CN105809644A - Image edge false color inhabitation method and apparatus - Google Patents
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Abstract
The invention is suitable for the field of real-time image video processing and provides an image edge false color inhabitation method and apparatus. The method comprises the steps of obtaining real-time image data; performing chromaticity transient enhancement filtering and median filtering on the real-time image data; when an oversaturated region exists around the current real-time image data, taking a filtering result of chromaticity transient enhancement filtering as output real-time image data; and when the oversaturated region does not exist around the current real-time image data, taking a filtering result of median filtering as the output real-time image data. Through the method, false colors of purple edge and other various edges can be inhibited.
Description
Technical field
The embodiment of the present invention belongs to image real time video processing field, particularly relates to a kind of image border fake color inhibition method and device.
Background technology
In camera imaging system, relation due to lens optical dispersion, lateral chromatic aberration and longitudinal chromatic aberration can be produced, these lateral chromatic aberrations and longitudinal chromatic aberration show as the false colours such as purple boundary, green limit, Huang Bian, Lan Bian at the edge of become image, and being limited produced moire fringes by the imaging capability of imaging system also can along with edge false colour.Additionally, some algorithms of Digital Image Processing also can produce abnormal color lump in image border, such as color interpolation algorithm may produce false colour in high frequency edge part.
At present, existing image border fake color inhibition method suppresses just for the purple boundary in picture processing field, and edge false colour is it is also possible that green limit, Lan Bian etc., and therefore, existing method is difficult to all false colours suppressing image border to produce.
Summary of the invention
Embodiments provide a kind of image border fake color inhibition method and device, it is intended to solve existing method and the false colour of purple boundary can only be suppressed can not to suppress other false colours, thus causing the problem that false colour suppresses narrow limits.
The embodiment of the present invention is achieved in that a kind of image border fake color inhibition method, and described method includes:
Obtain realtime image data;
Described realtime image data is carried out colourity transient state boostfiltering and medium filtering;
When there is supersaturation region around current realtime image data, using the filter result of colourity transient state boostfiltering as output realtime image data;
When being absent from supersaturation region around current realtime image data, using the filter result of medium filtering as output realtime image data.
The another object of the embodiment of the present invention is in that to provide a kind of image border false colour restraining device, and described device includes:
Realtime image data acquiring unit, is used for obtaining realtime image data;
Filter unit, for carrying out colourity transient state boostfiltering and medium filtering to described realtime image data;
First filter result output unit, for around current realtime image data, there is supersaturation region time, using the filter result of colourity transient state boostfiltering as output realtime image data;
Second filter result output unit, for around current realtime image data, be absent from supersaturation region time, using the filter result of medium filtering as output realtime image data.
In embodiments of the present invention, due to colourity transient state boostfiltering, can to filter saturation higher, the false colour of wider range, therefore, it is possible to filter the purple boundary that image border produces, due to medium filtering, can to filter some scopes narrower again, and the false colour that contrast on border is not strong, therefore, it is possible to filter the green limit owing to dispersion causes, Lan Bian etc., thus what expand false colour filters scope, improve the inhibition of the false colour that image border produces.
Accompanying drawing explanation
Fig. 1 is the flow chart of a kind of image border fake color inhibition method that first embodiment of the invention provides;
Fig. 2 is the particular flow sheet of the step S12 that second embodiment of the invention provides;
Fig. 3 is the structure chart of a kind of image border false colour restraining device that third embodiment of the invention provides.
Detailed description of the invention
In order to make the purpose of the present invention, technical scheme and advantage clearly understand, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein is only in order to explain the present invention, is not intended to limit the present invention.
In the embodiment of the present invention, the realtime image data obtained is carried out colourity transient state boostfiltering and medium filtering, when there is supersaturation region around current realtime image data, using the filter result of colourity transient state boostfiltering as output realtime image data, when being absent from supersaturation region around current realtime image data, using the filter result of medium filtering as output realtime image data.
In order to technical solutions according to the invention are described, illustrate below by specific embodiment.
Embodiment one:
Fig. 1 illustrates the flow chart of a kind of image border fake color inhibition method that first embodiment of the invention provides, and details are as follows:
Step S11, obtains realtime image data.
In this step, realtime image data includes the realtime image data that general picture is corresponding, also includes the realtime image data that video is corresponding, and the form of realtime image data is the data of yuv format.When the data that realtime image data is non-yuv format obtained, the realtime image data of the non-yuv format obtained is converted to the realtime image data of yuv format.
Step S12, carries out colourity transient state boostfiltering and medium filtering to described realtime image data.
Wherein, colourity transient state strengthens (TransientImprovement, TI) wave filter, and to be mainly used in saturation higher, filtering of the false colour of wider range, such as purple boundary;And median filter to be mainly used in some scopes narrower, filtering of the false colour that contrast on border is not strong, green limit that such as dispersion causes, Lan Bian etc..
Step S13, when there is supersaturation region around current realtime image data, using the filter result of colourity transient state boostfiltering as output realtime image data.
Alternatively, described around current realtime image data, there is supersaturation region time, using the filter result of colourity transient state boostfiltering as output realtime image data before, including:
The form of described realtime image data is yuv format, judge that whether the realtime image data in current realtime image data and described current realtime image data preset range is more than default supersaturation threshold value, and the realtime image data in current realtime image data and described current realtime image data preset range more than default supersaturation threshold value time, judge around current realtime image data, there is supersaturation region, otherwise, it is judged that around current realtime image data, be absent from supersaturation region.
Assume that current realtime image data preset range is o × p, due in sequential row cache more more convenient than row buffer memory (row buffer memory needs to use RAM, account for resource bigger) therefore, o can be set more than p, such as it is set to 21 × 9, supersaturation threshold value (saturated_thr) value preset can be set to 1000, then:
Due to colourity transient state boostfiltering, can to filter saturation higher, the false colour of wider range, therefore, it is possible to filter the purple boundary that image border produces.
Step S14, when being absent from supersaturation region around current realtime image data, using the filter result of medium filtering as output realtime image data.
Due to medium filtering, can to filter some scopes narrower, and the false colour that contrast on border is not strong, therefore, it is possible to filter the green limit owing to dispersion causes, Lan Bian etc..
In first embodiment of the invention, the realtime image data obtained is carried out colourity transient state boostfiltering and medium filtering, when there is supersaturation region around current realtime image data, using the filter result of colourity transient state boostfiltering as output realtime image data, when being absent from supersaturation region around current realtime image data, using the filter result of medium filtering as output realtime image data.Due to colourity transient state boostfiltering, can to filter saturation higher, the false colour of wider range, therefore, it is possible to filter the purple boundary that image border produces, due to medium filtering, can to filter some scopes narrower again, the false colour that contrast on border is not strong, therefore, it is possible to filter the green limit owing to dispersion causes, Lan Bian etc., thus expanding the scope that filters of false colour, improve the inhibition of the false colour that image border produces.
Embodiment two:
Fig. 2 illustrates the particular flow sheet of step S12, and details are as follows:
In order to reduce hardware resource consumption, when realtime image data carries out colourity transient state boostfiltering and medium filtering, horizontal and vertical two part all it is divided into process, now, described described realtime image data is carried out colourity transient state boostfiltering and medium filtering, specifically includes:
Step S121, the colourity transient state boostfiltering that described realtime image data is carried out simultaneously respectively vertical direction and medium filtering.Specifically, in order to improve the processing speed of realtime image data, can first use RAM buffer memory 8 row realtime image data, m × m window is provided, the realtime image data of m m matrix is carried out colourity TI filtering and the medium filtering of vertical direction again, wherein, described m > 0, can be 9 × 9 matrixes than m m matrix described above.It is pointed out that when realtime image data being carried out the filtering of vertical direction, colourity TI filtering and medium filtering carry out generally simultaneously, in order to avoid separately performed time increase hardware consumption and time delay.
Step S122, to the colourity transient state boostfiltering and the medium filtering that carry out horizontal direction through the filtered realtime image data of vertical direction more respectively simultaneously.Specifically, in order to improve the processing speed of realtime image data, can the realtime image data that need to process of first buffer memory, such as, with the corresponding realtime image data of REG buffer memory.
In above-mentioned steps S121 and step S122, first carry out vertical filtering, after carry out horizontal filtering, this is because the process of follow-up suppression false colour needs use supersaturation area information, namely need the realtime image data judging around current realtime image data whether more than default supersaturation threshold value, such as, when needing to judge that the data of the 21x9 size around current realtime image data are whether during more than default supersaturation threshold value, vertical filtering meeting buffer memory 8 row realtime image data, therefore, the 8 row realtime image datas that can directly utilize buffer memory while filtering obtain corresponding supersaturation area information.And owing to horizontal filtering does not need the realtime image data moved ahead of buffer memory, therefore, if first carrying out horizontal filtering, then in order to obtain this supersaturation area information, need buffer memory 8 row realtime image data, buffer memory 8 row realtime image data again when vertical filtering, thus wasting hardware resource, and increases algorithm time delay.
Further, above-mentioned steps S121 specifically includes:
A1, described realtime image data form be yuv format, and when being sized to m m matrix size of described realtime image data, U component and the V component of obtaining the realtime image data of described m m matrix size are specifying the maximum realtime image data value in northwards direction and direction to the south on row, and obtain the realtime image data of described m m matrix size and specifying the minimum realtime image data value in northwards direction and direction to the south on row, wherein, described m > 0;Realtime image data in current location is the maximum realtime image data value in northwards direction or direction to the south, and the realtime image data of current location less than the maximum realtime image data value in direction to the south or northwards direction time, then using the filter result as colourity transient state boostfiltering of the minima on the direction less with the difference of the realtime image data of described current location, otherwise, using the realtime image data of the current location filter result as colourity transient state boostfiltering.Wherein, it is intended that row can be the either rank of m m matrix size, it is preferable that for the middle column of m m matrix size.Assume that m × m is 9 × 9, it is intended that be classified as the 4th row, then:
X=U, V
As X=U, XNmaxRepresent the maximum realtime image data value in U passage direction northwards, XSmaxRepresent the maximum realtime image data value in U passage direction to the south, as X=V, XNmaxAnd XSmaxDuring with X=U similar, repeat no more herein.Wherein, Xin represents the realtime image data of these 2 passage inputs of corresponding U, V.If Xin (a, b) represents the realtime image data of current location, 0≤a≤m, 0≤b≤m, then the filter result of colourity transient state boostfiltering is:
X=U, V
It should be noted that above-mentioned b can be the middle column of present filter, it is such as 4.
A2, obtain the realtime image data of described m m matrix size and specifying the intermediate value on row, and using filter result as medium filtering of the intermediate value obtained.When m × m is 9 × 9, it is intended that be classified as the 4th row, ask for U component and V component in 9 × 9 matrixes the intermediate value in vertical direction particularly as follows:
Wherein, X can be U component or be V component.
In above-mentioned A1 and A2, owing to first carrying out vertical filtering, then carry out horizontal filtering, therefore, decrease the realtime image data needing buffer memory, and be prone to hardware realization, be conducive to improving the processing speed of realtime image data.
Alternatively, described step S122 specifically includes:
B1, described realtime image data form be yuv format, and when being sized to N × n matrix size of described realtime image data, obtain the U component of the realtime image data of described N × n matrix size and the V component maximum realtime image data value in westwards direction and direction eastwards in nominated bank, and obtain the realtime image data of the described N × n matrix size minimum realtime image data value in westwards direction and direction eastwards in nominated bank.Wherein, described N, n > 0.Realtime image data in current location is the maximum realtime image data value in westwards direction or direction eastwards, and the realtime image data of current location less than the maximum realtime image data value in direction eastwards or westwards direction time, then using the filter result as colourity transient state boostfiltering of the minima on the direction less with the difference of the realtime image data of described current location, otherwise, using the realtime image data of the current location filter result as colourity transient state boostfiltering.?.Alternatively, it is intended that row can be the 1st row.Assume appointment behavior the 1st row, then when described N × n is 17 × 1,
X=U, V
As X=U, XWmaxRepresent the maximum realtime image data value in U passage direction westwards, XEmaxRepresent the maximum realtime image data value in U passage direction eastwards, as X=V, XWmaxAnd XEmaxDuring with X=U similar, repeat no more herein.If Xin (c, d) represents the realtime image data of current location, 0≤c≤N, 0≤d≤n, then the filter result of colourity transient state boostfiltering is:
X=U, V
It should be noted that above-mentioned c can be 0, d can be 8.
B2, obtain realtime image data intermediate value in nominated bank, and using filter result as medium filtering of the intermediate value obtained.Assume when demand goes out the realtime image data of 9 × 1 matrixes intermediate value in nominated bank, then ask for U component and V component in 9 × 1 matrixes the intermediate value in horizontal direction particularly as follows:
Wherein, X can be U component or be V component.
Certainly, the information that the scope in follow-up supersaturation region can be transmitted through after directly adopting vertical filtering, when there is supersaturation region around current realtime image data, using the filter result of colourity transient state boostfiltering as output realtime image data, when being absent from supersaturation region around current realtime image data, using the filter result of medium filtering as output realtime image data.That is:
X=U, V
Should be understood that in embodiments of the present invention, the size of the sequence number of above-mentioned each process is not meant to the priority of execution sequence, and the execution sequence of each process should be determined with its function and internal logic, and the implementation process of the embodiment of the present invention should not constituted any restriction.
Embodiment three:
Fig. 3 illustrates the structure chart of a kind of image border false colour restraining device that third embodiment of the invention provides, this image border false colour restraining device is mainly for the real-time digital video of video camera, carrying out false colour suppression such as realizing the real time video data that platform is FPGA, it can also carry out false colour suppression for the picture of PC software platform.For the ease of illustrating, illustrate only the part relevant to the embodiment of the present invention.
Described image border false colour restraining device includes: realtime image data acquiring unit 31, filter unit the 32, first filter result output unit the 33, second filter result output unit 34.Wherein:
Realtime image data acquiring unit 31, is used for obtaining realtime image data.
Wherein, realtime image data includes the realtime image data that general picture is corresponding, also includes the realtime image data that video is corresponding, and the form of realtime image data is the data of yuv format.When the data that realtime image data is non-yuv format obtained, the realtime image data of the non-yuv format obtained is converted to the realtime image data of yuv format.
Filter unit 32, for carrying out colourity transient state boostfiltering and medium filtering to described realtime image data.
Wherein, it is higher that colourity TI wave filter is mainly used in saturation, filtering of the false colour of wider range, such as purple boundary;And median filter to be mainly used in some scopes narrower, filtering of the false colour that contrast on border is not strong, green limit that such as dispersion causes, Lan Bian etc..
Alternatively, described filter unit 32 includes:
Vertical filtering module, for carrying out colourity transient state boostfiltering and the medium filtering of vertical direction respectively simultaneously to described realtime image data.Specifically, in order to improve the processing speed of realtime image data, can the realtime image data that need to process of first buffer memory, such as, with RAM buffer memory 8 row realtime image data, it is provided that m × m window, the realtime image data of m m matrix is carried out colourity TI filtering and the medium filtering of vertical direction again, wherein, described m > 0, can be 9 × 9 matrixes than m m matrix described above.It is pointed out that when realtime image data being carried out the filtering of vertical direction, colourity TI filtering and medium filtering carry out generally simultaneously, in order to avoid separately performed time increase hardware consumption and time delay.
Horizontal filtering module, for the colourity transient state boostfiltering and the medium filtering that carry out horizontal direction through the filtered realtime image data of vertical direction more respectively simultaneously.
Further, above-mentioned vertical filtering module includes:
Vertical chrominance transient state boostfiltering result output module, for at realtime image data when being sized to m m matrix size, U component and the V component of obtaining the realtime image data of described m m matrix size are specifying the maximum realtime image data value in northwards direction and direction to the south on row, and the realtime image data obtaining described m m matrix size is specifying the minimum realtime image data value in northwards direction and direction to the south on row;Wherein, described m > 0;Realtime image data in current location is the maximum realtime image data value in northwards direction or direction to the south, and the realtime image data of current location less than the maximum realtime image data value in direction to the south or northwards direction time, then using the filter result as colourity transient state boostfiltering of the minima on the direction less with the difference of the realtime image data of described current location, otherwise, using the realtime image data of the current location filter result as colourity transient state boostfiltering;The form of described realtime image data is yuv format.Wherein, it is intended that row can be the either rank of m m matrix size, it is preferable that for the middle column of m m matrix size.
Vertical median-filtered result output module, is specifying the intermediate value on row for obtaining the realtime image data of described m m matrix size, and using filter result as medium filtering of the intermediate value obtained.When m × m is 9 × 9, it is intended that be classified as the 4th row.
Alternatively, above-mentioned horizontal filtering module includes:
Horizontal chroma transient state boostfiltering result output module, for at realtime image data when being sized to N × n matrix size, obtain the U component of the realtime image data of described N × n matrix size and the V component maximum realtime image data value in westwards direction and direction eastwards in nominated bank, and obtain the realtime image data of the described N × n matrix size minimum realtime image data value in westwards direction and direction eastwards in nominated bank;Wherein, described N, n > 0;Realtime image data in current location is the maximum realtime image data value in westwards direction or direction eastwards, and the realtime image data of current location less than the maximum realtime image data value in direction eastwards or westwards direction time, then using the filter result as colourity transient state boostfiltering of the minima on the direction less with the difference of the realtime image data of described current location, otherwise, using the realtime image data of the current location filter result as colourity transient state boostfiltering;The form of described realtime image data is yuv format.Further, because row cache is convenient in sequential, row buffer memory then needs to use RAM, accounts for resource relatively big, therefore, can arrange N > n.Alternatively, it is intended that row can be the 1st row.
Median level filter result output module, for obtaining realtime image data intermediate value in nominated bank, and using filter result as medium filtering of the intermediate value obtained.
First filter result output unit 33, for around current realtime image data, there is supersaturation region time, using the filter result of colourity transient state boostfiltering as output realtime image data.
Described image border false colour restraining device includes: supersaturation region decision unit, for judging that whether realtime image data in current realtime image data and described current realtime image data preset range is more than default supersaturation threshold value, and the realtime image data in current realtime image data and described current realtime image data preset range more than default supersaturation threshold value time, judge around current realtime image data, there is supersaturation region, otherwise, judge to be absent from supersaturation region around current realtime image data, the form of described realtime image data is yuv format.
Assume that current realtime image data preset range is o × p, due in sequential row cache more more convenient than row buffer memory (row buffer memory needs to use RAM, account for resource bigger) therefore, o can be set more than p, such as it is set to 21 × 9, supersaturation threshold value (saturated_thr) value preset can be set to 1000, then:
Due to colourity transient state boostfiltering, can to filter saturation higher, the false colour of wider range, therefore, it is possible to filter the purple boundary that image border produces.
Certainly, when carrying out horizontal filtering, the information that the scope in follow-up supersaturation region can be transmitted through after directly adopting vertical filtering.
Second filter result output unit 34, for around current realtime image data, be absent from supersaturation region time, using the filter result of medium filtering as output realtime image data.
Due to medium filtering, can to filter some scopes narrower, and the false colour that contrast on border is not strong, therefore, it is possible to filter the green limit owing to dispersion causes, Lan Bian etc..
In third embodiment of the invention, due to colourity transient state boostfiltering, can to filter saturation higher, the false colour of wider range, therefore, it is possible to filter the purple boundary that image border produces, due to medium filtering, can to filter some scopes narrower again, and the false colour that contrast on border is not strong, therefore, it is possible to filter the green limit owing to dispersion causes, Lan Bian etc., thus what expand false colour filters scope, improve the inhibition of the false colour that image border produces.
Those of ordinary skill in the art are it is to be appreciated that the unit of each example that describes in conjunction with the embodiments described herein and algorithm steps, it is possible to being implemented in combination in of electronic hardware or computer software and electronic hardware.These functions perform with hardware or software mode actually, depend on application-specific and the design constraint of technical scheme.Professional and technical personnel specifically can should be used for using different methods to realize described function to each, but this realization is it is not considered that beyond the scope of this invention.
Those skilled in the art is it can be understood that arrive, for convenience and simplicity of description, and the specific works process of the system of foregoing description, device and unit, it is possible to reference to the corresponding process in preceding method embodiment, do not repeat them here.
In several embodiments provided herein, it should be understood that disclosed system, apparatus and method, it is possible to realize by another way.Such as, device embodiment described above is merely schematic, such as, the division of described unit, being only a kind of logic function to divide, actual can have other dividing mode when realizing, for instance multiple unit or assembly can in conjunction with or be desirably integrated into another system, or some features can ignore, or do not perform.Another point, shown or discussed coupling each other or direct-coupling or communication connection can be through INDIRECT COUPLING or the communication connection of some interfaces, device or unit, it is possible to be electrical, machinery or other form.
The described unit illustrated as separating component can be or may not be physically separate, and the parts shown as unit can be or may not be physical location, namely may be located at a place, or can also be distributed on multiple NE.Some or all of unit therein can be selected according to the actual needs to realize the purpose of the present embodiment scheme.
It addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, it is also possible to be that unit is individually physically present, it is also possible to two or more unit are integrated in a unit.
If described function is using the form realization of SFU software functional unit and as independent production marketing or use, it is possible to be stored in a computer read/write memory medium.Based on such understanding, part or the part of this technical scheme that prior art is contributed by technical scheme substantially in other words can embody with the form of software product, this computer software product is stored in a storage medium, including some instructions with so that a computer equipment (can be personal computer, server, or the network equipment etc.) perform all or part of step of method described in each embodiment of the present invention.And aforesaid storage medium includes: USB flash disk, portable hard drive, read only memory (ROM, Read-OnlyMemory), the various media that can store program code such as random access memory (RAM, RandomAccessMemory), magnetic disc or CD.
The above; being only the specific embodiment of the present invention, but protection scope of the present invention is not limited thereto, any those familiar with the art is in the technical scope that the invention discloses; change can be readily occurred in or replace, all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should described be as the criterion with scope of the claims.
Claims (10)
1. an image border fake color inhibition method, it is characterised in that described method includes:
Obtain realtime image data;
Described realtime image data is carried out colourity transient state boostfiltering and medium filtering;
When there is supersaturation region around current realtime image data, using the filter result of colourity transient state boostfiltering as output realtime image data;
When being absent from supersaturation region around current realtime image data, using the filter result of medium filtering as output realtime image data.
2. method according to claim 1, it is characterised in that described described realtime image data carries out colourity transient state boostfiltering and medium filtering, specifically includes:
Described realtime image data is carried out simultaneously respectively colourity transient state boostfiltering and the medium filtering of vertical direction;
To the colourity transient state boostfiltering and the medium filtering that carry out horizontal direction through the filtered realtime image data of vertical direction more respectively simultaneously.
3. method according to claim 2, it is characterised in that the described colourity transient state boostfiltering that described realtime image data carries out vertical direction simultaneously respectively and medium filtering, specifically includes:
The form of described realtime image data is yuv format, and described realtime image data be sized to m m matrix size, U component and the V component of obtaining the realtime image data of described m m matrix size are specifying the maximum realtime image data value in northwards direction and direction to the south on row, and the realtime image data obtaining described m m matrix size is specifying the minimum realtime image data value in northwards direction and direction to the south on row;Wherein, described m > 0;Realtime image data in current location is the maximum realtime image data value in northwards direction or direction to the south, and the realtime image data of current location less than the maximum realtime image data value in direction to the south or northwards direction time, then using the filter result as colourity transient state boostfiltering of the minima on the direction less with the difference of the realtime image data of described current location, otherwise, using the realtime image data of the current location filter result as colourity transient state boostfiltering;
Obtain the realtime image data of described m m matrix size and specify the intermediate value on row, and using filter result as medium filtering of the intermediate value obtained.
4. the method according to claim 1 or 3, it is characterised in that described around current realtime image data, there is supersaturation region time, using the filter result of colourity transient state boostfiltering as output realtime image data before, including:
The form of described realtime image data is yuv format, judge that whether the realtime image data in current realtime image data and described current realtime image data preset range is more than default supersaturation threshold value, and the realtime image data in current realtime image data and described current realtime image data preset range more than default supersaturation threshold value time, judge around current realtime image data, there is supersaturation region, otherwise, it is judged that around current realtime image data, be absent from supersaturation region.
5. method according to claim 2, it is characterised in that described colourity transient state boostfiltering and medium filtering to carrying out horizontal direction more respectively through the filtered realtime image data of vertical direction simultaneously, specifically includes:
The form of described realtime image data is yuv format, and when being sized to N × n matrix size of realtime image data of described matrix size, obtain the U component of the realtime image data of described N × n matrix size and the V component maximum realtime image data value in westwards direction and direction eastwards in nominated bank, and obtain the realtime image data of the described N × n matrix size minimum realtime image data value in westwards direction and direction eastwards in nominated bank;Wherein, described N, n > 0;Realtime image data in current location is the maximum realtime image data value in westwards direction or direction eastwards, and the realtime image data of current location less than the maximum realtime image data value in direction eastwards or westwards direction time, then using the filter result as colourity transient state boostfiltering of the minima on the direction less with the difference of the realtime image data of described current location, otherwise, using the realtime image data of the current location filter result as colourity transient state boostfiltering;
Obtain realtime image data intermediate value in nominated bank, and using filter result as medium filtering of the intermediate value obtained.
6. an image border false colour restraining device, it is characterised in that described device includes:
Realtime image data acquiring unit, is used for obtaining realtime image data;
Filter unit, for carrying out colourity transient state boostfiltering and medium filtering to described realtime image data;
First filter result output unit, for around current realtime image data, there is supersaturation region time, using the filter result of colourity transient state boostfiltering as output realtime image data;
Second filter result output unit, for around current realtime image data, be absent from supersaturation region time, using the filter result of medium filtering as output realtime image data.
7. device according to claim 6, it is characterised in that described filter unit includes:
Vertical filtering module, for carrying out colourity transient state boostfiltering and the medium filtering of vertical direction respectively simultaneously to described realtime image data;
Horizontal filtering module, for the colourity transient state boostfiltering and the medium filtering that carry out horizontal direction through the filtered realtime image data of vertical direction more respectively simultaneously.
8. device according to claim 7, it is characterised in that described vertical filtering module includes:
Vertical chrominance transient state boostfiltering result output module, for at realtime image data when being sized to m m matrix size, U component and the V component of obtaining the realtime image data of described m m matrix size are specifying the maximum realtime image data value in northwards direction and direction to the south on row, and the realtime image data obtaining described m m matrix size is specifying the minimum realtime image data value in northwards direction and direction to the south on row;Wherein, described m > 0;Realtime image data in current location is the maximum realtime image data value in northwards direction or direction to the south, and the realtime image data of current location less than the maximum realtime image data value in direction to the south or northwards direction time, then using the filter result as colourity transient state boostfiltering of the minima on the direction less with the difference of the realtime image data of described current location, otherwise, using the realtime image data of the current location filter result as colourity transient state boostfiltering;The form of described realtime image data is yuv format;
Vertical median-filtered result output module, is specifying the intermediate value on row for obtaining the realtime image data of described m m matrix size, and using filter result as medium filtering of the intermediate value obtained.
9. the device according to claim 6 or 8, it is characterised in that described device includes:
Supersaturation region decision unit, for judging that whether realtime image data in current realtime image data and described current realtime image data preset range is more than default supersaturation threshold value, and the realtime image data in current realtime image data and described current realtime image data preset range more than default supersaturation threshold value time, judge around current realtime image data, there is supersaturation region, otherwise, judging to be absent from supersaturation region around current realtime image data, the form of described realtime image data is yuv format.
10. device according to claim 7, it is characterised in that described horizontal filtering module includes:
Horizontal chroma transient state boostfiltering result output module, for at realtime image data when being sized to N × n matrix size, obtain the U component of the realtime image data of described N × n matrix size and the V component maximum realtime image data value in westwards direction and direction eastwards in nominated bank, and obtain the realtime image data of the described N × n matrix size minimum realtime image data value in westwards direction and direction eastwards in nominated bank;Wherein, described N, n > 0;Realtime image data in current location is the maximum realtime image data value in westwards direction or direction eastwards, and the realtime image data of current location less than the maximum realtime image data value in direction eastwards or westwards direction time, then using the filter result as colourity transient state boostfiltering of the minima on the direction less with the difference of the realtime image data of described current location, otherwise, using the realtime image data of the current location filter result as colourity transient state boostfiltering;The form of described realtime image data is yuv format;
Median level filter result output module, for obtaining realtime image data intermediate value in nominated bank, and using filter result as medium filtering of the intermediate value obtained.
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Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106384118A (en) * | 2016-10-24 | 2017-02-08 | 乐视控股(北京)有限公司 | Method and device for determining degree of dispersion in virtual reality |
CN107833232A (en) * | 2017-10-27 | 2018-03-23 | 智车优行科技(北京)有限公司 | The extracting method and device of image detail, electronic equipment, computer-readable storage medium |
CN107864365A (en) * | 2017-10-31 | 2018-03-30 | 上海集成电路研发中心有限公司 | A kind of method for eliminating image purple boundary |
CN108124141A (en) * | 2017-12-15 | 2018-06-05 | 浙江大华技术股份有限公司 | A kind of image processing method and device |
WO2018130177A1 (en) * | 2017-01-12 | 2018-07-19 | 深圳岚锋创视网络科技有限公司 | Image purple fringe eliminating system, method, computer-readable storage medium, and photographing device |
CN108632583A (en) * | 2017-03-23 | 2018-10-09 | 展讯通信(上海)有限公司 | Digital image processing method and device |
US11399167B2 (en) | 2017-10-19 | 2022-07-26 | Zhejiang Dahua Technology Co., Ltd. | Methods and devices for processing images |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP1480166B1 (en) * | 2003-05-17 | 2006-10-04 | STMicroelectronics Asia Pacific Pte Ltd | An edge enhancement process and system |
CN101779221A (en) * | 2007-08-20 | 2010-07-14 | Nxp股份有限公司 | Method and device for improving chrominance sharpness |
CN102710944A (en) * | 2012-05-16 | 2012-10-03 | 上海高清数字科技产业有限公司 | System and method for synchronously and transiently improving brightness and color |
CN103841428A (en) * | 2012-11-27 | 2014-06-04 | 德克萨斯仪器股份有限公司 | Content adaptive edge and detail enhancement for image and video processing |
-
2016
- 2016-03-15 CN CN201610147461.0A patent/CN105809644B/en active Active
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP1480166B1 (en) * | 2003-05-17 | 2006-10-04 | STMicroelectronics Asia Pacific Pte Ltd | An edge enhancement process and system |
CN101779221A (en) * | 2007-08-20 | 2010-07-14 | Nxp股份有限公司 | Method and device for improving chrominance sharpness |
CN102710944A (en) * | 2012-05-16 | 2012-10-03 | 上海高清数字科技产业有限公司 | System and method for synchronously and transiently improving brightness and color |
CN103841428A (en) * | 2012-11-27 | 2014-06-04 | 德克萨斯仪器股份有限公司 | Content adaptive edge and detail enhancement for image and video processing |
Cited By (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106384118A (en) * | 2016-10-24 | 2017-02-08 | 乐视控股(北京)有限公司 | Method and device for determining degree of dispersion in virtual reality |
WO2018130177A1 (en) * | 2017-01-12 | 2018-07-19 | 深圳岚锋创视网络科技有限公司 | Image purple fringe eliminating system, method, computer-readable storage medium, and photographing device |
US11050985B2 (en) | 2017-01-12 | 2021-06-29 | Arashi Vision Inc. | Image purple fringe eliminating system, method, computer-readable storage medium, and photographing device |
CN108632583A (en) * | 2017-03-23 | 2018-10-09 | 展讯通信(上海)有限公司 | Digital image processing method and device |
CN108632583B (en) * | 2017-03-23 | 2019-10-22 | 展讯通信(上海)有限公司 | Digital image processing method and device |
US11399167B2 (en) | 2017-10-19 | 2022-07-26 | Zhejiang Dahua Technology Co., Ltd. | Methods and devices for processing images |
CN107833232A (en) * | 2017-10-27 | 2018-03-23 | 智车优行科技(北京)有限公司 | The extracting method and device of image detail, electronic equipment, computer-readable storage medium |
CN107833232B (en) * | 2017-10-27 | 2020-10-09 | 智车优行科技(北京)有限公司 | Image detail extraction method and device, electronic equipment and computer storage medium |
CN107864365A (en) * | 2017-10-31 | 2018-03-30 | 上海集成电路研发中心有限公司 | A kind of method for eliminating image purple boundary |
CN107864365B (en) * | 2017-10-31 | 2020-03-31 | 上海集成电路研发中心有限公司 | Method for eliminating purple border of image |
CN108124141A (en) * | 2017-12-15 | 2018-06-05 | 浙江大华技术股份有限公司 | A kind of image processing method and device |
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