits范围内，则真实世界的亮度范围可以达到107，称之为高动态范围(high dynamic range，HDR)。目前大部分的彩色数字图像中，R、G、B各通道分别使用一个字节8位来存储，也就是说，各通道的表示范围是0～255灰度级，即彩色数字图像的动态范围是0～255，称之为低动态范围(low dynamic range，LDR)。则数码相机的成像过程实际上就是真实世界的高动态范围到图像的低动态范围的映射。传统的HDR图像的处理方法包括HDR图像的编码和解码过程，其中HDR图像的编码过程为：将存储的RGB信息(RGB信息为真实世界的亮度信息)通过光电转移函数进行非线性映射，将非线性映射得到的RGB信息进行量化，得到10bit数据，对10bit数据进行编码。HDR图像的解码过程为：对编码后的数据进行解码得到10bit数据，对10bit数据进行反量化得到非线性映射后的RGB信息，通过电光转移函数将非线性映射后的RGB信息转移为真实世界的亮度信息，并输出转移后的RGB信息。Weber分数是用来衡量曲线量化质量的主要指标，通过光电转移函数得到在各区间的亮度值，如果对各区间的亮度值曲线量化后计算得到的Weber分数越小，表明该亮度的量化质量越高；如果得到的Weber分数在限制值之上，则会出现人眼视觉能察觉的条带噪声。其中，图像的亮度信息为真实世界的光信号，可以用“L”或者“E”表示，一般记录着对应于特定颜色分量(例如R、G、B或Y等)的数值，通常与光强度成正比。通过光电转移函数对图像的亮度信息进行光电转换得到电信号图像信息，转换得到的电信号图像信息可以用“L′”“E′”表示， 表示一个图像亮度信号的数字表达值。光电转移函数转换得到的电信号可以包括R、G、B以及Y等基色。图像的亮度信息可以用真实的亮度(如10000尼特)来表示，也可以用归一化的亮度来表示，比如按照最大亮度10000尼特，归一化为最大亮度为1。通过电光转移函数对输入的图像信息(电信号)进行电光转换得到图像的亮度信息，该图像亮度信息为还原的真实世界的光信号。
传统的方案一中的光电转移函数是根据人眼的亮度感知模型所提出的。该光电转移函数可以为：
R′＝PQ_TF(max(0,min(R/10000,1)))
G′＝PQ_TF(max(0,min(G/10000,1)))
B′＝PQ_TF(max(0,min(B/10000,1)))
Figure PCTCN2015098502-appb-000001
其中m1＝0.1593017578125，m2＝78.84375，c1＝0.8359375，c2＝18.8515625，c3＝18.6875。
Weber分数是用来衡量曲线量化质量的主要指标，以图1A所示的Weber分数为例，第一曲线为ITU Report BT.2246标准文件中的施赖伯阈值(Schreiber Threshold)，通过光电转移函数得到在各区间的亮度值，对各区间的亮度值曲线量化后计算得到的Weber分数越小，表明该亮度的量化质量越高；如果得到的Weber分数在该Schreiber Threshold之上，则会出现人眼视觉能察觉的条带噪声。第二曲线为通过方案一中的光电转移函数得到的Weber分数，第二曲线在亮度值为0.1nits以下的Weber分数超过了Schreiber Threshold，则输出的HDR图像会产生人眼能察觉的条带噪声，不能满足质量上的要求。
发明内容
本申请提供一种高动态范围图像的处理方法、装置及终端设备，可提高量化质量。
第一方面提供了一种高动态范围图像的处理方法，所述方法包括：
终端设备获取图像的亮度信息。
终端设备将亮度信息经过如下处理，得到处理后的图像信息：
Figure PCTCN2015098502-appb-000002
其中，a、b、m以及p为有理数，L为图像的亮度信息，L′为处理后的图像信息。
终端设备对处理后的图像信息进行量化，得到量化后的图像信息。
终端设备对量化后的图像信息进行编码，得到编码后的图像信息。
在该技术方案中，显示设备的动态范围是0～255灰度级，真实世界的动态范围达到107，由于动态范围关注的是亮度信息，则显示设备的亮度范围不足以表现真实世界的亮度域，如果简单的将真实世界的整个亮度域线性压缩到显示设备所能表现的亮度域内，则会在明暗两端丢失较多细节，为了克服这一情况提出了光电转移函数。传统的光电转移函数可以为方案一中的光电转移函数，如图1A所示，第二曲线为通过方案一中的光电转移函数得到的Weber分数，第四曲线为通过本申请的光电转移函数得到的Weber分数。由此可见，第二曲线在亮度值为0.1nits以下的Weber分数超过了Schreiber Threshold，则输出的HDR图像会产生人眼能察觉的条带噪声，不能满足质量上的要求。而第四曲线在满足Schreiber Threshold的同时，亮度值可以达到10000nits，因此本申请提供的高动态范围图像的处理方法可提高量化质量。
其中，亮度信息的单位为nits。图像的亮度信息可以包括各个通道的亮度信息，例如当该图像为RGB图象时，该亮度信息可以包括R、G、B通道的亮度信息；当该图像为Lab模式的图象时，该亮度信息可以包括L、a、b通道的亮度信息。该亮度信息可以包括归一化处理的亮度，例如将真实世界的亮度除以104，得到归一化处理后的亮度，归一化处理后的亮度位于0～1的范围内。
其中，a、b、m以及p为有理数。可选的，a与b之间的关系可以为：a+b＝1，例如，a＝1.12672，b＝-0.12672，m＝0.14，p＝2.2。又如，a＝1.19996，b＝-0.19996，m＝0.11，p＝1.1。又如，a＝1.17053，b＝-0.17053，m＝0.12，p＝1.4。又如，a＝1.14698，b＝-0.14698，m＝0.13，p＝1.8。又如，a＝1.11007，b＝-0.11007，m＝0.15，p＝2.7。又如，a＝1.13014，b＝-0.13014，m＝0.14，p＝2.6。进一步的，终端设备可以将亮度信息经过如下处理，得到处理后的图像信息：
Figure PCTCN2015098502-appb-000003
其 中，a、b以及m为有理数，L为图像的亮度信息，L′为处理后的图像信息。
可选的，a与b之间的关系也可以为：a+b≠1，例如a＝1.11204，b＝-0.122042，m＝0.15，p＝3。又如a＝1.09615，b＝-0.1161462，m＝0.16，p＝3.3。又如a＝1.12762，b＝-0.127622，m＝0.14，p＝2.3。又如a＝1.11204，b＝-0.112042，m＝0.15，p＝3。又如a＝1.09615，b＝-0.0961462，m＝0.16，p＝3.3。需要说明的是，a、b、m以及p为预先设定的有理数，可以是研发人员确定的经验值，也可以是在实验过程中通过Weber分数推导出的数值，具体不受本发明实施例的限制。
在一个可能的设计中，终端设备可以将本申请提供的高动态范围图像的处理方法与传统的HDR视频流编码框架结合，在提高量化质量的同时，提升资源利用率。传统的HDR视频流编码框架可以包括光电转移模块、空间转换模块、量化模块以及编码模块。光电转移模块用于通过光电转移函数将图像的亮度信息进行光电转移，得到光电转移后的电信号。空间转移模块，用于将光电转移后的电信号转移到YCBCR空间，得到空间转移后的图像信息。量化模块，用于在YCBCR空间对空间转移后的图像信息进行量化，通过量化操作转换为8/10bit数据。编码模块，用于对量化后的图像信息进行编码，得到编码后的图像信息。则终端设备通过本申请的
Figure PCTCN2015098502-appb-000004
对图像的亮度信息进行光电转移，得到光电转移后的电信号之后，可以通过预设的空间转移函数将光电转移后的电信号转移到YCBCR空间，得到空间转移后的图像信息，在YCBCR空间对空间转移后的图像信息进行量化，得到量化后的图像信息，对量化后的图像信息进行编码，得到编码后的图像信息。
其中，YCBCR空间为颜色空间，YCBCR空间用于通过压缩亮度信息以有效传输图像。
在一个可能的设计中，终端设备可以将本申请提供的高动态范围图像的处理方法与传统的ISO标准的HDR视频编码框架结合，在提高量化质量 的同时，提升资源利用率。传统的HDR视频编码框架可以包括光电转移模块、量化模块、格式转换模块以及编码模块。光电转移模块用于通过光电转移函数将图像的亮度信息进行光电转移，得到光电转移后的电信号。量化模块，用于对光电转移后的电信号进行量化，通过量化操作转换为10bit定点数。格式转换模块，用于将量化后的图像信息的格式由4:4:4转换为4:2:0。编码模块，用于对格式转换后的图像信息进行编码，得到编码后的图像信息。则终端设备通过本申请的
Figure PCTCN2015098502-appb-000005
对图像的亮度信息进行光电转移，得到光电转移后的电信号之后，可以将光电转移后的电信号进行量化，得到量化后的图像信息，对量化后的图像信息进行格式转换，得到格式转换后的图像信息，对格式转换后的图像信息进行编码，得到编码后的图像信息。
第二方面提供了一种高动态范围图像的处理方法，所述方法包括：
终端设备获取编码后的图像信息。
终端设备对编码后的图像信息进行解码，得到解码后的图像信息。
终端设备对解码后的图像信息进行反量化，得到反量化后的图像信息。
终端设备对反量化后的图像信息经过如下处理，得到处理后的图像信息。
Figure PCTCN2015098502-appb-000006
其中，a、b、m以及p为有理数，L′为反量化后的图像信息，L为处理后的图像信息。
在该技术方案中，第二方面的高动态范围图像的处理方法为第一方面的高动态范围图像的处理方法的逆过程。
其中，a、b、m以及p为有理数。可选的，a与b之间的关系可以为：a+b＝1，例如，a＝1.12672，b＝-0.12672，m＝0.14，p＝2.2。又如，a＝1.19996，b＝-0.19996，m＝0.11，p＝1.1。又如，a＝1.17053，b＝-0.17053，m＝0.12，p＝1.4。又如，a＝1.14698， b＝-0.14698，m＝0.13，p＝1.8。又如，a＝1.11007，b＝-0.11007，m＝0.15，p＝2.7。又如，a＝1.13014，b＝-0.13014，m＝0.14，p＝2.6。进一步的，终端设备可以对反量化后的图像信息经过如下处理，得到处理后的图像信息：
Figure PCTCN2015098502-appb-000007
其中，a、b以及m为有理数，L′为反量化后的图像信息，L为处理后的图像信息。
可选的，a与b之间的关系也可以为：a+b≠1，例如a＝1.11204，b＝-0.122042，m＝0.15，p＝3。又如a＝1.09615，b＝-0.1161462，m＝0.16，p＝3.3。又如a＝1.12762，b＝-0.127622，m＝0.14，p＝2.3。又如a＝1.11204，b＝-0.112042，m＝0.15，p＝3。又如a＝1.09615，b＝-0.0961462，m＝0.16，p＝3.3。需要说明的是，a、b、m以及p为预先设定的有理数，可以是研发人员确定的经验值，也可以是在实验过程中通过Weber分数推导出的数值，具体不受本发明实施例的限制。
在一个可能的设计中，终端设备可以将本申请提供的高动态范围图像的处理方法与传统的HDR视频流解码框架结合，在提高量化质量的同时，提升资源利用率。传统的HDR视频流解码框架可以包括解码模块、反量化模块、空间转换模块以及电光转移模块。解码模块，用于对编码后的图像信息进行解码。反量化模块，用于将解码后的图像信息进行反量化，得到[0，1]的浮点数据。空间转移模块，用于将反量化后的图像信息由YCBCR空间转移到RGB空间或者Lab空间，得到电信号。电光转移模块，用于对上述电信号进行电光转移，得到电光转移后的16位半浮点数或者32位浮点数的亮度信息。则终端设备可以获取编码后的图像信息，对编码后的图像信息进行解码，得到解码后的图像信息，对解码后的图像信息进行反量化，得到反量化后的图像信息，通过预设的空间转移函数将反量化后的图像信息由YCBCR空间转移到RGB空间或者Lab空间，得到电信号，通过本申请的
Figure PCTCN2015098502-appb-000008
对该电信号进行电光转移，得到亮度信息。
在一个可能的设计中，终端设备可以将本申请提供的高动态范围图像的处理方法与传统的ISO标准的HDR视频解码框架结合，在提高量化质量的同时，提升资源利用率。传统的HDR视频解码框架可以包括解码模块、格式转换模块、反量化模块以及电光转移模块。解码模块，用于对编码后的图像信息进行解码。格式转换模块，用于将解码后的图像信息的格式由4:2:0转换为4:4:4。反量化模块，用于对格式转换后的图像信息进行反量化，得到电信号。电光转移模块，用于对上述电信号进行电光转移，得到电光转移后的亮度信息。则终端设备可以获取编码后的图像信息，对编码后的图像信息进行解码，得到解码后的图像信息，对解码后的图像信息进行格式转换，得到格式转换后的图像信息，将格式转换后的图像信息进行反量化，得到电信号，通过本申请的
Figure PCTCN2015098502-appb-000009
对该电信号进行电光转移，得到亮度信息。
第三方面提供了一种计算机存储介质，其中，所述计算机存储介质可存储有程序，该程序执行时包括第一方面的部分或全部步骤。
第四方面提供了一种计算机存储介质，其中，所述计算机存储介质可存储有程序，该程序执行时包括第二方面的部分或全部步骤。
第五方面提供一种高动态范围图像的处理装置，所述装置包括的模块可以用于实施结合第一方面的部分或全部步骤。
第六方面提供一种高动态范围图像的处理装置，所述装置包括的模块可以用于实施结合第二方面的部分或全部步骤。
第七方面提供了一种终端设备，该终端设备包括处理器以及存储器，其中存储器用于存储指令，处理器用于执行指令，当处理器在执行指令时，可以用于实施结合第一方面的部分或全部步骤。
第八方面提供了一种终端设备，该终端设备包括处理器以及存储器，其中存储器用于存储指令，处理器用于执行指令，当处理器在执行指令时，可以用于实施结合第二方面的部分或全部步骤。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1A是本发明实施例中提供的一种Weber分数的界面示意图；
图1B是本发明实施例中提供的一种有理量化函数的量化曲线的界面示意图；
图1C是本发明实施例中提供的一种亮度统计曲线的界面示意图；
图2是本发明实施例中提供的一种高动态范围图像的处理方法的流程示意图；
图3是本发明另一实施例中提供的一种高动态范围图像的处理方法的流程示意图；
图4是本发明实施例中提供的一种终端设备的结构示意图；
图5是本发明实施例中提供的一种高动态范围图像的处理装置的结构示意图；
图6是本发明另一实施例中提供的一种高动态范围图像的处理装置的结 构示意图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚地描述。
请参见图2，图2是本发明实施例中提供的一种高动态范围图像的处理方法的流程示意图，如图所示本发明实施例中的高动态范围图像的处理方法至少可以包括：
S201，第一终端设备通过预设的光电转移函数对图像的亮度信息进行光电转移，得到光电转移后的电信号。
第一终端设备可以通过预设的光电转移函数对图像的亮度信息进行光电转移，得到光电转移后的电信号。其中，第一终端设备可以为卫星、个人计算机(personal computer，PC)或者智能手机等。
具体实现中，量化曲线是模拟人眼对于不同亮度的感知细节的变化。通过对测试序列统计，得到真实世界的亮度分布曲线与人眼对亮度感知曲线有较大的差别。例如，对现有的CT2020HDR高清序列进行了动态范围统计，按照亮度区间分成6个区间进行统计，统计结果如表一所示：
表一
Figure PCTCN2015098502-appb-000010
由表一可见，HDR序列虽然动态范围较高，但是主要的亮度分布在0～2000nits。其中，分布在0～1000nits的亮度占比80％-99％，分布在0～2000nits的亮度占比97％-99％。因此，考虑到人眼对亮度的敏感特性，从人眼视觉特性出发，将亮度为0～10000nits的范围作为量化曲线重点保护的亮度段。
传统的有理量化函数为：
Figure PCTCN2015098502-appb-000011
其中p为预设参数，L为真实世界的亮度信息，F(L)为量化值。以图1B所示的有理量化函数的量化曲线为例，曲线形式较为简单，而且有较好的自适应特性，可满足人眼的亮度感知特性，但有理量化曲线的Weber分数效果较差，低于Schreiber Threshold的动态范围很窄，不能完全分布在Schreiber Threshold之下。
另外，ITU-R Recommendation BT.1886标准当中定义了伽马(Gamma)函数，Gamma函数为早期的光电转移函数，Gamma函数如下所示：
L＝a(max[(V+b),0])r
其中，L为光电转移后的电信号，
Figure PCTCN2015098502-appb-000012
V为真实世界的亮度信息，
Figure PCTCN2015098502-appb-000013
r＝2.4。
通过Gamma函数在亮度为100nits的显示设备上显示的图像的质量较好。但随着显示设备的升级，当显示设备的亮度为600nits或者2000nits时，通过Gamma函数输出的图像无法在该显示设备上正常显示。
因此，本发明实施例结合有理量化函数和Gamma函数，提出本申请中的光电转移函数，通过该光电转移函数计算得到的Weber分数符合场景亮度统计的分布特点，使得量化曲线更符合人眼感知的特点，也就是说，有效地扩大符合Weber分数约束的动态范围。
以图1C所示的亮度统计曲线为例，第一曲线为方案一的亮度统计曲线，第二曲线为本申请的亮度统计曲线，第二曲线相对第一曲线在0～1000nits的范围内上升更快，也就表示在低亮度部分有更优秀的条带噪声抑制能力。
传统的方案二中的光电转移函数在低端应用传统的Gamma函数，在高端应用log曲线，提出了Hybrid Log-Gamma转移函数，Hybrid Log-Gamma函数 可以如下所示：
Figure PCTCN2015098502-appb-000014
其中，E′为光电转移后的电信号，E为真实世界的亮度信息，a、b、c以及r为预设参数。方案二的动态范围范围只有0-2000nits，超过2000nits的部分会被截取到2000nits。
以图1A所示的Weber分数为例，第一曲线为ITU Report BT.2246标准文件中的Schreiber Threshold，第二曲线为通过方案一中的光电转移函数得到的Weber分数，第三曲线为通过方案二中的光电转移函数得到的Weber分数，第四曲线为通过本申请的光电转移函数得到的Weber分数。第二曲线在0.1nits以下不满足Schreiber Threshold，第三曲线的曲线量化范围较小，为0.01nits～2000nits，第四曲线量化范围可以达到10000nits，更符合人眼感知的特点。
S202，第一终端设备通过预设的第一空间转移函数将光电转移后的电信号由RGB空间或者Lab空间转移到YCBCR空间，得到图像信息。
S203，第一终端设备在YCBCR空间对图像信息进行量化，得到量化后的图像信息。
S204，第一终端设备对量化后的图像信息进行编码，得到编码后的图像信息。
S205，第一终端设备将编码后的图像信息发送给第二终端设备。
S206，第二终端设备对编码后的图像信息进行解码，得到解码后的图像信息。
第二终端设备接收到第一终端设备发送的编码后的图像信息之后，可以对编码后的图像信息进行解码，得到解码后的图像信息。其中，第二终端设备可以为数字电视接收终端、PC或者智能手机等。
S207，第二终端设备对解码后的图像信息进行反量化，得到反量化后的图 像信息。
S208，第二终端设备通过预设的第二空间转移函数将反量化后的图像信息由YCBCR空间转移到RGB空间或者Lab空间，得到电信号。
S209，第二终端设备通过预设的电光转移函数对当前需要进行电光转移的电信号进行电光转移，得到亮度信息。
S210，第二终端设备输出亮度信息。
当视频流编解码的框架为SMPTE 2084TF时，将原有的光电转移模块更新为本申请的光电转移函数，将原有的电光转移模块更新为本申请的电光转移函数，通过分析可知，本申请的高动态范围图像的处理方法相对原有的视频流编解码方法对峰值信噪比(Peak Signal to Noise Ratio，PSNR)节省了18.8％的码率，对掩膜峰值信噪比(Masked Peak Signal to Noise Ratio，MPSNR)节省了20.3％的码率，对Delta-E(ΔE，人眼感觉色差的测试单位)节省了9％的码率。
在图2所示的高动态范围图像的处理方法中，第一终端设备通过预设的光电转移函数对图像的亮度信息进行光电转移，得到光电转移后的电信号，通过预设的第一空间转移函数将光电转移后的电信号由RGB空间或者Lab空间转移到YCBCR空间，得到图像信息，在YCBCR空间对图像信息进行量化，得到量化后的图像信息，对量化后的图像信息进行编码，并将编码后的图像信息发送给第二终端设备，第二终端设备对编码后的图像信息进行解码，得到解码后的图像信息，对解码后的图像信息进行反量化，得到反量化后的图像信息，通过预设的第二空间转移函数将反量化后的图像信息由YCBCR空间转移到RGB空间或者Lab空间，得到电信号，通过预设的电光转移函数对当前需要进行电光转移的电信号进行电光转移，得到亮度度信息，并输出亮度信息，可提高量化质量，并提升资源利用率。
请参见图3，图3是本发明另一实施例中提供的一种高动态范围图像的处理方法的流程示意图，如图所示本发明实施例中的高动态范围图像的处理方法至少可以包括：
S301，终端设备通过预设的光电转移函数对图像的亮度信息进行光电转移， 得到光电转移后的电信号。
终端设备可以通过预设的光电转移函数对图像的亮度信息进行光电转移，得到光电转移后的电信号。其中，终端设备可以为智能手机、相机或者平板电脑等。该图像可以是通过摄像头采集到的或者是本地预先存储的。
S302，终端设备将光电转移后的电信号进行量化，得到量化后的图像信息。
S303，终端设备对量化后的图像信息进行格式转换，得到格式转换后的图像信息。
S304，终端设备对格式转换后的图像信息进行编码，得到编码后的图像信息。
S305，终端设备对编码后的图像信息进行解码，得到解码后的图像信息。
S306，终端设备对解码后的图像信息进行格式转换，得到格式转换后的图像信息。
S307，终端设备对格式转换后的图像信息进行反量化，得到电信号。
S308，终端设备通过预设的电光转移函数对当前需要进行电光转移的电信号进行电光转移，得到亮度信息。
S309，终端设备输出亮度信息。
在图3所示的高动态范围图像的处理方法中，终端设备通过预设的光电转移函数对图像的亮度信息进行光电转移，得到光电转移后的电信号，将光电转移后的电信号进行量化，得到量化后的图像信息，对量化后的图像信息进行格式转换，得到格式转换后的图像信息，对格式转换后的图像信息进行编码，对编码后的图像信息进行解码，得到解码后的图像信息，对解码后的图像信息进行格式转换，得到格式转换后的图像信息，对格式转换后的图像信息进行反量化，得到电信号，通过预设的电光转移函数对当前需要进行电光转移的电信号进行电光转移，得到亮度信息，进而输出亮度信息，可提高量化质量，并提升资源利用率。
请参见图4，图4是本发明实施例中提供的一种终端设备的结构示意图。如图4所示，该终端设备可以包括：处理器401、存储器402、输入装置403、以及输出装置404。处理器401连接到存储器402、输入装置403以及输出装 置404，例如处理器401可以通过总线连接到存储器402、输入装置403以及输出装置404。
其中，处理器401可以是中央处理器(central processing unit，CPU)，网络处理器(network processor，NP)等。
存储器402具体可以用于图像的亮度信息等。存储器402可以包括易失性存储器(volatile memory)，例如随机存取存储器(random-access memory，RAM)；存储器也可以包括非易失性存储器(non-volatile memory)，例如只读存储器(read-only memory，ROM)，快闪存储器(flash memory)，硬盘(hard disk drive，HDD)或固态硬盘(solid-state drive，SSD)；存储器还可以包括上述种类的存储器的组合。
输出装置404，用于输出亮度信息，例如无线接口或者有线接口等。
其中，处理器401调用存储器402中存储的程序，可以执行以下操作：
处理器401，用于获取图像的亮度信息。
处理器401，还用于将亮度信息经过如下处理，得到处理后的图像信息。
Figure PCTCN2015098502-appb-000015
其中，a、b、m以及p为有理数，L为图像的亮度信息，L′为处理后的图像信息。
处理器401，还用于对处理后的图像信息进行量化，得到量化后的图像信息。
处理器401，还用于对量化后的图像信息进行编码，得到编码后的图像信息。
具体的，本发明实施例中介绍的终端设备可以用以实施本发明结合图2或者图3介绍的高动态范围图像的处理方法实施例中的部分或全部流程。
请参见图4，图4是本发明实施例中提供的一种终端设备的结构示意图。如图4所示，该终端设备可以包括：处理器401、存储器402、输入装置403、以及输出装置404。处理器401连接到存储器402、输入装置403以及输出装置404，例如处理器401可以通过总线连接到存储器402、输入装置403以及 输出装置404。
其中，处理器401可以是中央处理器，网络处理器等。
存储器402具体可以用于存储图像的亮度信息等。存储器402可以包括易失性存储器，例如随机存取存储器；存储器也可以包括非易失性存储器，例如只读存储器，快闪存储器，硬盘或固态硬盘；存储器还可以包括上述种类的存储器的组合。
输入装置403，用于获取编码后的图像信息，例如无线接口或者有线接口等。
输出装置404，用于输出亮度信息，例如显示屏幕。
其中，处理器401调用存储器402中存储的程序，可以执行以下操作：
处理器401，用于获取编码后的图像信息。
处理器401，还用于对编码后的图像信息进行解码，得到解码后的图像信息。
处理器401，还用于对解码后的图像信息进行反量化，得到反量化后的图像信息。
处理器401，还用于对反量化后的图像信息经过如下处理，得到处理后的图像信息：
Figure PCTCN2015098502-appb-000016
其中，a、b、m以及p为有理数，L′为反量化后的图像信息，L为处理后的图像信息。
具体的，本发明实施例中介绍的终端设备可以用以实施本发明结合图2或者图3介绍的高动态范围图像的处理方法实施例中的部分或全部流程。
请参见图5，图5是本发明实施例中提供的一种高动态范围图像的处理装置的结构示意图，其中本发明实施例提供的高动态范围图像的处理装置可以用以实施本发明结合图2或者图3介绍的高动态范围图像的处理方法实施例中的部分或全部流程。如图所示本发明实施例中的高动态范围图像的处理装置至少可以包括亮度信息获取模块501、亮度信息处理模块502、量化模块503以及 编码模块504，其中：
亮度信息获取模块501，用于获取图像的亮度信息。
亮度信息处理模块502，用于将亮度信息经过如下处理，得到处理后的图像信息：
Figure PCTCN2015098502-appb-000017
其中，a、b、m以及p为有理数，L为图像的亮度信息，L′为处理后的图像信息。
量化模块503，用于对处理后的图像信息进行量化，得到量化后的图像信息。
编码模块504，用于对量化后的图像信息进行编码，得到编码后的图像信息。
图5所示的高动态范围图像的处理装置中，亮度信息获取模块501获取图像的亮度信息，亮度信息处理模块502将亮度信息经过处理，得到处理后的图像信息，量化模块503对处理后的图像信息进行量化，得到量化后的图像信息，编码模块504对量化后的图像信息进行编码，得到编码后的图像信息，可提高量化质量。
请参见图6，图6是本发明另一实施例中提供的一种高动态范围图像的处理装置的结构示意图，其中本发明实施例提供的高动态范围图像的处理装置可以用以实施本发明结合图2或者图3介绍的高动态范围图像的处理方法实施例中的部分或全部流程。如图所示本发明实施例中的高动态范围图像的处理装置至少可以包括图像信息获取模块601、解码模块602、反量化模块603以及图像信息处理模块604，其中：
图像信息获取模块601，用于获取编码后的图像信息。
解码模块602，用于对所述编码后的图像信息进行解码，得到解码后的图像信息。
反量化模块603，用于对所述解码后的图像信息进行反量化，得到反量化后的图像信息。
图像信息处理模块604，用于对所述反量化后的图像信息经过如下处理， 得到处理后的图像信息：
Figure PCTCN2015098502-appb-000018
其中，a、b、m以及p为有理数，L′为反量化后的图像信息，L为处理后的图像信息。
图6所示的高动态范围图像的处理装置中，图像信息获取模块601获取编码后的图像信息，解码模块602对编码后的图像信息进行解码，得到解码后的图像信息，反量化模块603对解码后的图像信息进行反量化，得到反量化后的图像信息，图像信息处理模块604对反量化后的图像信息经过如下处理，得到处理后的图像信息，可提高量化质量。
本发明实施例中，对于
Figure PCTCN2015098502-appb-000019
a、b、m以及p为有理数。例如，a＝1.2441，b＝-0.2441，m＝0.1，p＝1.1。又如，a＝1.20228，b＝-0.20228，m＝0.11，p＝1.2。又如，a＝1.17529，b＝-0.17529，m＝0.12，p＝1.7。又如，a＝1.14933，b＝-0.14933，m＝0.13，p＝2。又如，a＝1.12762，b＝-0.12762，m＝0.14，p＝2.3。又如，a＝1.11204，b＝-0.11204，m＝0.15，p＝3。又如，a＝1.09615，b＝-0.09615，m＝0.16，p＝3.3。
对于
Figure PCTCN2015098502-appb-000020
a、b、m以及p为有理数。例如，a＝1.2441，b＝-0.2441，m＝0.1，p＝1.1。又如，a＝1.20228，b＝-0.20228，m＝0.11，p＝1.2。又如，a＝1.17529，b＝-0.17529，m＝0.12，p＝1.7。又如，a＝1.14933，b＝-0.14933，m＝0.13，p＝2。又如，a＝1.12762，b＝-0.12762，m＝0.14，p＝2.3。又如，a＝1.11204，b＝-0.11204，m＝0.15，p＝3。又如，a＝1.09615，b＝-0.09615，m＝0.16，p＝3.3。
在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包括于本发明的至少一个实施例或示例中。在本说明书中， 对上述术语的示意性表述不是必须针对相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外，在不相互矛盾的情况下，本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。
此外，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。在本发明的描述中，“多个”的含义是至少两个，例如两个，三个等，除非另有明确具体的限定。
在流程图中表示或在此以其他方式描述的逻辑和/或步骤，例如，可以被认为是用于实现逻辑功能的可执行指令的程序列表，可以具体实现在任何计算机可读介质中，以供指令执行系统、装置或设备(如基于计算机的系统、包括处理器的系统或其他可以从指令执行系统、装置或设备取指令并执行指令的系统)使用，或结合这些指令执行系统、装置或设备而使用。就本说明书而言，"计算机可读介质"可以是任何可以包括、存储、通信、传播或传输程序以供指令执行系统、装置或设备或结合这些指令执行系统、装置或设备而使用的装置。计算机可读介质的更具体的示例(非穷尽性列表)包括以下：具有一个或多个布线的电连接部(电子装置)，便携式计算机盘盒(磁装置)，随机存取存储器，只读存储器，可擦除可编辑只读存储器，光纤装置，以及便携式光盘只读存储器。另外，计算机可读介质甚至可以是可在其上打印所述程序的纸或其他合适的介质，因为可以例如通过对纸或其他介质进行光学扫描，接着进行编辑、解译或必要时以其他合适方式进行处理来以电子方式获得所述程序，然后将其存储在计算机存储器中。
应当理解，本发明的各部分可以用硬件、软件、固件或它们的组合来实现。在上述实施方式中，多个步骤或方法可以用存储在存储器中且由合适的指令执行系统执行的软件或固件来实现。例如，如果用硬件来实现，和在另一实施方式中一样，可用本领域公知的下列技术中的任一项或他们的组合来实现：具有用于对数据信号实现逻辑功能的逻辑门电路的离散逻辑电路，具有合适的组合逻辑门电路的专用集成电路，可编程门阵列，现场可编程门阵列等。
此外，在本发明各个实施例中的模块既可以采用硬件的形式实现，也可以 采用软件功能模块的形式实现。集成的模块如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。
尽管上面已经示出和描述了本发明的实施例，可以理解的是，上述实施例是示例性的，不能理解为对本发明的限制，本领域的普通技术人员在本发明的范围内可以对上述实施例进行变化、修改、替换和变型。

Claims (16)

  1. 一种高动态范围图像的处理方法，其特征在于，所述方法包括：
    获取图像的亮度信息；
    将所述亮度信息经过如下处理，得到处理后的图像信息：
    Figure PCTCN2015098502-appb-100001
    其中，a、b、m以及p为有理数，L为图像的亮度信息，L′为处理后的图像信息；
    对所述处理后的图像信息进行量化，得到量化后的图像信息；
    对所述量化后的图像信息进行编码，得到编码后的图像信息。
  2. 如权利要求1所述的方法，其特征在于，所述a、b、m以及p为有理数，包括：
    a＝1.12672，b＝-0.12672，m＝0.14，p＝2.2；或者
    a＝1.19996，b＝-0.19996，m＝0.11，p＝1.1；或者
    a＝1.17053，b＝-0.17053，m＝0.12，p＝1.4；或者
    a＝1.14698，b＝-0.14698，m＝0.13，p＝1.8；或者
    a＝1.11007，b＝-0.11007，m＝0.15，p＝2.7；或者
    a＝1.12762，b＝-0.127622，m＝0.14，p＝2.3；或者
    a＝1.13014，b＝-0.13014，m＝0.14，p＝2.6；或者
    a＝1.11204，b＝-0.112042，m＝0.15，p＝3；或者
    a＝1.09615，b＝-0.0961462，m＝0.16，p＝3.3。
  3. 如权利要求1所述的方法，其特征在于，所述a、b、m以及p为有理数，包括：
    a＝1.2441，b＝-0.2441，m＝0.1，p＝1.1；或者
    a＝1.20228，b＝-0.20228，m＝0.11，p＝1.2；或者
    a＝1.17529，b＝-0.17529，m＝0.12，p＝1.7；或者
    a＝1.14933，b＝-0.14933，m＝0.13，p＝2；或者
    a＝1.12762，b＝-0.12762，m＝0.14，p＝2.3；或者
    a＝1.11204，b＝-0.11204，m＝0.15，p＝3；或者
    a＝1.09615，b＝-0.09615，m＝0.16，p＝3.3。
  4. 一种高动态范围图像的处理方法，其特征在于，所述方法包括：
    获取编码后的图像信息；
    对所述编码后的图像信息进行解码，得到解码后的图像信息；
    对所述解码后的图像信息进行反量化，得到反量化后的图像信息；
    对所述反量化后的图像信息经过如下处理，得到处理后的图像信息：
    Figure PCTCN2015098502-appb-100002
    其中，a、b、m以及p为有理数，L′为反量化后的图像信息，L为处理后的图像信息。
  5. 如权利要求4所述的方法，其特征在于，所述a、b、m以及p为有理数，包括：
    a＝1.12672，b＝-0.12672，m＝0.14，p＝2.2；或者
    a＝1.19996，b＝-0.19996，m＝0.11，p＝1.1；或者
    a＝1.17053，b＝-0.17053，m＝0.12，p＝1.4；或者
    a＝1.14698，b＝-0.14698，m＝0.13，p＝1.8；或者
    a＝1.11007，b＝-0.11007，m＝0.15，p＝2.7；或者
    a＝1.12762，b＝-0.127622，m＝0.14，p＝2.3；或者
    a＝1.13014，b＝-0.13014，m＝0.14，p＝2.6；或者
    a＝1.11204，b＝-0.112042，m＝0.15，p＝3；或者
    a＝1.09615，b＝-0.0961462，m＝0.16，p＝3.3。
  6. 如权利要求4所述的方法，其特征在于，所述a、b、m以及p为有理数，包括：
    a＝1.2441，b＝-0.2441，m＝0.1，p＝1.1；或者
    a＝1.20228，b＝-0.20228，m＝0.11，p＝1.2；或者
    a＝1.17529，b＝-0.17529，m＝0.12，p＝1.7；或者
    a＝1.14933，b＝-0.14933，m＝0.13，p＝2；或者
    a＝1.12762，b＝-0.12762，m＝0.14，p＝2.3；或者
    a＝1.11204，b＝-0.11204，m＝0.15，p＝3；或者
    a＝1.09615，b＝-0.09615，m＝0.16，p＝3.3。
  7. 一种高动态范围图像的处理装置，其特征在于，所述装置包括：
    亮度信息获取模块，用于获取图像的亮度信息；
    亮度信息处理模块，用于将所述亮度信息经过如下处理，得到处理后的图像信息：
    Figure PCTCN2015098502-appb-100003
    其中，a、b、m以及p为有理数，L为图像的亮度信息，L′为处理后的图像信息；
    量化模块，用于对所述处理后的图像信息进行量化，得到量化后的图像信息；
    编码模块，用于对所述量化后的图像信息进行编码，得到编码后的图像信息。
  8. 一种高动态范围图像的处理装置，其特征在于，所述装置包括：
    图像信息获取模块，用于获取编码后的图像信息；
    解码模块，用于对所述编码后的图像信息进行解码，得到解码后的图像信息；
    反量化模块，用于对所述解码后的图像信息进行反量化，得到反量化后的图像信息；
    图像信息处理模块，用于对所述反量化后的图像信息经过如下处理，得到处理后的图像信息：
    Figure PCTCN2015098502-appb-100004
    其中，a、b、m以及p为有理数，L′为反量化后的图像信息，L为处理后的图像信息。
  9. 一种高动态范围图像的处理方法，其特征在于，所述方法包括：
    获取图像的亮度信息，所述图像的亮度信息为记录光信号的数值，所述图像的亮度信息与光强度成正比；
    将所述图像的亮度信息经过转换处理得到处理后的图像信息，所述图像信息为图像信号的数字表达值，所述转换处理包括如下处理：
    Figure PCTCN2015098502-appb-100005
    其中，a、b、m以及p为有理数，L为图像的亮度信息，L′为处理后的图像信息。
  10. 如权利要求9所述的方法，其特征在于，所述a、b、m以及p为有理数，包括：
    a＝1.12672，b＝-0.12672，m＝0.14，p＝2.2；或者
    a＝1.19996，b＝-0.19996，m＝0.11，p＝1.1；或者
    a＝1.17053，b＝-0.17053，m＝0.12，p＝1.4；或者
    a＝1.14698，b＝-0.14698，m＝0.13，p＝1.8；或者
    a＝1.11007，b＝-0.11007，m＝0.15，p＝2.7；或者
    a＝1.12762，b＝-0.127622，m＝0.14，p＝2.3；或者
    a＝1.13014，b＝-0.13014，m＝0.14，p＝2.6；或者
    a＝1.11204，b＝-0.112042，m＝0.15，p＝3；或者
    a＝1.09615，b＝-0.0961462，m＝0.16，p＝3.3。
  11. 如权利要求9所述的方法，其特征在于，所述a、b、m以及p为有理数，包括：
    a＝1.2441，b＝-0.2441，m＝0.1，p＝1.1；或者
    a＝1.20228，b＝-0.20228，m＝0.11，p＝1.2；或者
    a＝1.17529，b＝-0.17529，m＝0.12，p＝1.7；或者
    a＝1.14933，b＝-0.14933，m＝0.13，p＝2；或者
    a＝1.12762，b＝-0.12762，m＝0.14，p＝2.3；或者
    a＝1.11204，b＝-0.11204，m＝0.15，p＝3；或者
    a＝1.09615，b＝-0.09615，m＝0.16，p＝3.3。
  12. 一种高动态范围图像的处理方法，其特征在于，所述方法包括：
    获取输入的图像信息，所述图像信息为图像信号的数字表达值；
    对所述图像信息进行转换处理，得到图像的亮度信息。所述图像的亮度信息为用于显示设备显示所述图像的参考光信号的数值，所述图像的亮度信息与光强度成正比；
    所述转换处理包括：
    Figure PCTCN2015098502-appb-100006
    其中，a、b、m以及p为有理数，L′为输入的图像信息，L为处理后的图像的亮度信息。
  13. 如权利要求12所述的方法，其特征在于，所述a、b、m以及p为有理数，包括：
    a＝1.12672，b＝-0.12672，m＝0.14，p＝2.2；或者
    a＝1.19996，b＝-0.19996，m＝0.11，p＝1.1；或者
    a＝1.17053，b＝-0.17053，m＝0.12，p＝1.4；或者
    a＝1.14698，b＝-0.14698，m＝0.13，p＝1.8；或者
    a＝1.11007，b＝-0.11007，m＝0.15，p＝2.7；或者
    a＝1.12762，b＝-0.127622，m＝0.14，p＝2.3；或者
    a＝1.13014，b＝-0.13014，m＝0.14，p＝2.6；或者
    a＝1.11204，b＝-0.112042，m＝0.15，p＝3；或者
    a＝1.09615，b＝-0.0961462，m＝0.16，p＝3.3。
  14. 如权利要求12所述的方法，其特征在于，所述a、b、m以及p为有理数，包括：
    a＝1.2441，b＝-0.2441，m＝0.1，p＝1.1；或者
    a＝1.20228，b＝-0.20228，m＝0.11，p＝1.2；或者
    a＝1.17529，b＝-0.17529，m＝0.12，p＝1.7；或者
    a＝1.14933，b＝-0.14933，m＝0.13，p＝2；或者
    a＝1.12762，b＝-0.12762，m＝0.14，p＝2.3；或者
    a＝1.11204，b＝-0.11204，m＝0.15，p＝3；或者
    a＝1.09615，b＝-0.09615，m＝0.16，p＝3.3。
  15. 一种高动态范围图像的处理装置，其特征在于，所述装置包括：
    亮度信息获取模块，用于获取图像的亮度信息，所述图像的亮度信息为记录光信号的数值，所述图像的亮度信息与光强度成正比；
    亮度信息处理模块，用于将所述图像的亮度信息经过转换处理得到处理后的图像信息，所述图像信息为图像信号的数字表达值，所述转换处理包括如下 处理：
    Figure PCTCN2015098502-appb-100007
    其中，a、b、m以及p为有理数，L为图像的亮度信息，L′为处理后的图像信息。
  16. 一种高动态范围图像的处理装置，其特征在于，所述装置包括：
    图像信息获取模块，用于获取输入的图像信息，所述图像信息为图像信号的数字表达值；
    图像信息处理模块，用于对所述图像信息进行转换处理，得到图像的亮度信息。所述图像的亮度信息为用于显示设备显示所述图像的参考光信号的数值，所述图像的亮度信息与光强度成正比；
    所述转换处理包括：
    Figure PCTCN2015098502-appb-100008
    其中，a、b、m以及p为有理数，L′为输入的图像信息，L为处理后的图像的亮度信息。
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