CN107862671A - A kind of processing method of image, device and television set - Google Patents
A kind of processing method of image, device and television set Download PDFInfo
- Publication number
- CN107862671A CN107862671A CN201711308823.0A CN201711308823A CN107862671A CN 107862671 A CN107862671 A CN 107862671A CN 201711308823 A CN201711308823 A CN 201711308823A CN 107862671 A CN107862671 A CN 107862671A
- Authority
- CN
- China
- Prior art keywords
- brightness
- pixel
- luminance area
- luminance
- brightness section
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000003672 processing method Methods 0.000 title claims abstract description 15
- 238000000034 method Methods 0.000 claims abstract description 21
- 238000012545 processing Methods 0.000 claims abstract description 21
- 238000004590 computer program Methods 0.000 claims description 4
- 239000004744 fabric Substances 0.000 claims 1
- 230000006870 function Effects 0.000 description 10
- 230000008569 process Effects 0.000 description 8
- 230000006835 compression Effects 0.000 description 6
- 238000007906 compression Methods 0.000 description 6
- 238000004891 communication Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 230000002708 enhancing effect Effects 0.000 description 4
- 238000013507 mapping Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- 238000013461 design Methods 0.000 description 2
- 101100377097 Neurospora crassa (strain ATCC 24698 / 74-OR23-1A / CBS 708.71 / DSM 1257 / FGSC 987) yth-1 gene Proteins 0.000 description 1
- 101150094563 YTH1 gene Proteins 0.000 description 1
- 230000003321 amplification Effects 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000003199 nucleic acid amplification method Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000004549 pulsed laser deposition Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/90—Dynamic range modification of images or parts thereof
- G06T5/92—Dynamic range modification of images or parts thereof based on global image properties
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20172—Image enhancement details
- G06T2207/20208—High dynamic range [HDR] image processing
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Image Processing (AREA)
Abstract
The embodiment of the present application provides a kind of processing method of image, device and television set, is related to technical field of image processing, solves and loses problem using the image detail present in the HDR image of prior art generation.This method includes：Input picture is divided into different luminance areas, according to the Luminance Distribution of pixel in each luminance area, each luminance area is divided into different first brightness sections respectively；It is that each luminance area sets one-to-one object brightness region according to the target locating depth of input picture, and by each object brightness region division be different second brightness sections, the quantity of the first brightness section is identical with the quantity of the second brightness section in correspondence object brightness region in each luminance area；The bound of the bound of first brightness section and the second brightness section corresponding with the first brightness section according to residing for pixel to be corrected, pixel to be corrected is converted into the gray value in the second brightness section in the gray value of the first brightness section.
Description
Technical field
The application is related to technical field of image processing, more particularly to a kind of processing method of image, device and television set.
Background technology
Because HDR (High Dynamic Range, HDR) TV preferably can reflect in true environment
Visual effect, therefore, HDR TVs are by more and more extensive use.HDR TVs are when playing video, the height to reach HDR
Brightness and the display effect of high-contrast, film source need be HDR format film source.But common film source is on the market at present
The film source of standard dynamic range (Standard Dynamic Range, SDR) form.Therefore, in order to reach HDR high brightness with
The display effect of high-contrast, HDR TVs are when playing video, it is necessary to which the film source of SDR forms to be converted to the piece of HDR format
Source.
In the prior art, the film source of SDR forms is converted into HDR format usually using dynamic range of images enhancing algorithm
Film source.Specifically, for each two field picture in film source, prior art can divide the image according to a gray threshold
For highlight regions and low bright area, for low bright area, a compression function can be used by the gray scale of pixel in low bright area
Value carries out linear compression, for highlight regions, an enhancing function can be used to carry out the gray value of pixel in highlight regions
Linear enhancing, so as to increase the contrast of amplification image.
But because the low bright area and highlight regions that prior art is only image distribute a function respectively, that is, use
Same enhancing function is linearly strengthened the gray value of pixel in highlight regions, and using same compression function to low bright
The gray value of pixel carries out linear compression in region, and further accurate stroke is carried out to low bright area and highlight regions
Point, so as to cause the detail brightness in image effectively can not be lifted or stretched, and then cause image details to be present
Loss.
The content of the invention
Embodiments herein provides a kind of processing method of image, device and television set, solves using prior art
Image detail loss problem present in the HDR image of generation.
To reach above-mentioned purpose, embodiments herein adopts the following technical scheme that：
In a first aspect, the embodiment of the present application provides a kind of processing method of image, including：
The input picture is divided into different luminance areas；
According to the Luminance Distribution of pixel in each luminance area, each luminance area is divided into respectively different
First brightness section；
It is that each luminance area sets one-to-one object brightness region according to the target locating depth of the input picture, with
And by each object brightness region division be the second different brightness sections, wherein, the first brightness section in each luminance area
Quantity it is identical with the quantity of the second brightness section in corresponding object brightness region；
The bound of the first brightness section according to residing for pixel to be corrected and corresponding with first brightness section
The second brightness section bound, gray value of the pixel to be corrected in first brightness section is converted into institute
State the gray value of the second brightness section.
Second aspect, the embodiment of the present application provides a kind of processing unit of image, including memory and processor, described to deposit
Reservoir is used to store computer program, and the processor is schemed as described in relation to the first aspect for performing the computer program with realizing
The processing method of picture.
The third aspect, the embodiment of the present application provide a kind of computer-readable storage medium, stored on the computer-readable storage medium
For computer software instructions, computer is set to perform the processing of image as described in relation to the first aspect after the computer software instructions operation
Method.
Fourth aspect, the embodiment of the present application provide a kind of television set, include the processing unit of the image described in second aspect.
The scheme that the application provides, by the way that input picture to be divided into different luminance areas, then according to each brightness
The Luminance Distribution of pixel in region, each luminance area is divided into the first different brightness sections, then, schemed according to input
The target locating depth of picture is that each luminance area sets one-to-one object brightness region, and by each object brightness region division
For the second different brightness sections, by the application the quantity for the first brightness section that each luminance area is marked off with it is right
The quantity of the second brightness section is identical in the object brightness region answered, therefore, each in each luminance area in application
Corresponding second brightness section of one brightness section so that the pixel in the brightness section of difference first in different luminance areas
Point, can be according to the bound of the first brightness section residing for the pixel and corresponding with first brightness section second bright
The bound in section is spent, the pixel is converted into the gray value in the second brightness section in the gray value of the first brightness section,
So as to carry out different degrees of stretching or compression to the pixel in the brightness section of difference first in different luminance areas, avoid
The loss of detail of image.
Brief description of the drawings
, below will be in embodiment or description of the prior art in order to illustrate more clearly of the technical scheme of the embodiment of the present application
The required accompanying drawing used is briefly described, it should be apparent that, drawings in the following description are only some realities of the application
Example is applied, for those of ordinary skill in the art, on the premise of not paying creative work, can also be according to these accompanying drawings
Obtain other accompanying drawings.
Fig. 1 is a kind of schematic flow sheet of the processing method for image that the embodiment of the present application provides；
Fig. 2 is a kind of division schematic diagram of the brightness section for low bright area that the embodiment of the present application provides；
Fig. 3 is a kind of division schematic diagram of the brightness section for highlight regions that the embodiment of the present application provides；
Fig. 4 is a kind of structural representation of the processing unit for image that the embodiment of the present application provides.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present application, the technical scheme in the embodiment of the present application is carried out clear, complete
Site preparation describes, it is clear that described embodiment is only some embodiments of the present application, rather than whole embodiments.It is based on
Embodiment in the application, those of ordinary skill in the art are obtained every other under the premise of creative work is not made
Embodiment, belong to the scope of the application protection.
It should be noted that the printed words such as " first " herein, " second " are to function and act on essentially identical identical entry
Or similar item makes a distinction, it will be appreciated by those skilled in the art that the printed words such as " first ", " second " to quantity and do not perform secondary
Sequence is defined.
It should be noted that in the embodiment of the present application, " exemplary " or " such as " etc. word make example, example for expression
Card or explanation.Be described as in the embodiment of the present application " exemplary " or " such as " any embodiment or design should
It is interpreted than other embodiments or design more preferably or more advantage.Specifically, " exemplary " or " example are used
Such as " word is intended to that related notion is presented in a concrete fashion.
It should be noted that in the embodiment of the present application, unless otherwise indicated, the implication of " multiple " refer to two or two with
On.For example, multiple first brightness sections refer to two or more first brightness sections, multiple second brightness sections refer to
Two or more second brightness sections.
It should be noted that in the embodiment of the present application, " (English：Of) ", " corresponding (English：Corresponding,
Relevant it is) " and " corresponding (English：Corresponding) " can use with sometimes, it is noted that do not emphasizing it
During difference, its is to be expressed be meant that it is consistent.
The executive agent of the processing method for the image that the embodiment of the present application provides can be the processing unit of image, Huo Zheyong
In the display device for the processing method for performing above-mentioned image.Wherein, the processing unit of image can be in above-mentioned display device
Central processing unit (English：Central Processing Unit, referred to as：CPU) or can be in above-mentioned display device
Control unit or functional module.Exemplary, above-mentioned display device can be the display device comprising display screen, for example,
Computer, tablet personal computer, television set etc. have the product of display function.
Below in conjunction with the Figure of description of the embodiment of the present invention, technical scheme provided in an embodiment of the present invention is said
It is bright.Obviously, it is described be the present invention part of the embodiment, rather than whole embodiment.It should be noted that hereafter institute
Part or all of technical characteristic in any number of technical schemes provided can be used in combination, shape in the case where not conflicting
Cheng Xin technical scheme.
The processing method of the image provided based on the above, the embodiment of the present application, as shown in figure 1, this method is included such as
Lower step：
S101, input picture is divided into different luminance areas.
Wherein, above-mentioned input picture is not limited to SDR image, or other need to increase contrast and brightness
Image, the application do not limited this.
The application, can be according to the gray value of pixel in input picture when carrying out the division of luminance area to input picture
Different threshold values is set, carries out the division of luminance area.For example, by input picture be divided into highlight regions, middle bright area and
These three luminance areas of low bright area, or, input picture is directly divided into highlight regions and low bright area the two brightness
Region.It should be noted that the quantity for the luminance area that the application is not marked off to input picture is defined, input picture
The quantity of middle luminance area can flexibly be set according to practical application scene.
In a kind of example, it is assumed that input picture is divided into two luminance areas, then S101 specifically comprises the following steps：
S101a, average gray value and maximum gradation value according to pixel in input picture, first threshold is set.
S101b, using first threshold as critical value, input picture is divided into different luminance areas.
Exemplary, the application, being averaged according to input picture when carrying out the division of luminance area to input picture
Gray value gray_mean and maximum gradation value gray_max_input set a first threshold Seg_th, then, according to this
Input picture is divided into highlight regions and low bright area by one threshold value Seg_th, for each pixel in input picture, if should
The gray value of pixel is more than threshold value Seg_th, then the pixel belongs to highlight regions, and otherwise, the pixel belongs to low clear zone
Domain.But if the maximum gradation value of input picture is again smaller than first threshold Seg_th, the highlight regions of the input picture
Sky, it is all low bright area that now the input picture is overall.
Further, above-mentioned S101a is specifically included：
If the maximum gradation value of pixel is less than or equal to Second Threshold in A1, input picture, by input picture GTG most
Big value is used as first threshold.
Exemplary, when the maximum gradation value of pixel in input picture is less than or equal to Second Threshold, then it is assumed that the input figure
As to be overall excessively dark, in order to avoid subregion is thought into highlight regions, now setting the highlight regions of the input picture as sky,
It is all low bright area that i.e. the input picture is overall.
If the maximum gradation value of pixel is more than Second Threshold in A2, input picture, according in input picture pixel it is flat
Equal gray value, determines first threshold.
Above-mentioned step A1 and A2 is specifically represented with following formula 1.
Wherein, Seg_th is first threshold, and max_value_input is the maximum of input picture GTG, gray_mean
For the average gray value of pixel in input picture, gray_max_input is the maximum gradation value of pixel in input picture, max_
Th is Second Threshold, and gain is a customized parameter.In general, the maximum of input picture GTG is 2n, wherein, n is defeated
Enter the locating depth of image.For example, if the locating depth of input picture is 8bit, corresponding max_value_input is equal to 255, if defeated
The locating depth for entering image is 10bit, then corresponding max_value_input is equal to 1023.
S102, the Luminance Distribution according to pixel in each luminance area, are divided into difference by each luminance area respectively
The first brightness section.
Wherein, the Luminance Distribution of pixel is used to characterize in the luminance area in the brightness range of pixel in luminance area
The Density Distribution of pixel, the Density Distribution include the pixel in the brightness range of pixel under different brightness in the luminance area
Point number.
In a kind of example, in any one luminance area, the bound difference of each first brightness section with this first
The number of pixel in brightness section is inversely proportional.That is the first brightness section it is wider to should be in the first brightness section pixel
Number it is fewer, otherwise the narrower number to pixel that should be in the first brightness section of the first brightness section is more.Further
, the number of the pixel in any one luminance area in each first brightness section is identical.
In a kind of example, following step is performed for any luminance area in S102：
B1, the gray value according to pixel in luminance area, establish the accumulative histogram of luminance area.
Wherein, above-mentioned accumulative histogram is used for the Luminance Distribution for characterizing pixel in luminance area.Accumulative histogram
Behavior GTG, the scope of the GTG are the grey-scale range of pixel in the luminance area, and the accumulative histogram is classified as the GTG
Corresponding pixel points number accounts for the ratio of total pixel number in the luminance area.
Specifically, the accumulative histogram is used to represent in the luminance area that each GTG frequency occurs with the pixel under the GTG
Corresponding relation between secondary, the corresponding relation can be represented by following formula 2.
Wherein, N represents the sum of pixel in luminance area；NkRepresent the number for the pixel that GTG is k, k value model
Minimum gradation value for pixel in the luminance area is enclosed to maximum gradation value.P (k) represents the cumulative distribution probability that GTG is k.
B2, the luminance area is divided into according to accumulative histogram by the first different brightness sections.
In a kind of example, by taking the low bright area of input picture as an example, if the low bright area of input picture is divided into 3
First brightness section, then need four boundary values.As shown in Fig. 2 four boundary values be followed successively by xth0, xth1, xth2,
xth3.In this four boundary values, minimum value xth0 is 0, and maximum xth3 is above-mentioned first threshold, i.e. Seg_th.For it
Two remaining values, can be obtained according to the accumulative histogram of the low bright area.
Specifically, it is determined that, it is necessary to set two threshold values PER_LOW_TH1 and PER_LOW_ before setting xth1 and xth2
TH2, wherein, PER_LOW_TH1 is that the number of pixel in xth0 to xth1 brightness section accounts for total pixel in the low bright area
The ratio of point number, PER_LOW_TH2 are that the number of pixel in xth1 to xth2 brightness section is accounted in the low bright area always
The ratio of pixel number.Then, by corresponding to the row of first in the accumulative histogram accumulated probability more than PER_LOW_TH1
GTG is as xth1, and GTG is as xth2 corresponding to the row of first accumulated probability more than PER_LOW_TH2.Based on above-mentioned interior
Hold and understand, the brightness section of above three first is respectively：[xth0, xth1], [xth1, xth2], [xth2, xth3].
It should be noted that above-mentioned PER_LOW_TH1, PER_LOW_TH2 can constantly enter according in image quality test process
Row experiment obtains, and both spans are [0, p (Seg_th)], wherein, p (Seg_th) refers to the pixel in input picture
Gray value be Seg_th accumulated probability.For example, the quantity of the first brightness section if desired marked off is 3, can set
PER_LOW_TH1=p (Seg_th)/3, PER_LOW_TH2=2p (Seg_th)/3, will the low bright area be divided into pixel
3 the first brightness sections of number identical.
Wherein, above-mentioned xth1 and xth2 determination process can refer to following formula 3 and formula 4.
Xth1=i, hist [i]>PER_LOW_TH1＆＆hist [i-1]≤PER_LOW_TH1 (formula 3)
Xth2=j, hist [j]>PER_LOW_TH2＆＆hist [j-1]≤PER_LOW_TH2 (formula 4)
Wherein, i represents GTG corresponding to the row of first accumulated probability more than PER_LOW_TH1, and j represents first big
GTG corresponding to row in PER_LOW_TH2 accumulated probability, hist are the set of each accumulated probability in accumulative histogram.
In a kind of example, by taking the highlight regions of input picture as an example, if the highlight regions of input picture are divided into 3
First brightness section, then need four boundary values.As shown in figure 3, four boundary values be followed successively by xth3, xth4, xth5,
xth6.In this four boundary values, minimum value xth3 is first threshold, i.e. Seg_th, and maximum xth6 is input picture GTG
Maximum.For remaining two values, can be obtained according to the accumulative histogram of the highlight regions.Specific acquisition process and low clear zone
Xth1 is similar with xth2 acquisition process in domain, repeats no more here.
It should be noted that when obtaining the two boundary values of xth4 and xth5, set PER_HIGH_TH1 and
PER_HIGH_TH2 also according to constantly being tested to obtain in image quality test process, both spans for [P (Seg_th),
1].For example, the quantity of the first brightness section if desired marked off is 3, PER_HIGH_TH1=[1-P (Seg_th)]/3,
PER_HIGH_TH2=2P [1-P (Seg_th)]/3, will the low bright area be divided into pixel number identical 3 first
Brightness section.
S103, according to the target locating depth of input picture it is that each luminance area sets one-to-one object brightness region,
And by each object brightness region division it is the second different brightness sections.
Wherein, the quantity of the first brightness section and the second brightness region in corresponding object brightness region in each luminance area
Between quantity it is identical, i.e., each first brightness section in each luminance area has second brightness section to correspond to therewith.
Exemplary, the application can be directly according to the number of luminance area in the target locating depth and input picture of input picture
Amount, sets out different threshold values, so as to set an object brightness region for each luminance area.
In a kind of example, it is assumed that input picture is divided into two luminance areas, then according to input picture in S103
Target locating depth is that each luminance area sets one-to-one object brightness region, is comprised the following steps：
C1, the average gray value according to pixel in the target locating depth and input picture of input picture, determine the 3rd
Threshold value.
C2, using the 3rd threshold value as critical value, will be that each luminance area sets one-to-one object brightness region.
Wherein, the target locating depth of the input picture in the application is more than the locating depth of input picture.
Exemplary, the calculation formula of the 3rd above-mentioned threshold value Seg_th_y is as follows：
Seg_th_y=max_value_output*scl*gray_mean/max_value_input (formula 5)
Wherein, max_value_output is the target maximum gradation value of pixel in input picture.If for example, input picture
Target locating depth be 8, max_value_output 255, if the target locating depth of input picture be 10, max_value_output
For 1023；Scl is adjustment coefficient.Wherein, scl span is the real number more than 0.When scl is bigger, output image is brighter,
When scl is smaller, the image of output is darker.
In a kind of example, the application, can when being the second different brightness sections by each object brightness region division
With according to corresponding to each object brightness region in luminance area the first brightness section quantity, respectively by each object brightness area
Domain is divided, and the quantity for the second brightness section that each object brightness region is marked off is corresponding with the object brightness region
The quantity of the first brightness section is identical in luminance area.
As shown in Fig. 2 border xth0, xth1, xth2, xth3 (Seg_ of the first brightness section of above-mentioned low bright area
Th), the border of the second brightness section of corresponding object brightness region division is respectively yth0, yth1, yth2, yth3
(Seg_th_y).As shown in figure 3, the border xth3 (Seg_th) of the first brightness section of above-mentioned highlight regions, xth4, xth5,
Xth6, the border in corresponding object brightness region is respectively yth3 (Seg_th_y), yth4, yth5, yth6.
Specifically：
Yth0=0；
Yth1=Seg_th_y*PER_LOW_TH1_OUT；
Yth2=Seg_th_y*PER_LOW_TH2_OUT；
Yth3=Seg_th_y；
Yth4=Seg_th_y+max_value_output*PER_HIGH_TH1_OUT；
Yth5=Seg_th_y+max_value_output*PER_HIGH_TH2_OUT；
Yth6=max_value_output.
Wherein, above-mentioned PER_LOW_TH1_OUT, PER_LOW_TH1_OUT, PER_HIGH_TH2_OUT, PER_HIGH_
TH2_OUT is predetermined threshold value.Span is [0,1].Specific value can be constantly to be tested in image quality test process
Obtained empirical value.
For example, PER_LOW_TH1_OUT=PER_HIGH_TH1_OUT=1/3 can be set；PER_LOW_TH2_OUT=
PER_HIGH_TH2_OUT=2/3.
S104, the bound of the first brightness section according to residing for pixel to be corrected and corresponding with the first brightness section
The second brightness section bound, pixel to be corrected is converted into the gray value of first brightness section bright second
Spend the gray value in section.
Exemplary, the application is getting the bound of each first brightness section and corresponding to first brightness region
Between the second brightness section bound after, bound that can be based on each first brightness section and first bright corresponding to this
The bound of second brightness section in section is spent, obtains the gray value of pixel in each first brightness section to target gray value
The mapping coefficient of mapping.
Example 1：Understood with the brightness section division schematic diagram of the low bright area shown in Fig. 2, three in the low bright area
The gray value mapping relations of first brightness section are：
Example 2：Understood with the brightness section division schematic diagram of the highlight regions shown in Fig. 3, three in the highlight regions
The gray value mapping relations of first brightness section are：
Wherein, above-mentioned X represents gray value of the pixel in the first brightness section, and Y represents pixel pixel the
Gray value in two brightness sections.
The scheme that the application provides, by the way that input picture to be divided into different luminance areas, then according to each brightness
The Luminance Distribution of pixel in region, each luminance area is divided into the first different brightness sections, then, schemed according to input
The target locating depth of picture is that each luminance area sets one-to-one object brightness region, and by each object brightness region division
For the second different brightness sections, by the application the quantity for the first brightness section that each luminance area is marked off with it is right
The quantity of the second brightness section is identical in the object brightness region answered, therefore, each in each luminance area in application
Corresponding second brightness section of one brightness section so that the pixel in the brightness section of difference first in different luminance areas
Point, can be according to the bound of the first brightness section residing for the pixel and corresponding with first brightness section second bright
The bound in section is spent, the pixel is converted into the gray value in the second brightness section in the gray value of the first brightness section,
So as to carry out different degrees of stretching or compression to the pixel in the brightness section of difference first in different luminance areas, avoid
The loss of detail of image.
Illustrate the device embodiment corresponding with embodiment of the method presented above provided in an embodiment of the present invention below.
It should be noted that in following apparatus embodiment related content explanation, may be referred to above method embodiment.
In the case of using integrated unit, Fig. 4 shows the processing unit of image involved in above-described embodiment
A kind of possible structural representation.The device includes：Processor 21, memory 22, system bus 23 and communication interface 24.Storage
Device 21 is used to store computer executable code, and processor 21 is connected with memory 22 by system bus 23, when plant running,
Processor 21 be used for perform memory 22 storage computer executable code, with perform it is provided in an embodiment of the present invention any one
The processing method of image, e.g., processor 21 are used to support the processing unit of image to perform the Overall Steps in Fig. 1, and/or are used for
Other processes of techniques described herein, the processing method of specific image refer to the associated description in above and accompanying drawing,
Here is omitted.
The embodiment of the present invention also provides a kind of storage medium, and the storage medium can include memory 22.
The embodiment of the present invention also provides a kind of television set, and the television set includes the processing unit of the image shown in Fig. 4.
Processor 21 can be the general designation of a processor or multiple treatment elements.For example, processor 21 can be with
For central processing unit (central processing unit, CPU).Processor 21 can also be other general processors, numeral
Signal processor (digital signal processing, DSP), application specific integrated circuit (application specific
Integrated circuit, ASIC), field programmable gate array (field-programmable gate array, FPGA)
Either other PLDs, discrete gate or transistor logic, discrete hardware components etc., it can realize or hold
Various exemplary logic blocks of the row with reference to described by the disclosure of invention, module and circuit.General processor can be
Microprocessor or the processor can also be any conventional processors etc..Processor 21 can also be application specific processor, should
Application specific processor can include at least one in baseband processing chip, radio frequency processing chip etc..The processor can also be
The combination of computing function is realized, such as is combined comprising one or more microprocessors, combination of DSP and microprocessor etc..Enter
One step, the application specific processor can also include the chip with other dedicated processes functions of the device.
The step of method with reference to described by the disclosure of invention can be realized in a manner of hardware or by
The mode that reason device performs software instruction is realized.Software instruction can be made up of corresponding software module, and software module can be by
Deposit in random access memory (English：Random access memory, abbreviation：RAM), flash memory, read-only storage (English
Text：Read only memory, abbreviation：ROM), Erasable Programmable Read Only Memory EPROM (English：erasable
Programmable ROM, abbreviation：EPROM), EEPROM (English：Electrically EPROM,
Abbreviation：EEPROM), register, hard disk, mobile hard disk, read-only optical disc (CD-ROM) or any other shape well known in the art
In the storage medium of formula.A kind of exemplary storage medium is coupled to processor, so as to enable a processor to from the storage medium
Information is read, and information can be write to the storage medium.Certainly, storage medium can also be the part of processor.Processing
Device and storage medium can be located in ASIC.In addition, the ASIC can be located in terminal device.Certainly, processor and storage are situated between
Matter can also be present in terminal device as discrete assembly.
System bus 23 can include data/address bus, power bus, controlling bus and signal condition bus etc..The present embodiment
In for clear explanation, various buses are all illustrated as system bus 23 in Fig. 4.
Communication interface 24 can be specifically the transceiver on the device.The transceiver can be wireless transceiver.For example, nothing
Line transceiver can be antenna of the device etc..Processor 21 is by communication interface 24 and other equipment, if for example, the device is
During a module or component in the terminal device, the device is used to carry out data between other modules in the terminal device
Interactive, e.g., the display module of the device and the terminal device carries out data interaction, controls the display module to show before and after correcting
Image.
Those skilled in the art are it will be appreciated that in said one or multiple examples, work(described in the invention
It is able to can be realized with hardware, software, firmware or their any combination.When implemented in software, can be by these functions
It is stored in computer-readable medium or is transmitted as one or more instructions on computer-readable medium or code.
Computer-readable medium includes computer-readable storage medium and communication media, and wherein communication media includes being easy to from a place to another
Any medium of one place transmission computer program.It is any that storage medium can be that universal or special computer can access
Usable medium.
Finally it should be noted that：Above-described embodiment, to the purpose of the present invention, technical scheme and beneficial to effect
Fruit is further described, and should be understood that the embodiment that the foregoing is only the present invention, not
For limiting protection scope of the present invention, all any modifications on the basis of technical scheme, made, equally replace
Change, improve, all should be included within protection scope of the present invention.
Claims (9)
- A kind of 1. processing method of image, it is characterised in that including：The input picture is divided into different luminance areas；According to the Luminance Distribution of pixel in each luminance area, each luminance area is divided into different first respectively Brightness section；It is that each luminance area sets one-to-one object brightness region according to the target locating depth of the input picture, and will Each object brightness region division is the second different brightness section, wherein, the number of the first brightness section in each luminance area Amount is identical with the quantity of the second brightness section in corresponding object brightness region；The bound of the first brightness section according to residing for pixel to be corrected and corresponding with first brightness section The bound of two brightness sections, the pixel to be corrected is converted into described in the gray value of first brightness section The gray value of two brightness sections.
- 2. according to the method for claim 1, it is characterised in that described that the input picture is divided into different brightness regions Domain, including：According to the average gray value and maximum gradation value of pixel in input picture, first threshold is set；Using the first threshold as critical value, the input picture is divided into different luminance areas.
- 3. according to the method for claim 1, it is characterised in that the brightness of pixel point in each luminance area of basis Cloth, each luminance area is divided into the first different brightness sections respectively, including：Following steps are performed for any luminance area：According to the gray value of pixel in the luminance area, the accumulative histogram of the luminance area is established, it is described accumulative straight Scheme the Luminance Distribution for characterizing pixel in the luminance area in side；The luminance area is divided into according to the accumulative histogram by the first different brightness sections.
- 4. according to the method described in any one of claims 1 to 3, it is characterised in that in any one luminance area, each first The difference of the bound of brightness section and the number of the pixel in first brightness section are inversely proportional.
- 5. according to the method described in any one of claims 1 to 3, it is characterised in that in any one object brightness region, each The difference all same of the bound of second brightness section.
- 6. according to the method described in any one of claims 1 to 3, it is characterised in that in any one luminance area, each first The number of pixel in brightness section is identical.
- 7. a kind of processing unit of image, it is characterised in that including memory and processor, the memory, which is used to store, to be calculated Machine program, the processor are used to perform the computer program to realize such as the place of any one of claim 1 to 6 described image Reason method.
- A kind of 8. computer-readable storage medium, it is characterised in that computer software instructions are stored as on the computer-readable storage medium, Computer is set to perform such as the processing method of any one of claim 1 to 6 described image after the computer software instructions operation.
- 9. a kind of television set, it is characterised in that include the processing unit of the image described in claim 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711308823.0A CN107862671A (en) | 2017-12-11 | 2017-12-11 | A kind of processing method of image, device and television set |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711308823.0A CN107862671A (en) | 2017-12-11 | 2017-12-11 | A kind of processing method of image, device and television set |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107862671A true CN107862671A (en) | 2018-03-30 |
Family
ID=61705522
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711308823.0A Pending CN107862671A (en) | 2017-12-11 | 2017-12-11 | A kind of processing method of image, device and television set |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107862671A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109754443A (en) * | 2019-01-30 | 2019-05-14 | 京东方科技集团股份有限公司 | Image data method for transformation, device and storage medium |
| CN111683254A (en) * | 2020-06-24 | 2020-09-18 | 湖南国科微电子股份有限公司 | Image compression method and device, electronic equipment and storage medium |
| CN112449120A (en) * | 2019-08-30 | 2021-03-05 | 华为技术有限公司 | High dynamic range video generation method and device |
| CN112529786A (en) * | 2019-09-19 | 2021-03-19 | 佳能株式会社 | Image processing apparatus and method, and non-transitory computer-readable storage medium |
| CN112911186A (en) * | 2019-12-03 | 2021-06-04 | RealMe重庆移动通信有限公司 | Image storage method and device, electronic equipment and storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040258324A1 (en) * | 2003-06-20 | 2004-12-23 | Kuan Liang | Method for dynamic contrast enhancement by area gray-level detection |
| CN106342331B (en) * | 2010-09-03 | 2014-06-11 | 中国航空工业集团公司洛阳电光设备研究所 | A kind of histogram equalization method that dispositif de traitement lineaire adapte stretches |
-
2017
- 2017-12-11 CN CN201711308823.0A patent/CN107862671A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040258324A1 (en) * | 2003-06-20 | 2004-12-23 | Kuan Liang | Method for dynamic contrast enhancement by area gray-level detection |
| CN106342331B (en) * | 2010-09-03 | 2014-06-11 | 中国航空工业集团公司洛阳电光设备研究所 | A kind of histogram equalization method that dispositif de traitement lineaire adapte stretches |
Non-Patent Citations (3)
| Title |
|---|
| L. MEYLAN, S. DALY,S. SÜSSTRUNK: "The reproduction of specular Highlights on High Dynamic Range Displays", 《IS&T/SID 14TH COLOR IMAGING CONF》 * |
| TSUN-HSIEN WANG,CHENG-WEN CHIU,WEI-CHEN WU ET AL: "Pseudo-Multiple-Exposure-Based Tone Fusion With Local Region Adjustment", 《IEEE TRANSACTIONS ON MULTIMEDIA》 * |
| 许艳: "显微图像阈值分割算法的研究", 《应用光学》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109754443A (en) * | 2019-01-30 | 2019-05-14 | 京东方科技集团股份有限公司 | Image data method for transformation, device and storage medium |
| CN109754443B (en) * | 2019-01-30 | 2021-04-20 | 京东方科技集团股份有限公司 | Image data conversion method, device and storage medium |
| US11616895B2 (en) | 2019-01-30 | 2023-03-28 | Beijing Boe Optoelectronics Technology Co., Ltd. | Method and apparatus for converting image data, and storage medium |
| CN112449120A (en) * | 2019-08-30 | 2021-03-05 | 华为技术有限公司 | High dynamic range video generation method and device |
| CN112449120B (en) * | 2019-08-30 | 2022-06-10 | 华为技术有限公司 | High dynamic range video generation method and device |
| CN112529786A (en) * | 2019-09-19 | 2021-03-19 | 佳能株式会社 | Image processing apparatus and method, and non-transitory computer-readable storage medium |
| CN112911186A (en) * | 2019-12-03 | 2021-06-04 | RealMe重庆移动通信有限公司 | Image storage method and device, electronic equipment and storage medium |
| CN112911186B (en) * | 2019-12-03 | 2023-03-24 | RealMe重庆移动通信有限公司 | Image storage method and device, electronic equipment and storage medium |
| CN111683254A (en) * | 2020-06-24 | 2020-09-18 | 湖南国科微电子股份有限公司 | Image compression method and device, electronic equipment and storage medium |
| CN111683254B (en) * | 2020-06-24 | 2022-03-25 | 湖南国科微电子股份有限公司 | Image compression method and device, electronic equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107862671A (en) | A kind of processing method of image, device and television set | |
| CN107408367B (en) | Method, device and system for correcting unevenness of display screen | |
| CN107221306B (en) | The method, apparatus and display equipment of brightness of image in correction splicing device screen | |
| CN108074220A (en) | A kind of processing method of image, device and television set | |
| CN108962185B (en) | Method for reducing display image brightness, device thereof and display device | |
| US10783837B2 (en) | Driving method and driving device of display device, and related device | |
| CN109036333B (en) | Display parameter correction method and device of display, terminal equipment and storage medium | |
| CN108665428B (en) | Image enhancement method, device, equipment and storage medium | |
| CN109817170B (en) | Pixel compensation method and device and terminal equipment | |
| CN101408973A (en) | Method of image processing and device thereof | |
| EP3379822A1 (en) | Real-time video enhancement method, terminal, and nonvolatile computer readable storage medium | |
| CN109309826B (en) | Image color balancing method and device, terminal equipment and readable storage medium | |
| CN113507598B (en) | Video picture display method, device, terminal and storage medium | |
| CN110580693B (en) | Image processing method, image processing device, computer equipment and storage medium | |
| US20140348428A1 (en) | Dynamic range-adjustment apparatuses and methods | |
| EP3968141A1 (en) | Display attribute adjusting method and related device | |
| CN110807750B (en) | Image processing method and apparatus | |
| CN109215614A (en) | A kind of image quality adjusting method, regulating device and terminal device | |
| CN112783460B (en) | Display control method and device, electronic equipment and readable storage medium | |
| US20160012571A1 (en) | Image processor and image processing system including the same | |
| CN100525469C (en) | Image processing device and method | |
| US9292912B2 (en) | Display apparatus and method for image output thereof | |
| US11315223B2 (en) | Image processing apparatus, image processing method, and computer-readable recording medium | |
| CN114584641A (en) | Display adjustment method, device, electronic equipment and storage medium | |
| CN114793275B (en) | Image signal processing method, device, terminal and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180330 |