WO2018098982A1 - 图像处理方法、图像处理装置、成像装置及电子装置 - Google Patents

图像处理方法、图像处理装置、成像装置及电子装置 Download PDF

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Publication number
WO2018098982A1
WO2018098982A1 PCT/CN2017/081919 CN2017081919W WO2018098982A1 WO 2018098982 A1 WO2018098982 A1 WO 2018098982A1 CN 2017081919 W CN2017081919 W CN 2017081919W WO 2018098982 A1 WO2018098982 A1 WO 2018098982A1
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pixel
image
image processing
unit
color
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PCT/CN2017/081919
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English (en)
French (fr)
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韦怡
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广东欧珀移动通信有限公司
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    • 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
    • H04N23/81—Camera processing pipelines; Components thereof for suppressing or minimising disturbance in the image signal generation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformations in the plane of the image
    • G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
    • G06T3/4015—Image demosaicing, e.g. colour filter arrays [CFA] or Bayer patterns
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformations in the plane of the image
    • G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
    • G06T3/4007—Scaling of whole images or parts thereof, e.g. expanding or contracting based on interpolation, e.g. bilinear interpolation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/73—Deblurring; Sharpening
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • 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
    • H04N23/84—Camera processing pipelines; Components thereof for processing colour signals
    • H04N23/843—Demosaicing, e.g. interpolating colour pixel values
    • 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
    • H04N23/84—Camera processing pipelines; Components thereof for processing colour signals
    • H04N23/88—Camera processing pipelines; Components thereof for processing colour signals for colour balance, e.g. white-balance circuits or colour temperature control
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/10—Circuitry of solid-state image sensors [SSIS]; Control thereof for transforming different wavelengths into image signals
    • H04N25/11—Arrangement of colour filter arrays [CFA]; Filter mosaics
    • H04N25/13—Arrangement of colour filter arrays [CFA]; Filter mosaics characterised by the spectral characteristics of the filter elements
    • H04N25/134—Arrangement of colour filter arrays [CFA]; Filter mosaics characterised by the spectral characteristics of the filter elements based on three different wavelength filter elements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/40—Extracting pixel data from image sensors by controlling scanning circuits, e.g. by modifying the number of pixels sampled or to be sampled
    • H04N25/44—Extracting pixel data from image sensors by controlling scanning circuits, e.g. by modifying the number of pixels sampled or to be sampled by partially reading an SSIS array
    • H04N25/447—Extracting pixel data from image sensors by controlling scanning circuits, e.g. by modifying the number of pixels sampled or to be sampled by partially reading an SSIS array by preserving the colour pattern with or without loss of information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/40—Extracting pixel data from image sensors by controlling scanning circuits, e.g. by modifying the number of pixels sampled or to be sampled
    • H04N25/46—Extracting pixel data from image sensors by controlling scanning circuits, e.g. by modifying the number of pixels sampled or to be sampled by combining or binning pixels
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/60—Noise processing, e.g. detecting, correcting, reducing or removing noise
    • H04N25/68—Noise processing, e.g. detecting, correcting, reducing or removing noise applied to defects
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/60—Noise processing, e.g. detecting, correcting, reducing or removing noise
    • H04N25/68—Noise processing, e.g. detecting, correcting, reducing or removing noise applied to defects
    • H04N25/69—SSIS comprising testing or correcting structures for circuits other than pixel cells
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/70—SSIS architectures; Circuits associated therewith
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
    • H04N25/70—SSIS architectures; Circuits associated therewith
    • H04N25/76—Addressed sensors, e.g. MOS or CMOS sensors
    • H04N25/77—Pixel circuitry, e.g. memories, A/D converters, pixel amplifiers, shared circuits or shared components
    • H04N25/778—Pixel circuitry, e.g. memories, A/D converters, pixel amplifiers, shared circuits or shared components comprising amplifiers shared between a plurality of pixels, i.e. at least one part of the amplifier must be on the sensor array itself
    • 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

Definitions

  • the present invention relates to imaging technology, and more particularly to an image processing method, an image processing device, an imaging device, and an electronic device.
  • An existing image sensor includes a pixel unit array and a filter unit array disposed on the pixel unit array, each filter unit array covering a corresponding one of the photosensitive pixel units, and each of the photosensitive pixel units includes a plurality of photosensitive pixels.
  • the image sensor exposure output merged image may be controlled, and the merged image includes a merged pixel array, and the plurality of photosensitive pixels of the same pixel unit are combined and output as one merged pixel. In this way, the signal-to-noise ratio of the merged image can be improved, however, the resolution of the merged image is lowered.
  • the image sensor may also be controlled to output a high-pixel patch image
  • the patch image includes an original pixel array, and each photosensitive pixel corresponds to one original pixel.
  • the resolution of the patch image cannot be improved. Therefore, it is necessary to convert the high-pixel patch image into a high-pixel pseudo-image by interpolation calculation, and the pseudo-image may include a pseudo-origin pixel arranged in a Bayer array.
  • the original image can be converted into a true color image by image processing and saved. Interpolation calculations can improve the sharpness of true color images, but they are resource intensive and time consuming, resulting in longer shooting times and poor user experience. In addition, not all scenes are applicable or need to output a fake original color image.
  • Embodiments of the present invention provide an image processing method, an image processing apparatus, an imaging apparatus, and an electronic apparatus.
  • An image processing method for converting a patch image into an original image in an image forming apparatus, the image forming apparatus including an image sensor, the image sensor including an array of photosensitive pixel units, and an array of the photosensitive pixel unit An array of filter cells, each of the filter cell arrays covering a corresponding one of the photosensitive pixel units, each of the photosensitive pixel units comprising a plurality of photosensitive pixels, the patch image comprising a predetermined array arrangement An image pixel unit comprising a plurality of original pixels, each of the photosensitive pixels corresponding to one of the original pixels, the image processing method comprising the steps of:
  • the patch image includes the highlight area
  • the step of converting the patch image into the parse image includes the following steps:
  • the pixel value of the associated pixel is used as the pixel value of the current pixel
  • the pixel value of the current pixel is calculated by a second interpolation algorithm, and the complexity of the second interpolation algorithm is smaller than the first interpolation algorithm.
  • An image processing apparatus is for converting a patch image into an original image in an image forming apparatus, the image forming apparatus including an image sensor, the image sensor including an array of photosensitive pixel units, and an array of the photosensitive pixel unit An array of filter cells, each of the filter cell arrays covering a corresponding one of the photosensitive pixel units, each of the photosensitive pixel units comprising a plurality of photosensitive pixels, the patch image comprising a predetermined array arrangement
  • An image pixel unit, the image pixel unit includes a plurality of original pixels, each of the photosensitive pixels corresponding to one of the original pixels, and the image processing apparatus includes a dividing module, a calculating module, a merging module, and a converting module.
  • the dividing module is configured to divide the color patch image into a plurality of brightness analysis regions; the calculating module is configured to calculate a brightness value of each brightness analysis region; and the merging module is configured to match the brightness value to a condition Correspondingly, the brightness regions are merged into a highlight region; the conversion module is configured to convert the color patch image into a pseudo original image, where the pseudo original image includes an array of original pixels, the dummy pixel includes a current pixel, the original pixel includes an associated pixel corresponding to the current pixel, the color block image includes the highlighted area, and the conversion module includes a first determining unit, a second determining unit, a first calculating unit, a second calculation unit and a third calculation unit.
  • the first determining unit is configured to determine whether the associated pixel is located in the highlighted area, and the second determining unit is configured to determine a color of the current pixel when the associated pixel is located in the highlighted area Whether the color of the associated pixel is the same; the first calculating unit is configured to use the pixel value of the associated pixel as the pixel of the current pixel when the color of the current pixel is the same as the color of the associated pixel a value; the second calculating unit is configured to: according to the associated pixel, when the color of the current pixel is different from the color of the associated pixel a pixel value of the unit is calculated by a first interpolation algorithm, the image pixel unit including the associated pixel unit, the associated pixel unit having the same color as the current pixel and being associated with the current pixel The third calculating unit is configured to calculate a pixel value of the current pixel by using a second interpolation algorithm when the associated pixel is located outside the highlight area, where the complexity of the second interpolation algorithm is less than The
  • An image forming apparatus includes the above image processing apparatus.
  • An electronic device includes the above-described imaging device and touch panel.
  • An electronic device includes a housing, a processor, a memory, a circuit board, and a power supply circuit.
  • the circuit board is disposed inside a space enclosed by the casing, the processor and the memory are disposed on the circuit board; and the power circuit is configured to supply power to each circuit or device of the electronic device;
  • the memory is configured to store executable program code; the processor runs a program corresponding to the executable program code by reading executable program code stored in the memory for executing the image processing method described above .
  • the image processing method, the graphics processing device, the imaging device, and the electronic device perform image processing of the first interpolation algorithm only on the region where the luminance of the patch image is high according to the determination of the brightness of the image, thereby obtaining a high-quality image.
  • the problem that the processing time caused by the image processing of the entire frame image by the first interpolation algorithm is long is avoided, and the processing efficiency is improved.
  • FIG. 1 is a schematic flow chart of an image processing method according to an embodiment of the present invention.
  • FIG. 2 is another schematic flowchart of an image processing method according to an embodiment of the present invention.
  • FIG. 3 is a schematic diagram of functional blocks of an image processing apparatus according to an embodiment of the present invention.
  • FIG. 4 is a schematic block diagram of an image sensor according to an embodiment of the present invention.
  • FIG. 5 is a circuit diagram of an image sensor according to an embodiment of the present invention.
  • FIG. 6 is a schematic view of a filter unit according to an embodiment of the present invention.
  • FIG. 7 is a schematic structural diagram of an image sensor according to an embodiment of the present invention.
  • FIG. 8 is a schematic diagram of a merged image state according to an embodiment of the present invention.
  • FIG. 9 is a schematic diagram showing a state of a patch image according to an embodiment of the present invention.
  • FIG. 10 is a schematic diagram showing a state of an image processing method according to an embodiment of the present invention.
  • FIG. 11 is a schematic flow chart of an image processing method according to some embodiments of the present invention.
  • FIG. 12 is a schematic diagram of functional modules of a second computing unit according to some embodiments of the present invention.
  • FIG. 13 is a schematic flow chart of an image processing method according to some embodiments of the present invention.
  • FIG. 14 is a schematic diagram of functional blocks of an image processing apparatus according to some embodiments of the present invention.
  • 15 is a schematic flow chart of an image processing method according to some embodiments of the present invention.
  • 16 is a schematic diagram of functional blocks of an image forming apparatus according to some embodiments of the present invention.
  • 17 is a schematic diagram of functional modules of an electronic device according to some embodiments of the present invention.
  • FIG. 18 is a schematic diagram of functional blocks of an electronic device in accordance with some embodiments of the present invention.
  • an image processing method is used to convert a color patch image into a pseudo original image in an imaging device
  • the imaging device includes an image sensor
  • the image sensor includes a photosensitive pixel unit array and is disposed in the photosensitive pixel unit.
  • the method includes the following steps: including a plurality of original pixels, each photosensitive pixel corresponding to one original pixel, and the image processing method includes the following steps:
  • S14 Convert the color block image into a pseudo original image, where the original image includes an array of original pixels, the original pixel includes a current pixel, and the original pixel includes an associated pixel corresponding to the current pixel, and the color block image includes a highlighted area.
  • the step of converting the patch image to the original image includes the following steps:
  • an image processing method according to an embodiment of the present invention may be implemented by the image processing apparatus 10 of the embodiment of the present invention.
  • the image processing apparatus 10 is used to convert a patch image into an original image in the image forming apparatus 100.
  • the image forming apparatus 100 includes an image sensor 20 including a photosensitive pixel unit array 212 and a filter unit disposed on the photosensitive pixel unit array.
  • the array 211, each of the filter unit arrays 211 covers a corresponding one of the photosensitive pixel units 212a, each of the photosensitive pixel units 212a includes a plurality of photosensitive pixels 2121, and the patch images include image pixel units arranged in a predetermined array, and the image pixel units include multiple
  • the dividing module 11 is configured to divide the patch image into a plurality of luma analysis regions; the calculating module 12 is configured to calculate the luma value of each luma analyzing region; and the merging module 13 is configured to merge the corresponding luma regions in which the luminance values meet the conditions into high a bright area; the conversion module 14 is configured to convert the color block image into a pseudo original image, the original image includes an array of original pixels, the original pixel includes a current pixel, and the original pixel includes an associated pixel corresponding to the current pixel, and the color block
  • the image includes a highlight area, and the conversion module 14 includes a first determination unit 141, a second determination unit 143, a first calculation unit 145, a second calculation unit 147, and a third calculation unit 149.
  • the first determining unit 141 is configured to determine whether the associated pixel is located in the highlighted area; the second determining unit 143 is configured to determine whether the color of the current pixel is the same as the color of the associated pixel when the associated pixel is located in the highlighted area; 145, when the color of the current pixel is the same as the color of the associated pixel, the pixel value of the associated pixel is used as the pixel value of the current pixel; the second calculating unit 147 is configured to: when the color of the current pixel is different from the color of the associated pixel, The pixel value of the associated pixel unit is calculated by the first interpolation algorithm, and the image pixel unit includes an associated pixel unit, the color of the associated pixel unit is the same as the current pixel and adjacent to the current pixel; the third calculating unit 149 is configured to When the associated pixel is located outside the highlighted area, the pixel value of the current pixel is calculated by the second interpolation algorithm, and the complexity of the second interpolation algorithm is smaller than the first inter
  • step S11 can be implemented by the dividing module 11
  • step S12 can be implemented by the computing module 12
  • step S13 can be implemented by the merging module 13
  • step S14 can be implemented by the converting module 14
  • step S141 can be performed by the first determining unit 141.
  • step S143 may be implemented by the second determination unit 143
  • step S145 may be implemented by the first calculation unit
  • step S147 may be implemented by the second calculation unit 147
  • step S149 may be implemented by the third calculation unit 149.
  • the first interpolation algorithm is used for processing, and the highlighted region can be improved.
  • the noise of the region is higher, so the improvement of the sharpness of the image after processing with the first interpolation algorithm is not obvious.
  • the complexity of the first interpolation algorithm includes time complexity and spatial complexity, and compared with the second interpolation algorithm, the time complexity and spatial complexity of the first interpolation algorithm are relatively large.
  • the second interpolation algorithm with the complexity less than the first interpolation algorithm is processed for the image outside the highlighted area, which not only improves the image quality, but also improves the image quality.
  • the data processing and image processing time required for the image can be reduced, thereby improving the user experience.
  • the brightness analysis regions are arranged in an array.
  • the patch image may be divided into M*N luma analysis regions, and the luminance value is greater than the pre-determined by calculating the luminance value of each luma analysis region and comparing with the preset threshold.
  • the brightness area of the threshold is divided into highlighted areas. In this way, the image processing is performed on the highlighted image region using the first interpolation algorithm to obtain a high quality image.
  • each luma analysis region includes one or more original pixels.
  • each original pixel in the patch image can be used as a luminance analysis region, that is, after comparing the luminance value corresponding to each original pixel with a preset threshold, The original pixel whose luminance value is greater than the preset threshold is divided into a highlighted area. In this way, the first interpolation algorithm is used for image processing on the highlighted area to obtain a high quality image.
  • the image sensor 20 of the embodiment of the present invention includes a photosensitive pixel unit array 212 and a filter unit array 211 disposed on the photosensitive pixel unit array 212.
  • the photosensitive pixel unit array 212 includes a plurality of photosensitive pixel units 212a, each of which includes a plurality of adjacent photosensitive pixels 2121.
  • Each of the photosensitive pixels 2121 includes a photosensitive device 21211 and a transfer tube 21212, wherein the photosensitive device 21211 can be a photodiode, and the transfer tube 21212 can be a MOS transistor.
  • the filter unit array 211 includes a plurality of filter units 211a, each of which covers a corresponding one of the photosensitive pixel units 212a.
  • the filter cell array 211 includes a Bayer array, that is, the adjacent four filter units 211a are respectively a red filter unit and a blue filter unit. And two green filter units.
  • Each of the photosensitive pixel units 212a corresponds to the filter 211a of the same color. If one photosensitive pixel unit 212a includes a total of n adjacent photosensitive devices 21211, one filter unit 211a covers n of one photosensitive pixel unit 212a.
  • the photosensitive device 21211, the filter unit 211a may be an integrated structure, or may be n Separate sub-filters are assembled and connected together.
  • each photosensitive pixel unit 212a includes four adjacent photosensitive pixels 2121, and two adjacent photosensitive pixels 2121. together constitute one photosensitive pixel sub-unit 2120.
  • the photosensitive pixel sub-unit 2120 further includes a source follower.
  • the photosensitive pixel unit 212a further includes an adder 2122. Wherein one end electrode of each of the one of the photosensitive pixel sub-units 2120 is connected to the cathode electrode of the corresponding photosensitive device 21211, and the other end of each of the transfer tubes 21212 is commonly connected to the gate electrode of the source follower 21213. And connected to an analog to digital converter 21214 via a source follower 21213 source electrode.
  • the source follower 21213 may be a MOS transistor.
  • the two photosensitive pixel subunits 2120 are connected to the adder 2122 through respective source followers 21213 and analog to digital converters 21214.
  • the adjacent four photosensitive devices 21211 of one photosensitive pixel unit 212a of the image sensor 20 of the embodiment of the present invention share a filter unit 211a of the same color, and each photosensitive device 21211 is connected to a transmission tube 21212.
  • the two adjacent photosensitive devices 21211 share a source follower 21213 and an analog to digital converter 21214, and the adjacent four photosensitive devices 21211 share an adder 2122.
  • adjacent four photosensitive devices 21211 are arranged in a 2*2 array.
  • the two photosensitive devices 21211 in one photosensitive pixel subunit 2120 may be in the same column.
  • the pixels may be combined to output a combined image.
  • the photosensitive device 21211 is configured to convert illumination into electric charge, and the generated electric charge is proportional to the illumination intensity, and the transmission tube 21212 is configured to control the on or off of the circuit according to the control signal.
  • the source follower 21213 is configured to convert the charge signal generated by the light-sensing device 21211 into a voltage signal.
  • Analog to digital converter 21214 is used to convert the voltage signal to a digital signal.
  • the adder 2122 is for summing the two digital signals for common output for processing by the image processing module connected to the image sensor 20.
  • the image sensor 20 of the embodiment of the present invention can combine 16M photosensitive pixels into 4M, or output a combined image.
  • the size of the photosensitive pixels is equivalent to change. It is 4 times the original size, which improves the sensitivity of the photosensitive pixels.
  • the noise in the image sensor 20 is mostly random noise, it is possible that for the photosensitive pixels before the combination, there is a possibility that noise is present in one or two pixels, and the four photosensitive pixels are combined into one large photosensitive light. After the pixel, the influence of the noise on the large pixel is reduced, that is, the noise is weakened, and the signal-to-noise ratio is improved.
  • the resolution of the merged image will also decrease as the pixel value decreases.
  • the patch image can be output through image processing.
  • the photosensitive device 21211 is for converting illumination into electric charge, and the generated electric charge is proportional to the intensity of the illumination, and the transmission tube 21212 is for controlling the on or off of the circuit according to the control signal.
  • the source follower 21213 is configured to convert the charge signal generated by the light-sensing device 21211 into a voltage signal.
  • Analog to digital converter 21214 is used to convert the voltage signal to a digital signal for processing by an image processing module coupled to image sensor 20.
  • the image sensor 20 of the embodiment of the present invention can also maintain a 16M photosensitive pixel output, or an output patch image, and the patch image includes an image pixel unit, and an image pixel unit.
  • the original pixel is arranged in a 2*2 array, the size of the original pixel is the same as the size of the photosensitive pixel, but since the filter unit 211a covering the adjacent four photosensitive devices 21211 is the same color, that is, although four The photosensitive devices 21211 are respectively exposed, but the filter units 211a covered by them are of the same color. Therefore, the adjacent four original pixels of each image pixel unit output are the same color, and the resolution of the image cannot be improved.
  • An image processing method is configured to process an output patch image to obtain a pseudo original image.
  • the processing module receives the processing to output a true color image.
  • the color patch image is outputted separately for each photosensitive pixel at the time of output. Since the adjacent four photosensitive pixels have the same color, the four adjacent original pixels of one image pixel unit have the same color and are atypical Bayer arrays.
  • the image processing module cannot directly process the atypical Bayer array, that is, when the image sensor 20 adopts the unified image processing mode, the true color image output in the merge mode is compatible with the two modes of true color image output and The true color image output in the color block mode needs to convert the color block image into a pseudo original image, or convert the image pixel unit of the atypical Bayer array into a pixel arrangement of a typical Bayer array.
  • the original image includes imitation original pixels arranged in a Bayer array.
  • the pseudo original pixel includes a current pixel, and the original pixel includes an associated pixel corresponding to the current pixel.
  • the highlighted area of the patch image is first converted into a Bayer image array, and the image processing is performed using a first interpolation algorithm.
  • the current pixels are R3'3' and R5'5', and the corresponding associated pixels are R33 and R55, respectively.
  • the pixel values above and below should be broadly understood as the color attribute values of the pixel, such as color values.
  • the associated pixel unit includes a plurality of, for example, four, original pixels in the image pixel unit that are the same color as the current pixel and are adjacent to the current pixel.
  • the associated pixel corresponding to R5'5' is B55, which is adjacent to the image pixel unit where B55 is located and has the same color as R5'5'.
  • the image pixel units in which the associated pixel unit is located are image pixel units in which R44, R74, R47, and R77 are located, and are not other red image pixel units that are spatially farther from the image pixel unit in which B55 is located.
  • red original pixels closest to the B55 are R44, R74, R47 and R77, respectively, that is, the associated pixel unit of R5'5' is composed of R44, R74, R47 and R77, R5'5'
  • the colors are the same as and adjacent to R44, R74, R47 and R77.
  • the original pixel is converted into the original pixel in different ways, thereby converting the color block image into the original image, and a special Bayer array structure filter is adopted when the image is captured.
  • the image signal-to-noise ratio is improved, and in the image processing process, the color block image is interpolated by the first interpolation algorithm, thereby improving the resolution and resolution of the image.
  • step S147 includes the following steps:
  • S1472 Calculate the weight in each direction of the associated pixel; and S1473: calculate the pixel value of the current pixel according to the amount of the gradient and the weight.
  • the second calculation unit 147 includes a first calculation subunit 1471, a second calculation subunit 1472, and a third calculation subunit 1473.
  • the first calculation sub-unit 1471 is configured to calculate the amount of gradation in each direction of the associated pixel; the second calculation sub-unit 1472 is for calculating the weight in each direction of the associated pixel; the third calculation sub-unit 1473 is for calculating the current based on the gradation amount and the weight The pixel value of the pixel.
  • step S1471 can be implemented by the first calculation sub-unit 1471
  • step S1472 can be implemented by the second calculation sub-unit 1472
  • step S1473 can be implemented by the third calculation sub-unit 1473.
  • the first interpolation algorithm is an energy gradation of the reference image in different directions, and the color corresponding to the current pixel is the same and the adjacent associated pixel unit is calculated by linear interpolation according to the gradation weight in different directions.
  • the pixel value of the current pixel in the direction in which the amount of change in energy is small, the reference specific gravity is large, and therefore, the weight at the time of interpolation calculation is large.
  • R5'5' is interpolated from R44, R74, R47 and R77, and there is no color phase in the horizontal and vertical directions.
  • the same original pixel so the component of the color in the horizontal and vertical directions needs to be calculated from the associated pixel unit.
  • the components in the horizontal direction are R45 and R75
  • the components in the vertical direction are R54 and R57 which can be calculated by R44, R74, R47 and R77, respectively.
  • R45 R44*2/3+R47*1/3
  • R75 2/3*R74+1/3*R77
  • R54 2/3*R44+1/3*R74
  • R57 2/3 *R47+1/3*R77.
  • the amount of gradation and the weight in the horizontal and vertical directions are respectively calculated, that is, the gradation amount in different directions according to the color is determined to determine the reference weights in different directions at the time of interpolation, and the weight is smaller in the direction of the gradation amount. Large, and in the direction of larger gradient, the weight is smaller.
  • the gradient amount X1
  • the gradient amount X2
  • W1 X1/(X1+X2)
  • W2 X2/(X1+X2) .
  • R5'5' (2/3*R45+1/3*R75)*W2+(2/3*R54+1/3*R57)*W1. It can be understood that if X1 is greater than X2, W1 is greater than W2, so the weight in the horizontal direction is W2 when calculating, and the weight in the vertical direction is W1, and vice versa.
  • the pixel value of the current pixel can be calculated according to the first interpolation algorithm.
  • the original pixel can be converted into a pseudo original pixel arranged in a typical Bayer array, that is, the adjacent original pixels of the four 2*2 arrays include a red original pixel. , two green imitation original pixels and one blue imitation original pixel.
  • the first interpolation algorithm includes, but is not limited to, a manner in which only pixel values of the same color in both the vertical and horizontal directions are considered in the calculation, and for example, reference may also be made to pixel values of other colors.
  • the step S147 includes steps:
  • Step S147 includes steps:
  • S148a Perform white balance compensation and restoration on the original image.
  • the conversion module 14 includes a white balance compensation module 146a and a white balance compensation reduction module 148a.
  • the white balance compensation module 146a is configured to perform white balance compensation on the patch image
  • the white balance compensation and restoration module 148a is configured to perform white balance compensation and restoration on the original image.
  • step S146a can be implemented by the white balance compensation module 146a
  • step S148a can be implemented with the white balance compensation restoration module 148a.
  • the red and blue imitation original pixels often refer not only to the color of the original pixel of the channel whose color is the same, but also refer to The color weight of the original pixels of the green channel, therefore, white balance compensation is required before interpolation to eliminate the effects of white balance in the interpolation calculation.
  • white balance compensation In order not to destroy the white balance of the patch image, it is necessary to perform white balance compensation reduction after the interpolation, and restore according to the gain values of red, green and blue in the compensation.
  • the step S147 includes steps:
  • S146b Perform dead pixel compensation on the patch image.
  • the conversion module 14 includes a dead point compensation unit 146b for performing dead pixel compensation on the patch image.
  • step S146b can be implemented by the dead point compensation unit 146b.
  • the image sensor 20 may have a dead pixel.
  • the bad point usually does not always show the same color as the sensitivity changes, and the presence of the dead pixel will affect the image quality. Therefore, in order to ensure accurate interpolation, The effect of the dead point requires bad point compensation before interpolation.
  • the original pixel may be detected.
  • the pixel compensation may be performed according to the pixel value of the other original image of the image pixel unit in which it is located.
  • the step S147 includes steps:
  • the conversion module 14 includes a crosstalk compensation unit 146c for crosstalk compensation of the patch image.
  • step S146c can be implemented by the crosstalk compensation unit 146c.
  • the four photosensitive pixels in one photosensitive pixel unit cover the filter of the same color, and there may be a difference in sensitivity between the photosensitive pixels, so that the solid color region in the true color image converted by the original image is Fixed spectral noise occurs, affecting the quality of the image. Therefore, it is necessary to perform crosstalk compensation on the patch image.
  • step S147 includes steps:
  • S148b Perform lens shading correction, demosaicing, noise reduction and edge sharpening on the original image.
  • the conversion module 14 further includes a processing unit 148b.
  • step S148b can be implemented by the processing unit 148b.
  • the original pixel is arranged as a typical Bayer array, and the processing module 148b can be used for processing, including lens shadow correction, demosaicing, noise reduction and edge sharpening. Processing, in this way, the true color image can be output to the user after processing.
  • a second interpolation algorithm For an image outside the highlighted area of a frame of color block image, a second interpolation algorithm is needed for image processing.
  • the interpolation process of the second interpolation algorithm is: taking the average value of the pixel values of all the original pixels in each image pixel unit outside the highlighted area, and then determining whether the color of the current pixel and the associated pixel are the same, in the current pixel and the associated pixel. When the color values are the same, the pixel value of the associated pixel is taken as the pixel value of the current pixel. When the current pixel and the associated pixel color are different, the pixel value of the original pixel in the image pixel unit with the same color as the current pixel value is taken as the pixel value. The pixel value of the current pixel.
  • the pixel values of R11, R12, R21, and R22 are all Ravg, and the pixel values of Gr31, Gr32, Gr41, and Gr42 are all Gravg, and the pixel values of Gb13, Gb14, Gb23, and Gb24 are all Gbavg, B33, B34, and B43.
  • the pixel value of B44 is Bavg.
  • the associated pixel corresponding to the current pixel B22 is R22. Since the color of the current pixel B22 is different from the color of the associated pixel R22, the pixel value of the current pixel B22 should be the corresponding blue filter of the nearest neighbor.
  • the pixel value is the value of any Bavg of B33, B34, B43, B44.
  • other colors are also calculated using a second interpolation algorithm to obtain pixel values for individual pixels.
  • the original pixel is converted to the original pixel by the second interpolation algorithm, thereby converting the patch image into the original image.
  • the time complexity and spatial complexity of the second interpolation algorithm are smaller than the first interpolation algorithm.
  • the second interpolation algorithm is used to process the color block image outside the highlighted area, which reduces the time required for image processing and improves the user experience.
  • an imaging apparatus 100 includes an image processing apparatus 10.
  • an electronic device 1000 includes an imaging device 100 and a touch screen 200.
  • electronic device 1000 includes a cell phone and a tablet.
  • Both the mobile phone and the tablet computer have a camera, that is, the imaging device 100.
  • the image processing method of the embodiment of the present invention can be used to obtain a high-resolution picture.
  • the electronic device 1000 is not limited to a mobile phone and a tablet computer, and includes other electronic devices having a shooting function.
  • imaging device 100 includes a front camera and a rear camera.
  • many electronic devices 1000 include a front camera and a rear camera. Both the front camera and the rear camera can implement image processing by using the image processing method of the embodiment of the present invention to enhance the user experience.
  • an electronic device 1000 includes a processor 400, a memory 500, a circuit board 600, a power supply circuit 700, and a housing 800.
  • the circuit board 600 is disposed inside the space enclosed by the housing 800, the processor 400 and the memory 500 are disposed on the circuit board 600;
  • the power supply circuit 700 is used to supply power to various circuits or devices of the electronic device 1000;
  • the memory 500 is used for storing Executable program code;
  • the processor 400 runs a program corresponding to the executable program code by reading the executable code stored in the memory 500 to implement any of the above embodiments of the present invention.
  • Image processing method is a processor 400, a memory 500, a circuit board 600, a power supply circuit 700, and a housing 800.
  • processor 400 can be used to perform the following steps:
  • S14 Convert the color block image into a pseudo original image, where the original image includes an array of original pixels, the original pixel includes a current pixel, and the original pixel includes an associated pixel corresponding to the current pixel, and the color block image includes a highlighted area.
  • the step of converting the patch image to the original image includes the following steps:
  • the pixel value of the current pixel is calculated according to the pixel value of the associated pixel unit by using a first interpolation algorithm, where the image pixel unit includes an associated pixel unit, and the color of the associated pixel unit is related to the current pixel. Same and adjacent to the current pixel; and
  • a "computer-readable medium” can be any apparatus that can contain, store, communicate, propagate, or transport a program for use in an instruction execution system, apparatus, or device, or in conjunction with the 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 (RAM), Read only memory (ROM), erasable editable read only memory (EPROM or flash memory), fiber optic devices, and portable compact disk read only memory (CDROM).
  • the computer readable medium may even be a paper or other suitable medium on which the program may be printed, as it may be optically scanned, for example by paper or other medium, followed by editing, interpretation or, if appropriate, in other suitable manners. Processing to obtain the program electronically and then storing it in computer memory.
  • portions of the invention may be implemented in hardware, software, firmware or a combination thereof.
  • multiple steps or methods may be performed by software or firmware stored in a memory and executed by a suitable instruction execution system.
  • a suitable instruction execution system For example, if executed in hardware, as in another embodiment, it can be performed by any one of the following techniques or combinations thereof known in the art: having logic gates for performing logic functions on data signals Discrete logic circuits, application specific integrated circuits with suitable combinational logic gates, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.
  • each functional unit in each embodiment of the present invention may be integrated into one processing module, or each unit may exist physically separately, or two or more units may be integrated into one module.
  • the above integrated modules can be executed in the form of hardware or in the form of software functional modules.
  • An integrated module can also be stored on a computer readable storage medium if it is executed as a software function module and sold or used as a standalone product.
  • the above mentioned storage medium may be a read only memory, a magnetic disk or an optical disk or the like.

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Abstract

本发明公开了一种图像处理方法、图像处理装置、成像装置及电子装置。图像处理方法包括：将色块图像划分为多个亮度分析区域；计算每个亮度分析区域的亮度值，将亮度值符合条件的对应的亮度分析区域归并为高亮区域；将色块图像高亮区域用第一插值算法转化成仿原图像；色块图像高亮区域外的图像采用第二插值算法处理。本发明实施方式的图像处理方法根据图像亮度的判断，仅对色块图像亮度较高的区域进行第一插值算法的图像处理，从而获得高质量的图像，同时避免了利用第一插值算法对整帧图像进行图像处理导致的处理时间长的问题，提升了处理效率。

Description

图像处理方法、图像处理装置、成像装置及电子装置
优先权信息
本申请请求2016年11月29日向中国国家知识产权局提交的、专利申请号为201611099894.X的专利申请的优先权和权益，并且通过参照将其全文并入此处。
技术领域
本发明涉及成像技术，尤其涉及一种图像处理方法、图像处理装置、成像装置及电子装置。
背景技术
现有的一种图像传感器包括像素单元阵列和设置在像素单元阵列上的滤光片单元阵列，每个滤光片单元阵列覆盖对应一个感光像素单元，每个感光像素单元包括多个感光像素。工作时，可以控制图像传感器曝光输出合并图像，合并图像包括合并像素阵列，同一像素单元的多个感光像素合并输出作为一个合并像素。如此，可以提高合并图像的信噪比，然而，合并图像的解析度降低。当然，也可以控制图像传感器曝光输出高像素的色块图像，色块图像包括原始像素阵列，每个感光像素对应一个原始像素。然而，由于同一滤光片单元对应的多个原始像素颜色相同，同样无法提高色块图像的解析度。因此，需要通过插值计算的方式将高像素色块图像转换成高像素的仿原图像，仿原图像可以包括呈拜耳阵列排布的仿原像素。仿原图像可以通过图像处理方法转换成真彩图像并保存下来。插值计算可以提高真彩图像的清晰度，然而耗费资源且耗时，导致拍摄时间加长，用户体验差。此外，并非所有场景都适用或者需要输出仿原真彩图像。
发明内容
本发明的实施例提供一种图像处理方法、图像处理装置、成像装置及电子装置。
本发明实施方式的图像处理方法，用于成像装置中将色块图像转换成仿原图像，所述成像装置包括图像传感器，所述图像传感器包括感光像素单元阵列和设置在所述感光像素单元阵列上的滤光片单元阵列，每个所述滤光片单元阵列覆盖对应一个所述感光像素单元，每个所述感光像素单元包括多个感光像素，所述色块图像包括预定阵列排布的图像像素单元，所述图像像素单元包括多个原始像素，每个所述感光像素对应一个所述原始像素，所述图像处理方法包括以下步骤：
将所述色块图像划分成多个亮度分析区域；
计算每个所述亮度分析区域的亮度值；
将所述亮度值符合条件的对应的所述亮度区域归并为高亮区域；
将所述色块图像转换成仿原图像，所述仿原图像包括阵列排布的仿原像素，所述仿原像素包括当前像素，所述原始像素包括与所述当前像素对应的关联像素，所述色块图像包括所述高亮区域，所述将所述色块图像转换成所述仿原图像的步骤包括以下步骤：
判断所述关联像素是否位于所述高亮区域内；
在所述关联像素位于所述高亮区域内时判断所述当前像素的颜色与所述关联像素的颜色是否相同；
在所述当前像素的颜色与所述关联像素的颜色相同时，将所述关联像素的像素值作为所述当前像素的像素值；
在所述当前像素的颜色与所述关联像素的颜色不同时，根据关联像素单元的像素值通过第一插值算法计算所述当前像素的像素值，所述图像像素单元包括所述关联像素单元，所述关联像素单元的颜色与所述当前像素相同且与所述当前像素相邻；和
在所述关联像素位于所述高亮区域外时，通过第二插值算法计算所述当前像素的像素值，所述第二插值算法的复杂度小于所述第一插值算法。
本发明实施方式的图像处理装置，用于成像装置中将色块图像转换成仿原图像，所述成像装置包括图像传感器，所述图像传感器包括感光像素单元阵列和设置在所述感光像素单元阵列上的滤光片单元阵列，每个所述滤光片单元阵列覆盖对应一个所述感光像素单元，每个所述感光像素单元包括多个感光像素，所述色块图像包括预定阵列排布的图像像素单元，所述图像像素单元包括多个原始像素，每个所述感光像素对应一个所述原始像素，所述图像处理装置包括划分模块、计算模块、归并模块、转换模块。所述划分模块用于将所述色块图像划分成多个亮度分析区域；所述计算模块用于计算每个亮度分析区域的亮度值；所述归并模块用于将所述亮度值符合条件的对应的所述亮度区域归并为高亮区域；所述转换模块用于将所述色块图像转换成仿原图像，所述仿原图像包括阵列排布的仿原像素，所述仿原像素包括当前像素，所述原始像素包括与所述当前像素对应的关联像素，所述色块图像包括所述高亮区域，所述转换模块包括第一判断单元、第二判断单元、第一计算单元、第二计算单元和第三计算单元。所述第一判断单元用于判断所述关联像素是否位于所述高亮区域内；所述第二判断单元用于在所述关联像素位于所述高亮区域内时判断所述当前像素的颜色与所述关联像素的颜色是否相同；所述第一计算单元用于在所述当前像素的颜色与所述关联像素的颜色相同时，将所述关联像素的像素值作为所述当前像素的像素值；所述第二计算单元用于在所述当前像素的颜色与所述关联像素的颜色不同时，根据关联像素 单元的像素值通过第一插值算法计算所述当前像素的像素值，所述图像像素单元包括所述关联像素单元，所述关联像素单元的颜色与所述当前像素相同且与所述当前像素相邻；所述第三计算单元用于在所述关联像素位于所述高亮区域外时，通过第二插值算法计算所述当前像素的像素值，所述第二插值算法的复杂度小于所述第一插值算法。
本发明实施方式的成像装置包括上述的图像处理装置。
本发明实施方式的电子装置，所述电子装置包括上述的成像装置和触摸屏。
本发明实施方式的电子装置包括壳体、处理器、存储器、电路板和电源电路。所述电路板安置在所述壳体围成的空间内部，所述处理器和所述存储器设置在所述电路板上；所述电源电路用于为所述电子装置的各个电路或器件供电；所述存储器用于存储可执行程序代码；所述处理器通过读取所述存储器中存储的可执行程序代码来运行与所述可执行程序代码对应的程序，以用于执行上述的图像处理方法。
本发明实施方式的图像处理方法、图形处理装置、成像装置及电子装置根据图像亮度的判断，仅对色块图像亮度较高的区域进行第一插值算法的图像处理，从而获得高质量的图像，同时避免了利用第一插值算法对整帧图像进行图像处理导致的处理时间长的问题，提升了处理效率。
本发明的实施方式的附加方面和优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本发明的实施方式的实践了解到。
附图说明
本发明的上述和/或附加的方面和优点从结合下面附图对实施方式的描述中将变得明显和容易理解，其中：
图1是本发明实施方式的图像处理方法的流程示意图；
图2是本发明实施方式的图像处理方法的另一流程示意图；
图3是本发明实施方式的图像处理装置的功能模块示意图；
图4是本发明实施方式的图像传感器的模块示意图；
图5是本发明实施方式的图像传感器的电路示意图；
图6是本发明实施方式的滤光片单元的示意图；
图7是本发明实施方式的图像传感器的结构示意图；
图8是本发明实施方式的合并图像状态示意图；
图9是本发明实施方式的色块图像的状态示意图；
图10是本发明实施方式的图像处理方法的状态示意图；
图11是本发明某些实施方式的图像处理方法的流程示意图；
图12是本发明某些实施方式的第二计算单元的功能模块示意图；
图13是本发明某些实施方式的图像处理方法的流程示意图；
图14是本发明某些实施方式的图像处理装置的功能模块示意图；
图15是本发明某些实施方式的图像处理方法的流程示意图；
图16是本发明某些实施方式的成像装置的功能模块示意图；
图17是本发明某些实施方式的电子装置的功能模块示意图；
图18是本发明某些实施方式的电子装置的功能模块示意图。
具体实施方式
下面详细描述本发明的实施方式，所述实施方式的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施方式是示例性的，仅用于解释本发明，而不能理解为对本发明的限制。
请参阅图1至2，本发明实施方式的图像处理方法，用于成像装置中将色块图像转换成仿原图像，成像装置包括图像传感器，图像传感器包括感光像素单元阵列和设置在感光像素单元阵列上的滤光片单元阵列，每个滤光片单元阵列覆盖对应一个感光像素单元，每个感光像素单元包括多个感光像素，色块图像包括预定阵列排布的图像像素单元，图像像素单元包括多个原始像素，每个感光像素对应一个原始像素，图像处理方法包括以下步骤：
S11：将色块图像划分成多个亮度分析区域；
S12：计算每个亮度分析区域的亮度值；
S13：将亮度值符合条件的对应的亮度区域归并为高亮区域；
S14：将色块图像转换成仿原图像，仿原图像包括阵列排布的仿原像素，仿原像素包括当前像素，原始像素包括与当前像素对应的关联像素，色块图像包括高亮区域，将色块图像转换成仿原图像的步骤包括以下步骤：
S141：判断关联像素是否位于高亮区域内；
S143：在关联像素位于高亮区域内时判断当前像素的颜色与关联像素的颜色是否相同；
S145：在当前像素的颜色与关联像素的颜色相同时，将关联像素的像素值作为当前像素的像素值；
S147：在当前像素的颜色与关联像素的颜色不同时，根据关联像素单元的像素值通过第一插值算法计算当前像素的像素值，图像像素单元包括关联像素单元，关联像 素单元的颜色与当前像素相同且与当前像素相邻；和
S149：在关联像素位于高亮区域外时，通过第二插值算法计算当前像素的像素值，第二插值算法的复杂度小于第一插值算法。
请参阅图3至图5及图16，本发明实施方式的图像处理方法可以由本发明实施方式的图像处理装置10实现。
图像处理装置10用于成像装置100中将色块图像转换成仿原图像，成像装置100包括图像传感器20，图像传感器20包括感光像素单元阵列212和设置在感光像素单元阵列上的滤光片单元阵列211，每个滤光片单元阵列211覆盖对应一个感光像素单元212a，每个感光像素单元212a包括多个感光像素2121，色块图像包括预定阵列排布的图像像素单元，图像像素单元包括多个原始像素，每个感光像素对应一个原始像素，图像处理装置10包括划分模块11、计算模块12、归并模块13、转换模块14。划分模块11用于将色块图像划分成多个亮度分析区域；计算模块12用于计算每个亮度分析区域的亮度值；归并模块13用于将亮度值符合条件的对应的亮度区域归并为高亮区域；转换模块14用于将色块图像转换成仿原图像，仿原图像包括阵列排布的仿原像素，仿原像素包括当前像素，原始像素包括与当前像素对应的关联像素，色块图像包括高亮区域，转换模块14包括第一判断单元141、第二判断单元143、第一计算单元145、第二计算单元147和第三计算单元149。第一判断单元141用于判断关联像素是否位于高亮区域内；第二判断单元143用于在关联像素位于高亮区域内时判断当前像素的颜色与关联像素的颜色是否相同；第一计算单元145用于在当前像素的颜色与关联像素的颜色相同时，将关联像素的像素值作为当前像素的像素值；第二计算单元147用于在当前像素的颜色与关联像素的颜色不同时，根据关联像素单元的像素值通过第一插值算法计算当前像素的像素值，图像像素单元包括关联像素单元，关联像素单元的颜色与当前像素相同且与当前像素相邻；第三计算单元149用于在关联像素位于高亮区域外时，通过第二插值算法计算当前像素的像素值，第二插值算法的复杂度小于第一插值算法。
也即是说，步骤S11可以由划分模块11实现，步骤S12可以由计算模块12实现，步骤S13可以由归并模块13实现，步骤S14可以由转换模块14实现，步骤S141可以由第一判断单元141实现，步骤S143可以由第二判断单元143实现，步骤S145可以由第一计算单元实现，步骤S147可以由第二计算单元147实现，步骤S149可以由第三计算单元149实现。
可以理解，对于亮度较高的区域，采用第一插值算法进行处理，可以提高该高亮区 域内的图像的清晰度。而对于亮度较低的区域，由于该区域的噪声较高，因此，采用第一插值算法进行处理后图像的清晰度的提升不明显。此外，由于第一插值算法的复杂度包括时间复杂度和空间复杂度，且相较于第二插值算法，第一插值算法的时间复杂度和空间复杂度相对较大。如此，仅对高亮区域采用复杂度较大第一插值算法进行处理，而对于高亮区域外的图像采用复杂度小于第一插值算法的第二插值算法进行处理，不仅可以提升图像的质量，同时可以减少图像所需处理的数据和图像处理的时间，从而提升用户体验。
在某些实施方式中，亮度分析区域呈阵列排布。
可以理解，在某些实施方式中，可将色块图像划分成M*N个亮度分析区域，通过对每个亮度分析区域的亮度值计算并与预设阈值进行比较后，将亮度值大于预设阈值的亮度区域划分为高亮区域。如此，再对高亮图像区域利用第一插值算法进行图像处理，以获得高质量图像。
在某些实施方式中，每个亮度分析区域包括一个或者多个原始像素。
可以理解，在某些实施方式中，可将色块图像中的每个原始像素作为一个亮度分析区域，也即是说，将每个原始像素对应的亮度值与预设阈值进行比较后，将亮度值大于预设阈值的原始像素划分为高亮区域。如此，再对高亮区域利用第一插值算法进行图像处理，以获得高质量图像。
请一并参阅图4至图7，本发明实施方式的图像传感器20包括感光像素单元阵列212和设置在感光像素单元阵列212上的滤光片单元阵列211。
进一步地，感光像素单元阵列212包括多个感光像素单元212a，每个感光像素单元212a包括多个相邻的感光像素2121。每个感光像素2121包括一个感光器件21211和一个传输管21212，其中，感光器件21211可以是光电二极管，传输管21212可以是MOS晶体管。
滤光片单元阵列211包括多个滤光片单元211a，每个滤光片单元211a覆盖对应一个感光像素单元212a。
具体地，在某些示例中，滤光片单元阵列211包括拜耳阵列，也即是说，相邻的四个滤光片单元211a分别为一个红色滤光片单元、一个蓝色滤光片单元和两个绿色滤光片单元。
每一个感光像素单元212a对应同一颜色的滤光片211a，若一个感光像素单元212a中一共包括n个相邻的感光器件21211，那么一个滤光片单元211a覆盖一个感光像素单元212a中的n个感光器件21211，该滤光片单元211a可以是一体构造，也可以由n 个独立的子滤光片组装连接在一起。
在某些实施方式中，每个感光像素单元212a包括四个相邻的感光像素2121，相邻两个感光像素2121共同构成一个感光像素子单元2120，感光像素子单元2120还包括一个源极跟随器21213和一个模数转换器21214。感光像素单元212a还包括一个加法器2122。其中，一个感光像素子单元2120中的每个传输管21212的一端电极被连接到对应感光器件21211的阴极电极，每个传输管21212的另一端被共同连接至源极跟随器21213的闸极电极，并通过源极跟随器21213源极电极连接至一个模数转换器21214。其中，源极跟随器21213可以是MOS晶体管。两个感光像素子单元2120通过各自的源极跟随器21213及模数转换器21214连接至加法器2122。
也即是说，本发明实施方式的图像传感器20的一个感光像素单元212a中相邻的四个感光器件21211共用一个同颜色的滤光片单元211a，每个感光器件21211对应连接一个传输管21212，相邻两个感光器件21211共用一个源极跟随器21213和一个模数转换器21214，相邻四个感光器件21211共用一个加法器2122。
进一步地，相邻四个感光器件21211呈2*2阵列排布。其中，一个感光像素子单元2120中的两个感光器件21211可以处于同一列。
在成像时，当同一滤光片单元211a下覆盖的两个感光像素子单元2120或者说四个感光器件21211同时曝光时，可以对像素进行合并进而可输出合并图像。
具体地，感光器件21211用于将光照转换为电荷，且产生的电荷与光照强度成比例关系，传输管21212用于根据控制信号来控制电路的导通或断开。当电路导通时，源极跟随器21213用于将感光器件21211经光照产生的电荷信号转换为电压信号。模数转换器21214用于电压信号转换为数字信号。加法器2122用于将两路数字信号相加共同输出，以供与图像传感器20相连的图像处理模块处理。
请参阅图8，以16M的图像传感器20举例来说，本发明实施方式的图像传感器20可以将16M的感光像素合并成4M，或者说，输出合并图像，合并后，感光像素的大小相当于变成了原来大小的4倍，从而提升了感光像素的感光度。此外，由于图像传感器20中的噪声大部分都是随机噪声，对于合并之前的感光像素来说，有可能其中一个或两个像素中存在噪点，而在将四个感光像素合并成一个大的感光像素后，减小了噪点对该大像素的影响，也即是减弱了噪声，提高了信噪比。
但在感光像素大小变大的同时，由于像素值降低，合并图像的解析度也将降低。
在成像时，当同一滤光片单元211a覆盖的四个感光器件21211依次曝光时，经过图像处理可以输出色块图像。
具体地，感光器件21211用于将光照转换为电荷，且产生的电荷与光照的强度成比例关系，传输管21212用于根据控制信号来控制电路的导通或断开。当电路导通时，源极跟随器21213用于将感光器件21211经光照产生的电荷信号转换为电压信号。模数转换器21214用于将电压信号转换为数字信号以供与图像传感器20相连的图像处理模块处理。
请参阅图9，以16M的图像传感器20举例来说，本发明实施方式的图像传感器20还可以保持16M的感光像素输出，或者说输出色块图像，色块图像包括图像像素单元，图像像素单元包括2*2阵列排布的原始像素，该原始像素的大小与感光像素大小相同，然而由于覆盖相邻四个感光器件21211的滤光片单元211a为同一颜色，也即是说，虽然四个感光器件21211分别曝光，但其覆盖的滤光片单元211a颜色相同，因此，输出的每个图像像素单元的相邻四个原始像素颜色相同，仍然无法提高图像的解析度。
本发明实施方式的图像处理方法，用于对输出的色块图像进行处理，以得到仿原图像。
可以理解，合并图像在输出时，四个相邻的同色的感光像素以合并像素输出，如此，合并图像中的四个相邻的合并像素仍可看作是典型的拜耳阵列，可以直接被图像处理模块接收进行处理以输出真彩图像。而色块图像在输出时每个感光像素分别输出，由于相邻四个感光像素颜色相同，因此，一个图像像素单元的四个相邻原始像素的颜色相同，是非典型的拜耳阵列。而图像处理模块无法对非典型拜耳阵列直接进行处理，也即是说，在图像传感器20采用统一图像处理模式时，为兼容两种模式的真彩图像输出即合并模式下的真彩图像输出及色块模式下的真彩图像输出，需将色块图像转换为仿原图像，或者说将非典型拜耳阵列的图像像素单元转换为典型的拜耳阵列的像素排布。
仿原图像包括呈拜耳阵列排布的仿原像素。仿原像素包括当前像素，原始像素包括与当前像素对应的关联像素。
对于一帧色块图像的高亮区域内的图像，先将该色块图像的高亮区域转换成拜耳图像阵列，再利用第一插值算法进行图像处理。具体地，请参阅图10，以图10为例，当前像素为R3’3’和R5’5’，对应的关联像素分别为R33和R55。
在获取当前像素R3’3’时，由于R3’3’与对应的关联像素R33的颜色相同，因此在转换时直接将R33的像素值作为R3’3’的像素值。
在获取当前像素R5’5’时，由于R5’5’与对应的关联像素B55的颜色不相同，显然不能直接将B55的像素值作为R5’5’的像素值，需要根据R5’5’的关联像素单元通过插 值的方式计算得到。
需要说明的是，以上及下文中的像素值应当广义理解为该像素的颜色属性数值，例如色彩值。
关联像素单元包括多个，例如4个，颜色与当前像素相同且与当前像素相邻的图像像素单元中的原始像素。
需要说明的是，此处相邻应做广义理解，以图10为例，R5’5’对应的关联像素为B55，与B55所在的图像像素单元相邻的且与R5’5’颜色相同的关联像素单元所在的图像像素单元分别为R44、R74、R47、R77所在的图像像素单元，而并非在空间上距离B55所在的图像像素单元更远的其他的红色图像像素单元。其中，与B55在空间上距离最近的红色原始像素分别为R44、R74、R47和R77，也即是说，R5’5’的关联像素单元由R44、R74、R47和R77组成，R5’5’与R44、R74、R47和R77的颜色相同且相邻。
如此，针对不同情况的当前像素，采用不同方式的将原始像素转换为仿原像素，从而将色块图像转换为仿原图像，由于拍摄图像时，采用了特殊的拜耳阵列结构的滤光片，提高了图像信噪比，并且在图像处理过程中，通过第一插值算法对色块图像进行插值处理，提高了图像的分辨率及解析度。
请参阅图11，在某些实施方式中，步骤S147包括以下步骤：
S1471：计算关联像素各个方向上的渐变量；
S1472：计算关联像素各个方向上的权重；和S1473：根据渐变量及权重计算当前像素的像素值。
请参阅图12，在某些实施方式中，第二计算单元147包括第一计算子单元1471、第二计算子单元1472、第三计算子单元1473。第一计算子单元1471用于计算关联像素各个方向上的渐变量；第二计算子单元1472用于计算关联像素各个方向上的权重；第三计算子单元1473用于根据渐变量及权重计算当前像素的像素值。
也即是说，步骤S1471可以由第一计算子单元1471实现，步骤S1472可以由第二计算子单元1472实现，步骤S1473可以由第三计算子单元1473实现。
具体地，第一插值算法是参考图像在不同方向上的能量渐变，将与当前像素对应的颜色相同且相邻的关联像素单元依据在不同方向上的渐变权重大小，通过线性插值的方式计算得到当前像素的像素值。其中，在能量变化量较小的方向上，参考比重较大，因此，在插值计算时的权重较大。
在某些示例中，为方便计算，仅考虑水平和垂直方向。
R5’5’由R44、R74、R47和R77插值得到，而在水平和垂直方向上并不存在颜色相 同的原始像素，因此需根据关联像素单元计算在水平和垂直方向上该颜色的分量。其中，水平方向上的分量为R45和R75、垂直方向的分量为R54和R57可以分别通过R44、R74、R47和R77计算得到。
具体地，R45＝R44*2/3+R47*1/3，R75＝2/3*R74+1/3*R77，R54＝2/3*R44+1/3*R74，R57＝2/3*R47+1/3*R77。
然后，分别计算在水平和垂直方向的渐变量及权重，也即是说，根据该颜色在不同方向的渐变量，以确定在插值时不同方向的参考权重，在渐变量小的方向，权重较大，而在渐变量较大的方向，权重较小。其中，在水平方向的渐变量X1＝|R45-R75|，在垂直方向上的渐变量X2＝|R54-R57|，W1＝X1/(X1+X2)，W2＝X2/(X1+X2)。
如此，根据上述可计算得到，R5’5’＝(2/3*R45+1/3*R75)*W2+(2/3*R54+1/3*R57)*W1。可以理解，若X1大于X2，则W1大于W2，因此计算时水平方向的权重为W2，而垂直方向的权重为W1，反之亦反。
如此，可根据第一插值算法计算得到当前像素的像素值。依据上述对关联像素的处理方式，可将原始像素转换为呈典型拜耳阵列排布的仿原像素，也即是说，相邻的四个2*2阵列的仿原像素包括一个红色仿原像素，两个绿色仿原像素和一个蓝色仿原像素。
需要说明的是，第一插值算法包括但不限于本实施例中公开的在计算时仅考虑垂直和水平两个方向相同颜色的像素值的方式，例如还可以参考其他颜色的像素值。
请参阅图13，在某些实施方式中，步骤S147前包括步骤：
S146a：对色块图像做白平衡补偿；
步骤S147后包括步骤：
S148a：对仿原图像做白平衡补偿还原。
请参阅图14，在某些实施方式中，转换模块14包括白平衡补偿模块146a和白平衡补偿还原模块148a。白平衡补偿模块146a用于对色块图像做白平衡补偿，白平衡补偿还原模块148a用于对仿原图像做白平衡补偿还原。
也即是说，步骤S146a可以由白平衡补偿模块146a实现，步骤S148a可以与白平衡补偿还原模块148a实现。
具体地，在一些示例中，在将色块图像转换为仿原图像的过程中，在插值时，红色和蓝色仿原像素往往不仅参考与其颜色相同的通道的原始像素的颜色，还会参考绿色通道的原始像素的颜色权重，因此，在插值前需要进行白平衡补偿，以在插值计算中排除白平衡的影响。为了不破坏色块图像的白平衡，因此，在插值之后需要将仿原图像进行白平衡补偿还原，还原时根据在补偿中红色、绿色及蓝色的增益值进行还原。
如此，可排除在插值过程中白平衡的影响，并且能够使得插值后得到的仿原图像保持色块图像的白平衡。
请再参阅图13，在某些实施方式中，步骤S147前包括步骤：
S146b：对色块图像做坏点补偿。
请再参阅图14，在某些实施方式中，转换模块14包括坏点补偿单元146b，坏点补偿单元146b用于对色块图像做坏点补偿。
也即是说，步骤S146b可以由坏点补偿单元146b实现。
可以理解，受限于制造工艺，图像传感器20可能会存在坏点，坏点通常不随感光度变化而始终呈现同一颜色，坏点的存在将影响图像质量，因此，为保证插值的准确，不受坏点的影响，需要在插值前进行坏点补偿。
具体地，坏点补偿过程中，可以对原始像素进行检测，当检测到某一原始像素为坏点时，可根据其所在的图像像素单元的其他原始像的像素值进行坏点补偿。
如此，可排除坏点对插值处理的影响，提高图像质量。
请再参阅图13，在某些实施方式中，步骤S147前包括步骤：
S146c：对色块图像做串扰补偿。
请再参阅图14，在某些实施方式中，转换模块14包括串扰补偿单元146c，串扰补偿单元146c用于对色块图像做串扰补偿。
也即是说，步骤S146c可以由串扰补偿单元146c实现。
具体的，一个感光像素单元中的四个感光像素覆盖同一颜色的滤光片，而感光像素之间可能存在感光度的差异，以至于以仿原图像转换输出的真彩图像中的纯色区域会出现固定型谱噪声，影响图像的质量。因此，需要对色块图像进行串扰补偿。
请再参阅图13，在某些实施方式中，步骤S147后包括步骤：
S148b：对仿原图像进行镜片阴影校正、去马赛克、降噪和边缘锐化处理。
请再参阅图14，在某些实施方式中，转换模块14还包括处理单元148b。
也即是说，步骤S148b可以由处理单元148b实现。
可以理解，将色块图像转换为仿原图像后，仿原像素排布为典型的拜耳阵列，可采用处理模块148b进行处理，处理过程中包括镜片阴影校正、去马赛克、降噪和边缘锐化处理，如此，处理后即可得到真彩图像输出给用户。
对于一帧色块图像的高亮区域外的图像，需利用第二插值算法进行图像处理。第二插值算法的插值过程是：对高亮区域外的每一个图像像素单元中所有的原始像素的像素值取均值，随后判断当前像素与关联像素的颜色是否相同，在当前像素与关联像素 颜色值相同时，取关联像素的像素值作为当前像素的像素值，在当前像素与关联像素颜色不同时，取最邻近的与当前像素值颜色相同的图像像素单元中的原始像素的像素值作为当前像素的像素值。
具体地，请参阅图15，以图15为例，先计算图像像素单元中各个原始像素的像素值:Ravg＝(R1+R2+R3+R4)/4,Gravg＝(Gr1+Gr2+Gr3+Gr4)/4,Gbavg＝(Gb1+Gb2+Gb3+Gb4)/4，Bavg＝(B1+B2+B3+B4)/4。此时，R11、R12、R21、R22的像素值均为Ravg，Gr31、Gr32、Gr41、Gr42的像素值均为Gravg，Gb13、Gb14、Gb23、Gb24的像素值均为Gbavg，B33、B34、B43、B44的像素值均为Bavg。以当前像素B22为例，当前像素B22对应的关联像素为R22，由于当前像素B22的颜色与关联像素R22的颜色不同，因此当前像素B22的像素值应取最邻近的蓝色滤光片对应的像素值即取B33、B34、B43、B44中任一Bavg的值。同样地，其他颜色也采用第二插值算法进行计算以得到各个像素的像素值。
如此，对于色块图像的高亮区域外的图像，采用第二插值算法将原始像素转换为仿原像素，从而将色块图像转换为仿原图像。第二插值算法的时间复杂度和空间复杂度小于第一插值算法，如此，采用第二插值算法处理高亮区域外的色块图像，减少了图像处理所需的时间，提升了用户体验。
请参阅图16，本发明实施方式的成像装置100包括图像处理装置10。
请参阅图17，本发明实施方式的电子装置1000包括成像装置100和触摸屏200。
在某些实施方式中，电子装置1000包括手机和平板电脑。
手机和平板电脑均带有摄像头即成像装置100，用户使用手机或平板电脑进行拍摄时，可以采用本发明实施方式的图像处理方法，以得到高解析度的图片。
需要说明的是，电子装置1000不限于手机和平板电脑，也包括其他具有拍摄功能的电子设备。
在某些实施方式中，成像装置100包括前置相机和后置相机。
可以理解，许多电子装置1000包括前置相机和后置相机，前置相机和后置相机均可采用本发明实施方式的图像处理方法实现图像处理，以提升用户体验。
请参阅图18，本发明实施方式的电子装置1000包括处理器400、存储器500、电路板600、电源电路700和壳体800。其中，电路板600安置在壳体800围成的空间内部，处理器400和存储器500设置在电路板600上；电源电路700用于为电子装置1000的各个电路或器件供电；存储器500用于存储可执行程序代码；处理器400通过读取存储器500中存储的可执行代码来运行与可执行程序代码对应的程序以实现上述中本发明任一实施方式的 图像处理方法。
例如，处理器400可以用于执行以下步骤：
S11：将色块图像划分成多个亮度分析区域；
S12：计算每个亮度分析区域的亮度值；
S13：将亮度值符合条件的对应的亮度区域归并为高亮区域；
S14：将色块图像转换成仿原图像，仿原图像包括阵列排布的仿原像素，仿原像素包括当前像素，原始像素包括与当前像素对应的关联像素，色块图像包括高亮区域，将色块图像转换成仿原图像的步骤包括以下步骤：
S141：判断关联像素是否位于高亮区域内；
S143：在关联像素位于高亮区域内时判断当前像素的颜色与关联像素的颜色是否相同；
S145：在当前像素的颜色与关联像素的颜色相同时，将关联像素的像素值作为当前像素的像素值；
S147：在当前像素的颜色与关联像素的颜色不同时，根据关联像素单元的像素值通过第一插值算法计算当前像素的像素值，图像像素单元包括关联像素单元，关联像素单元的颜色与当前像素相同且与当前像素相邻；和
S149：在关联像素位于高亮区域外时，通过第二插值算法计算当前像素的像素值，第二插值算法的复杂度小于第一插值算法。
在本说明书的描述中，参考术语“一个实施方式”、“一些实施方式”、“示意性实施方式”、“示例”、“具体示例”、或“一些示例”等的描述意指结合实施方式或示例描述的具体特征、结构、材料或者特点包含于本发明的至少一个实施方式或示例中。在本说明书中，对上述术语的示意性表述不一定指的是相同的实施方式或示例。而且，描述的具体特征、结构、材料或者特点可以在任何的一个或多个实施方式或示例中以合适的方式结合。
流程图中或在此以其他方式描述的任何过程或方法描述可以被理解为，表示包括一个或更多个用于执行特定逻辑功能或过程的步骤的可执行指令的代码的模块、片段或部分，并且本发明的优选实施方式的范围包括另外的执行，其中可以不按所示出或讨论的顺序，包括根据所涉及的功能按基本同时的方式或按相反的顺序，来执行功能，这应被本发明的实施例所属技术领域的技术人员所理解。
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，可以被认为是用于执行逻辑功能的可执行指令的定序列表，可以具体执行在任何计算机可读介质中，以供指令执行***、装置或设备(如基于计算机的***、包括处理器的***或其他可以从指令执行***、装置或设备取指令并执行指令的***)使用，或结合这些指令执行***、装置或设备而 使用。就本说明书而言，"计算机可读介质"可以是任何可以包含、存储、通信、传播或传输程序以供指令执行***、装置或设备或结合这些指令执行***、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(RAM)，只读存储器(ROM)，可擦除可编辑只读存储器(EPROM或闪速存储器)，光纤装置，以及便携式光盘只读存储器(CDROM)。另外，计算机可读介质甚至可以是可在其上打印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执行。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***执行的软件或固件来执行。例如，如果用硬件来执行，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执行：具有用于对数据信号执行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(PGA)，现场可编程门阵列(FPGA)等。
本技术领域的普通技术人员可以理解执行上述实施方法携带的全部或部分步骤是可以通过程序来指令相关的硬件完成，的程序可以存储于一种计算机可读存储介质中，该程序在执行时，包括方法实施例的步骤之一或其组合。
此外，在本发明各个实施例中的各功能单元可以集成在一个处理模块中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个模块中。上述集成的模块既可以采用硬件的形式执行，也可以采用软件功能模块的形式执行。集成的模块如果以软件功能模块的形式执行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。
上述提到的存储介质可以是只读存储器，磁盘或光盘等。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 (25)

  1. 一种图像处理方法，用于成像装置中将色块图像转换成仿原图像，其特征在于，所述成像装置包括图像传感器，所述图像传感器包括感光像素单元阵列和设置在所述感光像素单元阵列上的滤光片单元阵列，每个所述滤光片单元阵列覆盖对应一个所述感光像素单元，每个所述感光像素单元包括多个感光像素，所述色块图像包括预定阵列排布的图像像素单元，所述图像像素单元包括多个原始像素，每个所述感光像素对应一个所述原始像素，所述图像处理方法包括以下步骤：
    将所述色块图像划分成多个亮度分析区域；
    计算每个所述亮度分析区域的亮度值；
    将所述亮度值符合条件的对应的所述亮度区域归并为高亮区域；
    将所述色块图像转换成仿原图像，所述仿原图像包括阵列排布的仿原像素，所述仿原像素包括当前像素，所述原始像素包括与所述当前像素对应的关联像素，所述色块图像包括所述高亮区域，所述将所述色块图像转换成所述仿原图像的步骤包括以下步骤：
    判断所述关联像素是否位于所述高亮区域内；
    在所述关联像素位于所述高亮区域内时判断所述当前像素的颜色与所述关联像素的颜色是否相同；
    在所述当前像素的颜色与所述关联像素的颜色相同时，将所述关联像素的像素值作为所述当前像素的像素值；
    在所述当前像素的颜色与所述关联像素的颜色不同时，根据关联像素单元的像素值通过第一插值算法计算所述当前像素的像素值，所述图像像素单元包括所述关联像素单元，所述关联像素单元的颜色与所述当前像素相同且与所述当前像素相邻；和
    在所述关联像素位于所述高亮区域外时，通过第二插值算法计算所述当前像素的像素值，所述第二插值算法的复杂度小于所述第一插值算法。
  2. 根据权利要求1所述的图像处理方法，其特征在于，所述亮度分析区域呈阵列排布。
  3. 根据权利要求1所述的图像处理方法，其特征在于，每个所述亮度分析区域包括一个或者多个所述原始像素。
  4. 根据权利要求1所述的图像处理方法，其特征在于，所述预定阵列包括拜耳阵列。
  5. 根据权利要求1所述的图像处理方法，其特征在于，所述图像像素单元包括2*2阵 列的所述原始像素。
  6. 根据权利要求1所述的图像处理方法，其特征在于，所述根据关联像素单元的像素值通过第一插值算法计算所述当前像素的像素值的步骤包括以下步骤：
    计算所述关联像素各个方向上的渐变量；
    计算所述关联像素各个方向上的权重；和
    根据所述渐变量及所述权重计算所述当前像素的像素值。
  7. 根据权利要求1所述的图像处理方法，其特征在于，所述图像处理方法在所述根据关联像素单元的像素值通过插值算法计算所述当前像素的像素值的步骤前包括以下步骤：
    对所述色块图像做白平衡补偿；
    所述图像处理方法在所述根据关联像素单元的像素值通过第一插值算法计算所述当前像素的像素值的步骤后包括以下步骤：
    对所述仿原图像做白平衡补偿还原。
  8. 根据权利要求1所述的图像处理方法，其特征在于，所述图像处理方法在所述根据关联像素单元的像素值通过插值算法计算所述当前像素的像素值的步骤前包括以下步骤：
    对所述色块图像做坏点补偿。
  9. 根据权利要求1所述的图像处理方法，其特征在于，所述图像处理方法在所述根据关联像素单元的像素值通过插值算法计算所述当前像素的像素值的步骤前包括以下步骤：
    对所述色块图像做串扰补偿。
  10. 根据权利要求1所述的图像处理方法，其特征在于，所述图像处理方法在所述根据关联像素单元的像素值通过第一插值算法计算所述当前像素的像素值的步骤后包括如下步骤：
    对所述仿原图像进行镜片形状校正、去马赛克、降噪和边缘锐化处理。
  11. 一种图像处理装置，用于成像装置中将色块图像转换成仿原图像，其特征在于，所述成像装置包括图像传感器，所述图像传感器包括感光像素单元阵列和设置在所述感光像素单元阵列上的滤光片单元阵列，每个所述滤光片单元阵列覆盖对应一个所述感光像素单元，每个所述感光像素单元包括多个感光像素，所述色块图像包括预定阵列排布的图像 像素单元，所述图像像素单元包括多个原始像素，每个所述感光像素对应一个所述原始像素，所述图像处理装置包括：
    划分模块，所述划分模块用于将所述色块图像划分成多个亮度分析区域；
    计算模块，所述计算模块用于计算每个亮度分析区域的亮度值；
    归并模块，所述归并模块用于将所述亮度值符合条件的对应的所述亮度区域归并为高亮区域；
    第一转换模块，所述第一转换模块用于将所述色块图像转换成仿原图像，所述仿原图像包括阵列排布的仿原像素，所述仿原像素包括当前像素，所述原始像素包括与所述当前像素对应的关联像素，所述色块图像包括所述高亮区域，所述第一转换模块包括：
    第一判断单元，所述第一判断单元用于判断所述关联像素是否位于所述高亮区域内；
    第二判断单元，所述第二判断单元用于在所述关联像素位于所述高亮区域内时判断所述当前像素的颜色与所述关联像素的颜色是否相同；
    第一计算单元，所述第一计算单元用于在所述当前像素的颜色与所述关联像素的颜色相同时，将所述关联像素的像素值作为所述当前像素的像素值；和
    第二计算单元，所述第二计算单元用于在所述当前像素的颜色与所述关联像素的颜色不同时，根据关联像素单元的像素值通过第一插值算法计算所述当前像素的像素值，所述图像像素单元包括所述关联像素单元，所述关联像素单元的颜色与所述当前像素相同且与所述当前像素相邻；和
    第三计算单元，所述第三计算单元用于在所述关联像素位于所述高亮区域外时，通过第二插值算法计算所述当前像素的像素值，所述第二插值算法的复杂度小于所述第一插值算法。
  12. 根据权利要求11所述的图像处理装置，其特征在于，所述亮度分析区域呈阵列排布。
  13. 根据权利要求11所述的图像处理装置，其特征在于，每个所述亮度分析区域包括一个或者多个所述原始像素。
  14. 根据权利要求11所述的图像处理装置，其特征在于，所述预定阵列包括拜耳阵列。
  15. 根据权利要求11所述的图像处理装置，其特征在于，所述图像像素单元包括2*2阵列的所述原始像素。
  16. 根据权利要求11所述的图像处理装置，其特征在于，所述第二计算单元包括：
    第一计算子单元，所述第一计算子单元用于计算所述关联像素各个方向上的渐变量；
    第二计算子单元，所述第二计算子单元用于计算所述关联像素各个方向上的权重；和
    第三计算子单元，所述第三计算子单元用于根据所述渐变量及所述权重计算所述当前像素的像素值。
  17. 根据权利要求11所述的图像处理装置，其特征在于，所述转换模块包括：
    白平衡补偿单元，所述白平衡补偿单元用于对所述色块图像做白平衡补偿；
    白平衡补偿还原单元，所述白平衡补偿还原单元用于对所述仿原图像做白平衡补偿还原。
  18. 根据权利要求11所述的图像处理装置，其特征在于，所述转换模块包括：
    坏点补偿单元，所述坏点补偿单元用于对所述色块图像做坏点补偿。
  19. 根据权利要求11所述的图像处理装置，其特征在于，所述转换模块包括：
    串扰补偿单元，所述串扰补偿单元用于对所述色块图像做串扰补偿。
  20. 根据权利要求11所述的图像处理装置，其特征在于，所述转换模块包括：
    处理单元，所述处理单元用于对所述仿原图像进行镜片形状校正、去马赛克、降噪和边缘锐化处理。
  21. 一种成像装置，其特征在于包括权利要求11-20任意一项所述的图像处理装置。
  22. 一种电子装置，其特征在于包括：
    权利要求21所述的成像装置；和
    触摸屏。
  23. 根据权利要求22所述的电子装置，其特征在于，所述电子装置包括手机或平板电脑。
  24. 根据权利要求22所述的电子装置，其特征在于，所述成像装置包括前置相机或后 置相机。
  25. 一种电子装置，包括壳体、处理器、存储器、电路板和电源电路，其特征在于，所述电路板安置在所述壳体围成的空间内部，所述处理器和所述存储器设置在所述电路板上；所述电源电路用于为所述电子装置的各个电路或器件供电；所述存储器用于存储可执行程序代码；所述处理器通过读取所述存储器中存储的可执行程序代码来运行与所述可执行程序代码对应的程序，以用于执行权利要求1至10中任意一项所述的图像处理方法。
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