CN106651815A - Method and device for processing Bayer-formatted video images - Google Patents
Method and device for processing Bayer-formatted video images Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 109
- 238000012545 processing Methods 0.000 title claims abstract description 40
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 125
- 238000007781 pre-processing Methods 0.000 claims abstract description 3
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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
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- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/10—Cameras or camera modules comprising electronic image sensors; Control thereof for generating image signals from different wavelengths
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- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
- H04N25/50—Control of the SSIS exposure
- H04N25/57—Control of the dynamic range
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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
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30232—Surveillance
Abstract
The application discloses a method and device for processing Bayer-formatted video images. The method comprises the following steps: preprocessing an input Bayer-formatted video image to generate pre-processed data; processing the pre-processed data to generate high-light data and low-light data; processing the high-light data and the low-light data by utilizing a spatial domain variation algorithm to generate algorithm data; and outputting a video image according to the algorithm data. According to the method and device for processing the Bayer-formatted video images, an original image can be restored better, and the requirement of a real-time and wide-dynamic video monitoring system is met.
Description
Technical field
The present invention relates to computer vision field, in particular to a kind of for processing Bayer format video image
Method and device.
Background technology
Due to the lifting of security protection demand in industry-by-industry and people's life, the various instrument and equipments for monitoring are constantly pushed away
It is old go out it is new, and spread all over each corner of our lives gradually.In these monitor modes, Video Supervision Technique, so that it is directly perceived, can
It is used widely by, the advantage that contains much information, such as：Traffic, electric power, shop, department store, operating room, finance, government bodies
Public institution's window, and the key departments such as army, public security, prison, Aero-Space.Along with digital image processing techniques and micro- electricity
The progress of sub- technology, acquisition, process, transmission and the analysis of digital picture become more convenient and quick, and monitoring system is also from mould
Intend to digital gradually transition.
The dynamic rage extension method of digital imaging system has the approach of various realizations, and two classes can be mainly classified as at present,
That is software extensions method and hard ware extension method.Dynamic Range is extended from hardware there is very high technical difficulty, also
Scheme without mature and reliable.And the method needs to transform camera or imageing sensor, or even redesign,
Great effort is taken on hardware device, manufacturing cost is also greatly improved.The main thought of software extensions method is that scene is entered
Row multiexposure, multiple exposure is imaged, and by arranging the different time for exposure, changes the brightness range of system detection, obtains several difference exposures
The image of degree, then they are synthesized by a secondary high dynamic range images, the detailed information of restoration scenario by software approach.The method
It is disadvantageous in that needs, by shooting several scene pictures, need to be processed multiple image, does not meet video monitoring
Requirement of real-time.The improved method that most high dynamic is processed is all based on what RGB image was carried out, due to the data for processing it is total
Amount is not changed in, and operation efficiency lifting is limited, and hardware resource consumption is big, it is difficult to carry out embedded development.
Accordingly, it would be desirable to a kind of new method and device for processing Bayer format video image.
Above- mentioned information is only used for strengthening the understanding of the background to the present invention, therefore it disclosed in the background section
Can include not constituting the information to prior art known to persons of ordinary skill in the art.
The content of the invention
In view of this, the present invention provides a kind of method and device for processing Bayer format video image, can be preferable
Reduction original image, while meeting the requirement of the dynamic video monitoring system of real-time width.
Other characteristics and advantage of the present invention will be apparent from by detailed description below, or partially by the present invention
Practice and acquistion.
According to an aspect of the invention, it is proposed that a kind of method for processing Bayer format video image, the method bag
Include：The video image of the Bayer format to being input into is pre-processed, and generates preprocessed data；Preprocessed data is processed,
High light data is generated with low light data；Using the high light data of spatial domain change algorithm process and low light data, generating algorithm data；With
And by algorithm data output video image.
In a kind of exemplary embodiment of the disclosure, the video image of the Bayer format to being input into is pre-processed, raw
Into preprocessed data, including：The video image of the Bayer format to being input into carries out linear space filtering, generates filtering data；With
And correction is filtered to filtering data, generate preprocessed data.
In a kind of exemplary embodiment of the disclosure, preprocessed data is processed, generate high light data and low light
Data, including：By the gray value of video image, preprocessed data is divided into high light data with low light data.
In a kind of exemplary embodiment of the disclosure, using the high light data of spatial domain change algorithm process and low light data,
Generating algorithm data, including：By the high light data of spatial domain change algorithm process, bloom algorithm data is generated；Changed by spatial domain
The low light data of algorithm process, generates low smooth algorithm data；By bloom algorithm data and low smooth algorithm data, generating algorithm number
According to.
In a kind of exemplary embodiment of the disclosure, by the low light data of spatial domain change algorithm process, generate low light and calculate
Method data, including：Part algorithmic formula is compensated by low light and processes low light data, generate low smooth algorithm data；
Low light compensates part algorithmic formula, including：
Wherein, Y2For low smooth algorithm data, k is low smooth compensating parameter, and I is the pixel value of the video image of input, Y1For defeated
The correction value of the video image for entering.
In a kind of exemplary embodiment of the disclosure, by the high light data of spatial domain change algorithm process, generate bloom and calculate
Method data, including：Part algorithmic formula is compensated by bloom and processes high light data, generate bloom algorithm data；
Bloom compensates part algorithmic formula, including：
Wherein, Y3For bloom algorithm data, α is bloom compensating parameter, and I is the pixel value of the video image of input, Y1For defeated
The correction value of the video image for entering, Max a are the pixel maximum of the video image of input.
In a kind of exemplary embodiment of the disclosure, bloom compensating parameter scope is 0.7-1.
In a kind of exemplary embodiment of the disclosure, by bloom algorithm data and low smooth algorithm data, generating algorithm
Data, including equation below：
Y=Y2+Y3
Wherein, Y is algorithm data, Y2For low smooth algorithm data, Y3For bloom algorithm data.
It is wide dynamic images by algorithm data output video image in a kind of exemplary embodiment of the disclosure.
According to an aspect of the invention, it is proposed that a kind of device for processing Bayer format video image, the device bag
Include：Pretreatment module, for pre-processing to the video image of the Bayer format being input into, generates preprocessed data；Data mould
Block, for processing preprocessed data, generates high light data and low light data；Algoritic module, for being changed using spatial domain
The high light data of algorithm process and low light data, generating algorithm data；And output module, for exporting video by algorithm data
Image.
Method and device for processing Bayer format video image of the invention, can preferably reduce original
Image, while meeting the requirement of the dynamic video monitoring system of real-time width.
It should be appreciated that the general description of the above and detailed description hereinafter are only exemplary, this can not be limited
Invention.
Description of the drawings
Its example embodiment is described in detail by referring to accompanying drawing, above and other target of the present invention, feature and advantage will
Become more fully apparent.Drawings discussed below is only some embodiments of the present invention, for the ordinary skill of this area
For personnel, on the premise of not paying creative work, can be with according to these other accompanying drawings of accompanying drawings acquisition.
Fig. 1 is a kind of stream for processing the method for Bayer format video image according to an exemplary embodiment
Cheng Tu.
Fig. 2 is filtered in a kind of method for processing Bayer format video image according to an exemplary embodiment
Ripple algorithm principle figure.
Fig. 3 is at a kind of method for processing Bayer format video image exemplified according to another exemplary enforcement
Comparison diagram before and after reason.
Fig. 4 is at a kind of method for processing Bayer format video image exemplified according to another exemplary enforcement
Comparison diagram before and after reason.
Fig. 5 is at a kind of method for processing Bayer format video image exemplified according to another exemplary enforcement
Comparison diagram before and after reason.
Fig. 6 is a kind of method for processing Bayer format video image exemplified according to another exemplary enforcement
Flow chart.
Fig. 7 is a kind of frame for processing the device of Bayer format video image according to an exemplary embodiment
Figure.
Specific embodiment
Example embodiment is described more fully with referring now to accompanying drawing.However, example embodiment can be real in a variety of forms
Apply, and be not understood as limited to embodiment set forth herein；Conversely, thesing embodiments are provided so that the present invention will be comprehensively and complete
It is whole, and the design of example embodiment is comprehensively conveyed into those skilled in the art.Identical reference is represented in figure
Same or similar part, thus repetition thereof will be omitted.
Additionally, described feature, structure or characteristic can be combined in one or more enforcements in any suitable manner
In example.In the following description, there is provided many details fully understand so as to be given to embodiments of the invention.However,
It will be appreciated by persons skilled in the art that it is one or more during technical scheme can be put into practice without specific detail,
Or can be using other methods, constituent element, device, step etc..In other cases, it is not shown in detail or describes known side
Method, device, realization operate to avoid fuzzy each aspect of the present invention.
Block diagram shown in accompanying drawing is only functional entity, not necessarily must be corresponding with physically separate entity.
I.e., it is possible to realize these functional entitys using software form, or realize in one or more hardware modules or integrated circuit
These functional entitys, or these functional entitys are realized in heterogeneous networks and/or processor device and/or microcontroller device.
Flow chart shown in accompanying drawing is merely illustrative, it is not necessary to including all of content and operation/step,
It is not required to be performed by described order.For example, some operation/steps can also decompose, and some operation/steps can be closed
And or part merge, therefore the actual order for performing is possible to be changed according to actual conditions.
It should be understood that although herein various assemblies may be described using term first, second, third, etc., these groups
Part should not be limited by these terms.These terms are to distinguish a component with another component.Therefore, first group for being discussed herein below
Part can be described as teaching of second component without departing from disclosure concept.As used herein, term " and/or " include it is associated
The all combinations for listing any one and one or more in project.
It will be understood by those skilled in the art that accompanying drawing is the schematic diagram of example embodiment, the module or flow process in accompanying drawing
Not necessarily implement the present invention necessary, therefore cannot be used for limiting the scope of the invention.
Fig. 1 is a kind of stream for processing the method for Bayer format video image according to an exemplary embodiment
Cheng Tu.
As shown in figure 1, in S102, the video image of the Bayer format to being input into is pre-processed, pretreatment number is generated
According to.For coloured image, the various most basic colors of collection, such as tri- kinds of colors of R, G, B are needed, simplest method is exactly with filter
The method of mirror, through red wavelength, the filter of green passes through the wavelength of green to red filter, and blue filter is through blue
Wavelength.If gathering tri- Essential colour of R, G, B, three pieces of filters are needed, it is so expensive, and bad manufacture, because
Three pieces of filters all must assure that each pixel aligns.The different face that bayer format pictures are arranged on one piece of filter
Color, finds that human eye is more sensitive to green, so the picture of general bayer forms is green by analyzing perception of the human eye to color
The pixel of color form be R and G pixels and.The video image of the Bayer format to being input into carries out pretreatment can for example, to defeated
The video image of the Bayer format for entering carries out linear space filtering, also for example can be filtered correction to filtered data.
In S104, preprocessed data is processed, generate high light data and low light data.In example in real time of the invention
In, in order to preferably process image, preprocessed data is divided into high light data and is subsequently located respectively with low light data
Reason.For example preprocessed data can be divided into by bloom number according to the weighted average and a predetermined threshold value of pixel in input picture
According to low light data, can also for example, by the gray values of each pixel in image and another predetermined value by preprocessed data
It is divided into high light data with low light data.The present invention is not limited.
In S106, using the high light data of spatial domain change algorithm process and low light data, generating algorithm data.Spatial domain changes
Algorithm belongs to the one kind in tone-mapping algorithm, and tone mapping is the approximate display high dynamic range on limited dynamic range medium
Enclose a computer graphics techniques of image.Print result, CRT or LCD display and projecting apparatus etc. are all only limited
Dynamic range.Essentially, tone mapping be the problem to be solved be carry out significantly contrast decay scene is bright
Degree transforms to the scope that can be shown, while to keep image detail and color etc. for the very important letter of performance original scene
Breath.Tone-mapping algorithm has many kinds, the image of the six width difference depth of exposure for generating front piece image having.Also one
It is the method based on contrast or gradient field to plant algorithm, and the emphasis of these algorithms is the holding rather than brightness of contrast
Mapping, the mapping of this tone is due to preferably saving contrast detail, so very sharp keen image would generally be produced, but
It is that the cost of do so is so that overall picture contrast becomes gentle.In embodiments of the present invention, calculated by spatial domain change
Method processes respectively high light data and low light data, generating algorithm data.
In S108, by algorithm data output video image.Can for example, by data processing algorithm of the prior art
The algorithm data is carried out into data preparation output.Wherein, it is wide dynamic images by algorithm data output video image.
Method for processing Bayer format video image of the invention, by the way that view data is divided into bloom number
According to low light data, and process the mode of high light data and low light data respectively using spatial domain change algorithm, can be preferable
Reduction original image, while meeting the requirement of the dynamic video monitoring system of real-time width.
It will be clearly understood that the present disclosure describe how being formed and using particular example, but the principle of the present invention to be not limited to
Any details of these examples.Conversely, the teaching based on present disclosure, these principles can be applied to many other
Embodiment.
In a kind of exemplary embodiment of the disclosure, the video image of the Bayer format to being input into is pre-processed, raw
Into preprocessed data, including：The video image of the Bayer format to being input into carries out linear space filtering, generates filtering data；With
And correction is filtered to filtering data, generate preprocessed data.
The realistic meaning of linear space filtering is improvement image quality, including removes high-frequency noise and interference, and image side
Along enhancing, linear enhancing and deblurring.Linear space is filtered, and is to define respective filter size, and neighborhood territory pixel is carried out
Linear operation, the response of output carries out the value after linear operation for the pixel in wave filter.Linear space is filtered, from essence
It is the convolution or related operation of two matrixes for upper：By respective filter, (or referred to as mask, actual is also one
Two-dimensional matrix) carry out convolution or related operation realization with image array.
Its algorithm is expressed as：
Y1=Imfilter (I, GH, ' conv ')+Mean β
Can be with formulae express：
Y1=I*GH+Mean β
Wherein, Y1For the correction value of the video image of input, Imfilter is linear space filter function, and I is input
The pixel value of video image, it is notable that what is be input into herein is the RGB that the data form without the need for processing is 12bit
Bayer type images, therefore arithmetic speed is greatly improved, and do not affect whole structure.In addition, GH is filtering matrix,
Conv is convolution algorithm (convolution algorithm of input pixel value I and filtering matrix GH), and Mean is the mean value of whole two field picture, and β is
Adjust mean value (adjust mean value needs to be manually set according to system).
Method for processing Bayer format video image of the invention, it is pre- by carrying out to Bayer view data
The mode of process, can reduce the noise of inputted video image.
Fig. 2 is filtered in a kind of method for processing Bayer format video image according to an exemplary embodiment
Ripple algorithm principle figure.Filtering algorithm principle is as shown in Figure 2.Can for example, H is the filtering mask of a 5*5, and weighted average rotates
Symmetrically, it is bigger the closer to center weights.In the present embodiment, original image takes one respectively with each pixel as core
The matrix of individual 5*5, after the weight coefficient weighting corresponding with H-matrix of the pixel value in array, then divided by weight coefficient and 256.Such as
Fruit center pixel is on border or closes on border, then replicate border, supplies the matrix of 5*5.
Filtering and calibration is the product (Mean β) for adjusting mean value and the mean value of whole two field picture.
In a kind of exemplary embodiment of the disclosure, preprocessed data is processed, generate high light data and low light
Data, including：By the gray value of video image, preprocessed data is divided into high light data with low light data.
In a kind of exemplary embodiment of the disclosure, by the high light data of spatial domain change algorithm process and low light data,
Generating algorithm data, including：By the high light data of spatial domain change algorithm process, bloom algorithm data is generated；Changed by spatial domain
The low light data of algorithm process, generates low smooth algorithm data；By bloom algorithm data and low smooth algorithm data, generating algorithm number
According to.
Method for processing Bayer format video image of the invention, by spatial domain change algorithm Bayer is processed
View data, is obtained in that preferable effect, high to the reduction degree of image, meets the requirement of real-time of video monitoring system.
Tone mapping method can be divided into Global Algorithm (the constant algorithm in spatial domain) and local algorithm (spatial domain change algorithm) two
Kind.In Global Algorithm, the process to image each pixel is unrelated with the value of its locus and surrounding pixel, and all pixels are same
One mapping function is processed.
Because the mapping curve that the constant algorithm in spatial domain needs has uniformity, consistency and stationarity, so its calculating
Simple and fast, easily realizes, algorithm complex during mapping is relatively low, but simple mapping must will affect last effect,
The minutia in image is caused to be likely to lose, and therefore the information such as contrast of local also will receive shadow in original image
Ring.
Spatial domain change algorithm is then different.It is contrasted with the constant algorithm in spatial domain, this kind of algorithm is concerned with current picture
Relation between vegetarian refreshments and its surrounding pixel point, pixel once changes, and therefore corresponding mapping relations also will occur
Change.
In a kind of exemplary embodiment of the disclosure, by the low light data of spatial domain change algorithm process, generate low light and calculate
Method data, including：Part algorithmic formula is compensated by low light and processes low light data, generate low smooth algorithm data.
In a kind of exemplary embodiment of the disclosure, low light compensates part algorithmic formula, including：
Wherein, Y2For low smooth algorithm data, k is low smooth compensating parameter, and I is the pixel value of the video image of input, Y1For defeated
The correction value of the video image for entering.
In a kind of exemplary embodiment of the disclosure, by the high light data of spatial domain change algorithm process, generate bloom and calculate
Method data, including：Part algorithmic formula is compensated by bloom and processes high light data, generate bloom algorithm data.
In a kind of exemplary embodiment of the disclosure, bloom compensation part algorithmic formula, including：
Wherein, Y3For bloom algorithm data, α is bloom compensating parameter, and I is the pixel value of the video image of input, Y1For defeated
The correction value of the video image for entering, Max a are the pixel maximum of the video image of input.
In a kind of exemplary embodiment of the disclosure, bloom compensating parameter scope is 0.7-1.
In a kind of exemplary embodiment of the disclosure, by bloom algorithm data and low smooth algorithm data, generating algorithm
Data, including equation below：
Y=Y2+Y3
As：
Wherein, Y is algorithm data, Y2For low smooth algorithm data, Y3For bloom algorithm data.
Fig. 3,4,5 are a kind of sides for processing Bayer format video image exemplified according to another exemplary enforcement
Comparison diagram after method before processing.From in figure, the method in the embodiment of the present invention effectively improves the dynamic range of image, figure
The chrominance information of picture also keeps good, strengthens obvious to image detail.At the same time, mode step proposed by the present invention is simple,
Robustness is good, and real-time also can be met.
Fig. 6 is a kind of method for processing Bayer format video image exemplified according to another exemplary enforcement
Flow chart.
As shown in fig. 6, S602, the input of Bayer format video image.
S604, to input picture linear space filtering is carried out.
S606, to filtered image correction is filtered.
S608, enters line width dynamic to the video image after filtering and processes based on improved tone reflection method
Wide dynamic images after S610 outputs process.
Wherein, the linear space filtering in S604 is the pretreatment of video image, in order to reduce making an uproar for inputted video image
Sound.And the special arrangement mode of Bayer images, the hardware resource of system is effectively reduced, in embodiments of the present invention, by width
Dynamic algorithm is applied to Bayer format video image, and handled data fundamentally reduce 2/3 compared with other algorithms, are not dropping
On the premise of low video image effect, the amount of calculation of wide dynamic algorithm is largely reduced, improve efficiency of algorithm.
It will be appreciated by those skilled in the art that realizing that all or part of step of above-described embodiment is implemented as being performed by CPU
Computer program.When the computer program is performed by CPU, the above-mentioned work(that the said method of present invention offer is limited is performed
Energy.Described program can be stored in a kind of computer-readable recording medium, and the storage medium can be read-only storage, magnetic
Disk or CD etc..
Further, it should be noted that above-mentioned accompanying drawing is only the place included by method according to an exemplary embodiment of the present invention
That what is managed schematically illustrates, rather than limits purpose.It can be readily appreciated that above-mentioned process shown in the drawings is not intended that or limits at these
The time sequencing of reason.In addition, being also easy to understand, these process for example can be performed either synchronously or asynchronously in multiple modules.
It is following for apparatus of the present invention embodiment, can be used for performing the inventive method embodiment.For apparatus of the present invention reality
The details not disclosed in example is applied, the inventive method embodiment is refer to.
Fig. 7 is a kind of frame for processing the device of Bayer format video image according to an exemplary embodiment
Figure.
Pretreatment module 702 is used for the video image of the Bayer format to being input into and pre-processes, and generates pretreatment number
According to.
Data module 704 is used for by pre-defined rule and preprocessed data, generates high light data and low light data.
Algoritic module 706 is used to process high light data and low light data, generating algorithm data by spatial domain change algorithm.
Output module 708 is used to pass through algorithm data output video image.
In a kind of exemplary embodiment of the disclosure, pretreatment module, including：Filtering submodule, for input
The video image of Bayer format carries out linear space filtering, generates filtering data；And correction module, for filtering number
According to correction is filtered, preprocessed data is generated.
In a kind of exemplary embodiment of the disclosure, algoritic module, including：High photonic module, for being become by spatial domain
Change the high light data of algorithm process, generate bloom algorithm data；And low photonic module, for processing low by spatial domain change algorithm
Light data, generates low smooth algorithm data.
Device in the embodiment of the present invention can for example be embedded in FPGA realizations, apply to real-time HDR camera
Or in video camera.
It will be appreciated by those skilled in the art that above-mentioned each module can be distributed in device according to the description of embodiment, also may be used
In to carry out one or more devices of respective change uniquely different from the present embodiment.The module of above-described embodiment can be merged into
One module, it is also possible to be further split into multiple submodule.
The description of the embodiment by more than, those skilled in the art is it can be readily appreciated that example embodiment described herein
Can be realized by software, it is also possible to realize by way of software is with reference to necessary hardware.Therefore, according to present invention enforcement
The technical scheme of example can be embodied in the form of software product, and the software product can be stored in a non-volatile memories
In medium (can be CD-ROM, USB flash disk, portable hard drive etc.) or on network, including some instructions are so that a computing device (can
Being personal computer, server, mobile terminal or network equipment etc.) perform method according to embodiments of the present invention.
Detailed description by more than, those skilled in the art is it can be readily appreciated that according to embodiments of the present invention for locating
The method and device of reason Bayer format video image has one or more of the following advantages.
According to some embodiments, the method for processing Bayer format video image of the present invention, by by view data
It is divided into high light data and low light data, and the mode of high light data and low light data is processed respectively using spatial domain change algorithm,
Original image can be preferably reduced, while meeting the requirement of the dynamic video monitoring system of real-time width.
According to other embodiments, the method for processing Bayer format video image of the present invention, by Bayer
The mode that view data is pre-processed, can reduce the noise of inputted video image.
According to still other embodiments, the method for processing Bayer format video image of the present invention, changed by spatial domain
Algorithm process Bayer view data, is obtained in that preferable effect, high to the reduction degree of image, meets video monitoring system
Requirement of real-time.
More than it is particularly shown and described the exemplary embodiment of the present invention.It should be appreciated that the invention is not restricted to
Detailed construction described herein, set-up mode or implementation method；On the contrary, it is intended to cover be included in claims
Various modifications and equivalence setting in spirit and scope.
Additionally, structure, ratio, size shown by this specification Figure of description etc., only to coordinate specification institute
Disclosure, for skilled in the art realises that with reading, be not limited to the enforceable qualifications of the disclosure, therefore
Do not have technical essential meaning, the modification of any structure, the change of proportionate relationship or the adjustment of size are not affecting the disclosure
Under the technique effect that can be generated and achieved purpose, all should still fall obtain and can cover in the technology contents disclosed in the disclosure
In the range of.Meanwhile, in this specification it is cited such as " on ", " first ", the term of " second " and " ", be also only and be easy to
Narration understands, and be not used to limit the disclosure enforceable scope, and its relativeness is altered or modified, without substantive change
Under technology contents, when being also considered as enforceable category of the invention.
Claims (10)
1. a kind of method for processing Bayer format video image, it is characterised in that include：
The video image of the Bayer format to being input into is pre-processed, and generates preprocessed data；
The preprocessed data is processed, high light data and low light data is generated；
Using the spatial domain change algorithm process high light data and the low light data, generating algorithm data；And
By the algorithm data output video image.
2. the method for claim 1, it is characterised in that the video image of the Bayer format of described pair of input carries out pre-
Process, generate preprocessed data, including：
The video image of the Bayer format to being input into carries out linear space filtering, generates filtering data；And
Correction is filtered to the filtering data, the preprocessed data is generated.
3. the method for claim 1, it is characterised in that described to process the preprocessed data, generates bloom
Data and low light data, including：
By the gray value of the video image, the preprocessed data is divided into the high light data with the low light data.
4. the method for claim 1, it is characterised in that the utilization spatial domain change algorithm process high light data with
The low light data, generating algorithm data, including：
By the spatial domain change algorithm process high light data, bloom algorithm data is generated；
By the spatial domain change algorithm process low light data, low smooth algorithm data is generated；
By the bloom algorithm data and the low smooth algorithm data, the algorithm data is generated.
5. method as claimed in claim 4, it is characterised in that described by the spatial domain change algorithm process low light number
According to, low smooth algorithm data is generated, including：
Part algorithmic formula is compensated by low light and processes the low light data, generate the low smooth algorithm data；
The low light compensates part algorithmic formula, including：
Wherein, Y2For the low smooth algorithm data, k is low smooth compensating parameter, and I is the pixel value of the video image of input, Y1For defeated
The correction value of the video image for entering.
6. method as claimed in claim 5, it is characterised in that described by the spatial domain change algorithm process bloom number
According to, bloom algorithm data is generated, including：
Part algorithmic formula is compensated by bloom and processes the high light data, generate bloom algorithm data；
The bloom compensates part algorithmic formula, including：
Wherein, Y3For the bloom algorithm data, α is bloom compensating parameter, and I is the pixel value of the video image of input, Y1For defeated
The correction value of the video image for entering, Max a are the pixel maximum of the video image of input.
7. method as claimed in claim 6, it is characterised in that the bloom compensating parameter scope is 0.7-1.
8. method as claimed in claim 7, it is characterised in that described by the bloom algorithm data and the low smooth algorithm
Data, generate the algorithm data, including equation below：
Y=Y2+Y3
Wherein, Y be the algorithm data, Y2For the low smooth algorithm data, Y3For the bloom algorithm data.
9. the method for claim 1, it is characterised in that described is wide dynamic by the algorithm data output video image
State image.
10. a kind of device for processing Bayer format video image, it is characterised in that include：
Pretreatment module, for pre-processing to the video image of the Bayer format being input into, generates preprocessed data；
Data module, for processing the preprocessed data, generates high light data and low light data；
Algoritic module, for using the spatial domain change algorithm process high light data and the low light data, generating algorithm data；
And
Output module, for by the algorithm data output video image.
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