CN107967668A - A kind of image processing method and device - Google Patents
A kind of image processing method and device Download PDFInfo
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- CN107967668A CN107967668A CN201610916025.5A CN201610916025A CN107967668A CN 107967668 A CN107967668 A CN 107967668A CN 201610916025 A CN201610916025 A CN 201610916025A CN 107967668 A CN107967668 A CN 107967668A
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- 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
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- 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
- G06T3/4023—Scaling of whole images or parts thereof, e.g. expanding or contracting based on decimating pixels or lines of pixels; based on inserting pixels or lines of pixels
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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
- G06T5/70—Denoising; Smoothing
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- 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
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
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- 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
- G06T2207/10—Image acquisition modality
- G06T2207/10048—Infrared image
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- 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
- G06T2207/20024—Filtering details
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- 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
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Abstract
The invention discloses a kind of image processing method and device, this method includes:RGBIR mosaic images are gathered using the imaging sensor of RGBIR forms;Demosaicing processing is carried out to RGBIR mosaic images, obtains the RGBIR images in full width face;The photobehavior of IR component values and imaging sensor in the RGBIR images in full width face carries out color recovery, eliminates the infrared optical information in R, G, B component image;White balance processing and colour correction processing are carried out to the image after infrared elimination;Image after colour correction is handled carries out colour space transformation, obtains YUV area images;The mosaic image in YUV domains is obtained to YUV area image down-samplings;Time domain noise reduction and spatial domain noise reduction process are carried out to YUV mosaic images;Interpolation calculation is carried out to the image after noise reduction, obtains the YUV image in full width face, processing of the RGBIR mosaic images to YUV image is realized by the present invention.
Description
Technical field
The present invention relates to technical field of image processing, more particularly to a kind of image processing method based on RGBIR forms
And device.
Background technology
RGBIR is a kind of new imaging sensor color filter arrangement mode, is different from the Bayer format of generally use
Color filter array (Color Filter Array, CFA), RGBIR filter arrays usually have two kinds of arrangement modes:It is a kind of
It is the pattern matrix formed with 2 × 2 colour filter arrangement mode, as shown in Figure 1, red channel (R), green channel (G), indigo plant
Chrominance channel (B), infrared channel (Infra Red, IR), have the image sampling rate of identical a quarter;Another kind be with 4 ×
The pattern matrix of 4 colour filter arrangement mode composition, as shown in Fig. 2, wherein, green channel G has the image of half
Sample rate, infrared channel IR have the image sampling rate of a quarter, and red channel R and blue channel B respectively have 1/8th
Image sampling rate, RGB channel can sense visible ray in RGBIR color filter lens arrays, can also sense sightless infrared light,
IR passages can also sense visible ray when sensing sightless infrared light.
Due to the difference of filter arrangement mode, and the difference of photosensitive mode so that the image based on RGBIR colour filters
The image processing system of sensor cannot directly continue to use image processing method and device based on Bayer colour filters, therefore, real
It is necessary to propose a kind of technological means, it is normal to obtain color to carry out image procossing to the view data based on RGBIR forms
For subsequent treatment, storage or the YUV image of display.
The content of the invention
To overcome above-mentioned the shortcomings of the prior art, the purpose of the present invention is to provide a kind of image processing method and dress
Put, the RGBIR mosaic images data of collection can be obtained color normally for follow-up by it by a series of image procossing
The YUV image of processing, storage or display.
In view of the above and other objects, the present invention proposes a kind of image processing method, include the following steps:
Step 1, RGBIR mosaic images are gathered using the imaging sensor of RGBIR forms;
Step 2, carries out demosaicing processing to the RGBIR mosaic images of acquisition, obtains the RGBIR images in full width face;
Step 3, the photosensitive spy of IR component values and imaging sensor in the RGBIR images in the full width face of acquisition
Property carry out color recovery, eliminate R, G, the infrared optical information in B component image;
Step 4, carries out the image after infrared elimination white balance processing and colour correction is handled;
Step 5, the image after colour correction is handled carry out colour space transformation, obtain YUV area images;
Step 6, the mosaic image in YUV domains is obtained to the YUV area image down-samplings of acquisition;
Step 7, time domain noise reduction and spatial domain noise reduction process are carried out to the YUV mosaic images of acquisition;
Step 8, carries out interpolation calculation to the YUV domains mosaic image after noise reduction, obtains the YUV image in full width face.
Further, in step 1,4 × 4 forms are gathered by the RGBIR imaging sensors of 4 × 4 filter arrangement modes
RGBIR mosaic images;Or 2 × 2 forms are gathered by the RGBIR imaging sensors of 2 × 2 filter arrangement modes
RGBIR mosaic images.
Further, in step 2, using the method for border reservation, first interpolation G passages obtain full width face G component maps
Picture, then using the difference of G passages and other passages, other channel values of interpolation, obtain R, G, B, IR component image in full width face.
Further, in step 3, after step 2 interpolation obtains R, G, B, IR component image in full width face, according to work as
Preceding pixel IR component values, and the photobehavior of imaging sensor, are calculated the ratio of IR components in current R, G, B component image
Example, and influencing each other between R, G, B component, eliminate the infrared optical information in R, G, B component image.
Further, in step 7, the spatial domain that retains into row bound the YUV domains mosaic image subchannel of acquisition
Noise reduction, and the time-domain noise reduction process that movement retains.
Further, in step 8, the interpolation that interpolation calculation is retained using border is carried out to YUV mosaic images and is calculated
Method.
To reach above-mentioned purpose, the present invention also provides a kind of image processing apparatus, including:
Image acquisition units, RGBIR mosaic images are gathered using the imaging sensor of RGBIR forms;
RGBIR image demosaicing units, for carrying out demosaicing processing to the RGBIR mosaic images of acquisition, obtain
To the RGBIR images in full width face;
Color recovery unit, for the IR component values and image sensing in the RGBIR images according to the full width face of acquisition
The photobehavior of device carries out color recovery, eliminates the infrared optical information in R, G, B component image;
Colors countenance unit, for carrying out white balance processing and colour correction processing to the image after infrared elimination;
Colour space transformation unit, carries out colour space transformation for the image after colour correction is handled, obtains YUV domains
Image;
Image down sampling unit, for obtaining the mosaic image in YUV domains to the YUV area image down-samplings of acquisition;
Image noise reduction unit, for carrying out time domain noise reduction and spatial domain noise reduction process to the YUV mosaic images of acquisition;
Image interpolation unit, for carrying out interpolation calculation to the YUV domains mosaic image after noise reduction, obtains full width face
YUV image.
Further, which uses the method that border retains, and first interpolation G passages obtain entirely
Breadth G component images, then using the difference of G passages and other passages, other channel values of interpolation, obtain the R, G in full width face, B,
IR component images.
Further, the color recovery unit is after R, G, B, IR component image in full width face is obtained, according to current pixel
IR component values, and the photobehavior of imaging sensor, are calculated the ratio of IR components in current R, G, B component image, and
R, influencing each other between G, B component, and then eliminate the infrared optical information in R, G, B component image.
Further, the sky which retains the YUV domains mosaic image subchannel of acquisition into row bound
Between domain noise reduction, and movement retain time-domain noise reduction process.
Compared with prior art, the present invention realizes a kind of method and device of the image procossing based on RGBIR forms, its
By the RGBIR mosaic images data of collection by a series of image procossing obtain color normally for subsequent treatment, deposit
Storage or the YUV image of display.
Brief description of the drawings
Fig. 1 is the prior art 2 × 2RGBIR picture format schematic diagrames;
Fig. 2 is the prior art 4 × 4RGBIR picture format schematic diagrames;
Fig. 3 is a kind of step flow chart of image processing method of the present invention;
Fig. 4 is YUV mosaic image schematic diagrames in the specific embodiment of the invention;
Fig. 5 is a kind of system architecture diagram of image processing apparatus of the present invention.
Embodiment
Below by way of specific instantiation and embodiments of the present invention are described with reference to the drawings, those skilled in the art can
Understand the further advantage and effect of the present invention easily by content disclosed in the present specification.The present invention can also pass through other differences
Instantiation implemented or applied, the various details in this specification also can be based on different viewpoints with application, without departing substantially from
Various modifications and change are carried out under the spirit of the present invention.
Using the imaging sensor of the color filter array of RGBIR, acquisition is a kind of mosaic image.It is follow-up necessary
The component color of missing is recovered from mosaic image by image processing techniques, obtains the RGBIR images in full width face.Due to
The RGB image in full width face contains sightless infrared light component, it is therefore necessary to recovers the true color of RGB using infrared channel IR
It is color.Since successive image processing full width face RGB image can cause the hardware of larger row caching hardware spending and frame buffer to be held
Pin, it is therefore desirable to the RGB image after color recovery is subjected to mosaic processing (down-sampled processing), then is carried out at successive image
Reason.
Fig. 3 is a kind of step flow chart of image processing method of the present invention.A kind of as shown in figure 3, image procossing of the present invention
Method, includes the following steps:
Step 301, RGBIR mosaic images are gathered using the imaging sensor of RGBIR forms.Specifically, by 4 ×
The RGBIR imaging sensors of 4 filter arrangement modes gather the RGBIR mosaic images of 4 × 4 forms;Or pass through 2 × 2 filters
The RGBIR imaging sensors of arrangement mode gather the RGBIR mosaic images of 2 × 2 forms.
Step 302, demosaicing processing is carried out to the RGBIR mosaic images of acquisition, obtains the RGBIR figures in full width face
Picture.In the specific embodiment of the invention, using 11 × 11 data window, the method retained using border, first interpolation G passages obtain
Full width face G component images;Then using the difference of G passages and other passages, other channel values of interpolation, obtain full width face R, G,
B, IR component images.
Step 303, according to the IR component values in the RGBIR images in the full width face of acquisition and the photosensitive spy of imaging sensor
Property carry out color recovery, eliminate R, G, the infrared optical information in B component image.Specifically, obtained when according to step 302 interpolation
After R, G, B, IR component image in full width face, according to current pixel IR component values, and the photobehavior of imaging sensor, it can count
Calculation obtains IR ratios in current R, G, B component image, and influencing each other between R, G, B component, utilizes color recovery calculation formula
The infrared optical information in R, G, B component image is eliminated, shown in the color recovery calculation formula such as following formula (1), wherein each parameter becomes
Amount has different value according to different RGBIR sensors.
Step 304, white balance processing is carried out to the image after infrared elimination and colour correction is handled.Of the invention specific
In embodiment, after infrared elimination is carried out to the RGBIR images in full width face according to step 303, to the image after infrared elimination into
The processing of row white balance, then the image again after dialogue Balance Treatment does colour correction processing so that color is closer to truly.
Step 305, the image after colour correction is handled carries out colour space transformation, obtains YUV area images.Specifically
Say, in step 305, carry out conversion of the RGB image to YUV color space images.
Step 306, the mosaic image in YUV domains is obtained to the YUV area image down-samplings of acquisition.It is embodied in the present invention
In example, the YUV mosaic images of 2 × 2 forms are obtained to YUV image down-sampling, as shown in figure 4, there are four kinds of sampling configurations, its
Middle Y-component has half sample rate, and U, V component have a quarter sample rate.
Step 307, time domain noise reduction and spatial domain noise reduction process are carried out to the YUV mosaic images of acquisition.Specifically, this step
Suddenly at the spatial domain noise reduction retained into row bound YUV domains mosaic image subchannel, and the time-domain noise reduction of movement reservation
Reason, to obtain higher subjective quality image.
Step 308, interpolation calculation is carried out to the YUV domains mosaic image after noise reduction, obtains the YUV image in full width face.
In the specific embodiment of the invention, interpolation calculation is carried out to YUV mosaic images, the interpolation retained using complex border is calculated
Method, obtains the YUV image in full width face.
Step 309, the YUV image in the full width face after output image interpolation, used for follow-up further image procossing or
Person does image storage processing or terminal is shown.
Fig. 5 is a kind of system architecture diagram of image processing apparatus of the present invention, as shown in figure 5, a kind of image procossing of the present invention
Device, including:At image acquisition units 501, RGBIR image demosaicings unit 502, color recovery unit 503, color
Manage unit 504, colour space transformation unit 505, image down sampling unit 506, image noise reduction unit 507, image interpolation unit
508 and image output unit 509.
Image acquisition units 501, RGBIR mosaic images are gathered using the imaging sensor of RGBIR forms.Specifically
Say, image acquisition units 301 gather the RGBIR horses of 4 × 4 forms by the RGBIR imaging sensors of 4 × 4 filter arrangement modes
Match gram image;Or the RGBIR mosaic figures for RGBIR imaging sensors 2 × 2 forms of collection for passing through 2 × 2 filter arrangement modes
Picture.
RGBIR image demosaicings unit 502, for carrying out demosaicing processing to the RGBIR mosaic images of acquisition,
Obtain the RGBIR images in full width face.In the specific embodiment of the invention, RGBIR image demosaicings unit 502 uses 11 × 11
Data window, the method retained using border, first interpolation G passages obtain full width face G component images;Then G passages and its are utilized
The difference of his passage, other channel values of interpolation, obtain R, G, B, IR component image in full width face.
Color recovery unit 503, passes for the IR component values in the RGBIR images according to the full width face of acquisition and image
The photobehavior of sensor carries out color recovery, eliminates the infrared optical information in R, G, B component image.Specifically, when RGBIR schemes
After obtaining R, G, B, IR component image in full width face as 502 interpolation of demosaicing unit, color recovery unit 503 is then according to current
Pixel IR component values, and the photobehavior of imaging sensor, obtain IR ratios in current R, G, B component image, and R, G, B points
Influencing each other between amount, the infrared optical information in R, G, B component image, the color recovery are eliminated using color recovery calculation formula
Calculation formula is as follows, wherein each parametric variable has different value according to different RGBIR sensors.
Colors countenance unit 504, for carrying out white balance processing and colour correction processing to the image after infrared elimination.
In the specific embodiment of the invention, after color recovery unit 503 carries out infrared elimination to the RGBIR images in full width face, color
Processing unit 504 carries out white balance processing to the image after infrared elimination, and then the image again after dialogue Balance Treatment does color
Correction process so that color is closer to truly.
Colour space transformation unit 505, carries out colour space transformation for the image after colour correction is handled, obtains
YUV area images.Specifically, the image after colour space transformation unit 505 handles colour correction carries out RGB image to YUV
The conversion of color space image.
Image down sampling unit 506, for obtaining the mosaic image in YUV domains to the YUV area image down-samplings of acquisition.
In the specific embodiment of the invention, image down sampling unit 506 obtains YUV image down-sampling in the YUV mosaic figures of 2 × 2 forms
Picture, has four kinds of sampling configurations, and wherein Y-component has half sample rate, and U, V component have a quarter sample rate.
Image noise reduction unit 507, for carrying out time domain noise reduction and spatial domain noise reduction process to the YUV mosaic images of acquisition.
Specifically, the spatial domain noise reduction that image noise reduction unit 507 retains YUV domains mosaic image subchannel into row bound, and
The time-domain noise reduction process retained is moved, to obtain higher subjective quality image.
Image interpolation unit 508, for carrying out interpolation calculation to the YUV domains mosaic image after noise reduction, obtains full width face
YUV image.In the specific embodiment of the invention, image interpolation unit 508 carries out interpolation calculation to YUV mosaic images, adopts
The interpolation algorithm retained with complex border, obtains the YUV image in full width face.
Image output unit 509, the YUV image in the full width face after output image interpolation, at follow-up further image
Reason uses or does image storage processing or terminal is shown.
The above-described embodiments merely illustrate the principles and effects of the present invention, not for the limitation present invention.Any
Field technology personnel can modify above-described embodiment and changed under the spirit and scope without prejudice to the present invention.Therefore,
The scope of the present invention, should be as listed by claims.
Claims (10)
1. a kind of image processing method, includes the following steps:
Step 1, RGBIR mosaic images are gathered using the imaging sensor of RGBIR forms;
Step 2, carries out demosaicing processing to the RGBIR mosaic images of acquisition, obtains the RGBIR images in full width face;
Step 3, the photobehavior of IR component values and imaging sensor in the RGBIR images in the full width face of acquisition into
Row color recovery, eliminates the infrared optical information in R, G, B component image;
Step 4, carries out the image after infrared elimination white balance processing and colour correction is handled;
Step 5, the image after colour correction is handled carry out colour space transformation, obtain YUV area images;
Step 6, the mosaic image in YUV domains is obtained to the YUV area image down-samplings of acquisition;
Step 7, time domain noise reduction and spatial domain noise reduction process are carried out to the YUV mosaic images of acquisition;
Step 8, carries out interpolation calculation to the YUV domains mosaic image after noise reduction, obtains the YUV image in full width face.
A kind of 2. image processing method as claimed in claim 1, it is characterised in that:In step 1, arranged by 4 × 4 filters
The RGBIR imaging sensors of row mode gather the RGBIR mosaic images of 4 × 4 forms;Or pass through 2 × 2 filter arrangement modes
RGBIR imaging sensors gather 2 × 2 forms RGBIR mosaic images.
A kind of 3. image processing method as claimed in claim 1, it is characterised in that:In step 2, retained using border
Method, first interpolation G passages obtain full width face G component images, and then using the difference of G passages and other passages, other are logical for interpolation
Road value, obtains R, G, B, IR component image in full width face.
4. a kind of image processing method as claimed in claim 3, it is characterised in that in step 3, obtained in step 2 interpolation
To after R, G, B, IR component image in full width face, according to current pixel IR component values, and the photobehavior of imaging sensor, meter
Calculation obtains the ratio of IR components in current R, G, B component image, and influencing each other between R, G, B component, and then eliminates R, G, B points
Infrared optical information in spirogram picture.
A kind of 5. image processing method as claimed in claim 1, it is characterised in that:In step 7, to the YUV domains horse of acquisition
The spatial domain noise reduction that match gram image subchannel retains into row bound, and the time-domain noise reduction process that movement retains.
A kind of 6. image processing method as claimed in claim 1, it is characterised in that:In step 8, to YUV mosaic images
Carry out the interpolation algorithm that interpolation calculation uses border to retain.
7. a kind of image processing apparatus, including:
Image acquisition units, RGBIR mosaic images are gathered using the imaging sensor of RGBIR forms;
RGBIR image demosaicing units, for carrying out demosaicing processing to the RGBIR mosaic images of acquisition, obtain complete
The RGBIR images of breadth;
Color recovery unit, for the IR component values in the RGBIR images according to the full width face of acquisition and imaging sensor
Photobehavior carries out color recovery, eliminates the infrared optical information in R, G, B component image;
Colors countenance unit, for carrying out white balance processing and colour correction processing to the image after infrared elimination;
Colour space transformation unit, carries out colour space transformation for the image after colour correction is handled, obtains YUV domains figure
Picture;
Image down sampling unit, for obtaining the mosaic image in YUV domains to the YUV area image down-samplings of acquisition;
Image noise reduction unit, for carrying out time domain noise reduction and spatial domain noise reduction process to the YUV mosaic images of acquisition;
Image interpolation unit, for carrying out interpolation calculation to the YUV domains mosaic image after noise reduction, obtains the YUV figures in full width face
Picture.
A kind of 8. image processing apparatus as claimed in claim 7, it is characterised in that:The RGBIR image demosaicing units are adopted
The method retained with border, first interpolation G passages obtain full width face G component images, then utilize the difference of G passages and other passages
Value, other channel values of interpolation, obtain R, G, B, IR component image in full width face.
9. a kind of image processing apparatus as claimed in claim 7, it is characterised in that the color recovery unit is in obtaining full width face
R, G, B, IR component image after, according to current pixel IR component values, and the photobehavior of imaging sensor, be calculated and work as
The ratio of IR components in preceding R, G, B component image, and influencing each other between R, G, B component, and then eliminate in R, G, B component image
Infrared optical information.
A kind of 10. image processing method as claimed in claim 7, it is characterised in that:YUV of the image noise reduction unit to acquisition
The spatial domain noise reduction that domain mosaic image subchannel retains into row bound, and the time-domain noise reduction process that movement retains.
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Cited By (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110290370A (en) * | 2019-07-05 | 2019-09-27 | 上海富瀚微电子股份有限公司 | Image processing method and device |
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CN113781326A (en) * | 2021-08-11 | 2021-12-10 | 北京旷视科技有限公司 | Demosaicing method and device, electronic equipment and storage medium |
CN114095672A (en) * | 2020-07-31 | 2022-02-25 | 北京小米移动软件有限公司 | Imaging system, method and electronic device |
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102663719A (en) * | 2012-03-19 | 2012-09-12 | 西安电子科技大学 | Bayer-pattern CFA image demosaicking method based on non-local mean |
CN103686111A (en) * | 2013-12-31 | 2014-03-26 | 上海富瀚微电子有限公司 | Method and device for correcting color based on RGBIR (red, green and blue, infra red) image sensor |
CN103685858A (en) * | 2012-08-31 | 2014-03-26 | 北京三星通信技术研究有限公司 | Real-time video processing method and equipment |
CN104539919A (en) * | 2014-12-31 | 2015-04-22 | 上海富瀚微电子股份有限公司 | Demosaicing method and device of image sensor |
US20160165202A1 (en) * | 2014-12-04 | 2016-06-09 | Samsung Electronics Co., Ltd. | Method and apparatus for controlling white balance |
-
2016
- 2016-10-20 CN CN201610916025.5A patent/CN107967668B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102663719A (en) * | 2012-03-19 | 2012-09-12 | 西安电子科技大学 | Bayer-pattern CFA image demosaicking method based on non-local mean |
CN103685858A (en) * | 2012-08-31 | 2014-03-26 | 北京三星通信技术研究有限公司 | Real-time video processing method and equipment |
CN103686111A (en) * | 2013-12-31 | 2014-03-26 | 上海富瀚微电子有限公司 | Method and device for correcting color based on RGBIR (red, green and blue, infra red) image sensor |
US20160165202A1 (en) * | 2014-12-04 | 2016-06-09 | Samsung Electronics Co., Ltd. | Method and apparatus for controlling white balance |
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