CN105872397A - Single frame wide dynamic enhancement method and system capable of automatically identifying bright area and dark area - Google Patents
Single frame wide dynamic enhancement method and system capable of automatically identifying bright area and dark area Download PDFInfo
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- CN105872397A CN105872397A CN201610203548.5A CN201610203548A CN105872397A CN 105872397 A CN105872397 A CN 105872397A CN 201610203548 A CN201610203548 A CN 201610203548A CN 105872397 A CN105872397 A CN 105872397A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/70—Circuitry for compensating brightness variation in the scene
- H04N23/741—Circuitry for compensating brightness variation in the scene by increasing the dynamic range of the image compared to the dynamic range of the electronic image sensors
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
- H04N25/60—Noise processing, e.g. detecting, correcting, reducing or removing noise
- H04N25/63—Noise processing, e.g. detecting, correcting, reducing or removing noise applied to dark current
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Abstract
The invention discloses a single frame wide dynamic enhancement method and system capable of automatically identifying a bright area and a dark area. The method comprises following steps of capturing each frame of image in video streaming; and carrying out following steps of S1, adjusting a low brightness area; S2, adjusting a high brightness area; and S3, intelligent fusion, on each frame of image. According to the method and the system, method modification is carried out on the existing single frame wide dynamic technique. According to the actual measurement, in a wide dynamic scene, both the dark area and the bright area can be adjusted; and especially, the processing effect on the bright area is relatively clear. Partial operators are realized by table look-up, therefore, the operation steps are reduced, and automatic calculation of fusion parameters is suitable for engineering realization. Compared with the prior art, the method and the system have the advantages that the high brightness area is adjusted clearly; the method and the system are suitable for processing both a relatively dark scene and a relatively bright scene; the principle is simple; the hardware realization is convenient; and the intelligent fusion is realized with parameter adjustment.
Description
Technical field
The present invention relates to a kind of automatic identification clear zone and the dynamic Enhancement Method of single frames width of dark space and system.
Background technology
It is integrated with single frames width dynamic adjustment algorithm inside current most of soc chip, but most of soc adjustment algorithm is the most right
Dark space is adjusted, and adjusts clear zone not quite or does not has clear improvement, it is impossible to meeting actual application environment complicated and changeable, especially
It is in scene alternately bright, dark, it may appear that over-exposed cause image information to be lost.The method of adjustment purpose of the present invention be into
One step promotes the details in clear zone in wide dynamic scene, does prior art the most perfect.
Summary of the invention
It is an object of the invention to overcome the deficiencies in the prior art, it is provided that the single frames width of a kind of automatic identification clear zone and dark space dynamically increases
Strong method and system, design clear zone and dark space adjustment framework, clear zone adjustment algorithm, generation look-up method and clear zone and dark space are certainly
Dynamic recognition methods.
It is an object of the invention to be achieved through the following technical solutions: the single frames width of a kind of automatic identification clear zone and dark space dynamically increases
Strong method, captures each two field picture img in video streaming, and each two field picture carries out following steps:
S1: adjust low brightness area, including following sub-step:
S11: take the minima of original image img each pixel color component, the result obtained is designated as minRGB1；
S12: negated by the minRGB1 obtained in step S11, it may be assumed that 255-minRGB1, the result obtained is designated as
MminRGB1；
S13: the MminRGB1 obtained in step S12 is substituted into two-sided filter, and result is designated as bf1；
S14: result step S13 obtained is tabled look-up, and result is designated as lookbf1；Wherein, the generation of form is according to as follows
Mode generates:
E1=a(b-x)./b
Table=ye1
In formula, a, b are adjustable parameter；E1 is intermediate object program, and table is the form generated, and the value of x, y is respectively as follows:
X=0,1,2,3 ... 255
Y=0,1,2,3 ... 255；
Owing to denominator can not be 0, therefore, 0 in y is modified to 1 and substitutes into calculating again；
S2: adjust high-brightness region, including following sub-step:
S21: being negated by original image img, result is designated as img2, it may be assumed that img2=255-img；
S22: in the result images that will obtain in step S21, each pixel takes color component minima, result is designated as min2；
S23: result step S22 obtained negates, and result is designated as Mmin2, i.e. Mmin2=255-min2；
S24: the two-sided filter that result step S23 obtained substitutes into, result is designated as bf2；
S25: result step S24 obtained is tabled look-up, and result is designated as lookbf2；Wherein, the generation of form is according to step
The mode of S14 produces；
S26: result step S25 obtained negates, result is designated as M lookbf2, i.e. M lookbf2=255-lookbf2；
S3: Intelligent Fusion, result Mlookbf2 result lookbf1 produced in step S1 and step S2 produced is according to such as
Under type merges:
Out=m lookbf1+ (1-m) Mlookbf2；
In formula, out is fusion results, and m is fusion parameters, and span is [0,1], and when m is less, main adjustment is highlighted
Region；When m is bigger, adjust low brightness area.
In step S1, the span of a is [1,5], and the span of b is [1,255].
Interval less for described m be [0,0.5), interval less for described m is [0.5,1].
Described step S3 includes following sub-step:
S31: detection clear zone: the minRGB1 of step S11 is substituted into below equation and calculates, obtain high luminance area area image o (x, y):
O (x, y)=1/ (1+r (x, y)-z)；
In formula, (x y) represents that (z is parameter to pixel for x, the value of minRGB1 y) at coordinate to r；Then high-brightness region is traveled through
Image o (x, y), to each pixel o (x, y) carries out binary conversion treatment: when L (x, y) value more than or equal to M time, o ' (x, y)=1,
When L (x, y) value less than M time, o ' (x, y)=0, it may be assumed that
In formula, (x, y) is binary image to o ', and M is the average of image minRGB1, and acquiring method is cumulative minRGB1
The all pixel values of image, then the number of pixels divided by minRGB1 image；
S32: reference area: (x, y) all pixel values of image add up, and the result obtained is designated as k ', k ' for image highlight bar by o '
The area in territory；If minRGB1 image pixel number is k ", then calculating clear zone accounts for the ratio of minRGB1 image size is t:
T=k '/k "；
S33: calculate average: by step S31 obtains clear zone binary image o ' (x, y) with minRGB1 image respective pixel
Point is multiplied, and the result obtained is designated as o " (x, y), it may be assumed that
O " (x, y)=minRGB1 o ' (x, y)；
By o, " (x, y) all pixel values of image add up, and the result obtained is designated as k, calculate minRGB1 image according to below equation
Clear zone average M ':
M '=k/k '；
S34: determine fusion parameters m:
(1) when clear zone average M ' is more than or equal to first threshold P, fusion parameters m choose by detection clear zone decision: when
When bright area area accounts for ratio t of total image area more than Q%, mainly adjust bright area, adjust parameter m and take X, X
More than 0.5；Otherwise take 0；
(2) when clear zone average M ' is less than first threshold P, mainly adjusting dark areas, fusion parameters m takes 1；
S35: Intelligent Fusion: the lookbf1 obtained in fusion parameters m that step S34 is obtained, step S1 and step S2
In the Mlookbf2 that obtains substitute into below equation and merge:
Out=m lookbf1+ (1-m) Mlookbf2；
Wherein, out is fusion results, and m is calculated fusion parameters.
The value of described first threshold P is 200, and the value of Q is 40, and the value of X is 0.6, and the value of z takes 10.
The single frames width of a kind of automatic identification clear zone and dark space dynamically strengthens system, including:
Picture frame acquisition module: for each two field picture in settlement in video streaming；
Low brightness area adjusting module: for being adjusted low brightness area, including capture vegetarian refreshments minima being sequentially connected with
Modules A, negate submodule A, bilateral filtering submodule A and the submodule A that tables look-up；The described submodule A that tables look-up includes that table generates
Unit A and table query unit A；
High-brightness region adjusting module: for being adjusted high-brightness region, negates submodule B including be sequentially connected with, take
Pixel minima submodule B, negate submodule C, bilateral filtering submodule B, table look-up submodule B and negate submodule D；
The described submodule B that tables look-up includes table signal generating unit B and table query unit B；
Intelligent Fusion module: the knot that the result for being produced by low brightness area adjusting module produces with high-brightness region adjusting module
Fruit carries out Intelligent Fusion.
Brightness detection sub-module that described Intelligent Fusion module includes being sequentially connected with, areal calculation submodule, mean value computation submodule
Block, fusion parameters determine submodule and Intelligent Fusion submodule.
The invention has the beneficial effects as follows:
The present invention is the improvement doing in method to existing single frames width dynamic technique, through actual measurement, in wide dynamic scene, it is possible to right
Dark areas and bright area all adjust, especially the process to bright area, and effect is more apparent.Part operator uses realization of tabling look-up,
Decreasing calculation step, automatically calculating of fusion parameters is suitable for through engineering approaches realization.Compared with prior art, there is following advantage:
(1) highlight regions is adjusted substantially；(2) it is suitable for the process of relatively dark scene, also is adapted for the process of relatively bright field scape；(3) principle letter
Single, facilitate hardware to realize；(4) Intelligent Fusion, printenv regulates.
Accompanying drawing explanation
Fig. 1 is the inventive method flow chart.
Detailed description of the invention
Technical scheme is described in further detail below in conjunction with the accompanying drawings: automatically identify that clear zone is with dark as it is shown in figure 1, a kind of
The dynamic Enhancement Method of single frames width in district, captures each two field picture img in video streaming, and each two field picture carries out following steps:
S1: adjust low brightness area, including following sub-step:
S11: take the minima of original image img each pixel color component, the result obtained is designated as minRGB1；
S12: negated by the minRGB1 obtained in step S11, it may be assumed that 255-minRGB1, the result obtained is designated as
MminRGB1；
S13: the MminRGB1 obtained in step S12 is substituted into two-sided filter, and result is designated as bf1；
S14: result step S13 obtained is tabled look-up, and result is designated as lookbf1；Wherein, the generation of form is according to as follows
Mode generates:
E1=a(b-x)./b
Table=ye1
In formula, a, b are adjustable parameter；E1 is intermediate object program, and table is the form generated, and the value of x, y is respectively as follows:
X=0,1,2,3 ... 255
Y=0,1,2,3 ... 255；
Owing to denominator can not be 0, therefore, 0 in y is modified to 1 and substitutes into calculating again；
S2: adjust high-brightness region, including following sub-step:
S21: being negated by original image img, result is designated as img2, it may be assumed that img2=255-img；
S22: in the result images that will obtain in step S21, each pixel takes color component minima, result is designated as min2；
S23: result step S22 obtained negates, and result is designated as Mmin2, i.e. Mmin2=255-min2；
S24: the two-sided filter that result step S23 obtained substitutes into, result is designated as bf2；
S25: result step S24 obtained is tabled look-up, and result is designated as lookbf2；Wherein, the generation of form is according to step
The mode of S14 produces；
S26: result step S25 obtained negates, result is designated as M lookbf2, i.e. M lookbf2=255-lookbf2；
S3: Intelligent Fusion, result Mlookbf2 result lookbf1 produced in step S1 and step S2 produced is according to such as
Under type merges:
Out=m lookbf1+ (1-m) Mlookbf2；
In formula, out is fusion results, and m is fusion parameters, and span is [0,1], and when m is less, main adjustment is highlighted
Region；When m is bigger, adjust low brightness area.
In step S1, the span of a is [1,5], and the span of b is [1,255].
Interval less for described m be [0,0.5), interval less for described m is [0.5,1].
Described step S3 includes following sub-step:
S31: detection clear zone: the minRGB1 of step S11 is substituted into below equation and calculates, obtain high luminance area area image o (x, y):
O (x, y)=1/ (1+r (x, y)-z)；
In formula, (x y) represents that (z is parameter to pixel for x, the value of minRGB1 y) at coordinate to r；Then high-brightness region is traveled through
Image o (x, y), to each pixel o (x, y) carries out binary conversion treatment: when L (x, y) value more than or equal to M time, o ' (x, y)=1,
When L (x, y) value less than M time, o ' (x, y)=0, it may be assumed that
In formula, (x, y) is binary image to o ', and M is the average of image minRGB1, and acquiring method is cumulative minRGB1
The all pixel values of image, then the number of pixels divided by minRGB1 image；
S32: reference area: (x, y) all pixel values of image add up, and the result obtained is designated as k ', k ' for image highlight bar by o '
The area in territory；If minRGB1 image pixel number is k ", then calculating clear zone accounts for the ratio of minRGB1 image size is t:
T=k '/k "；
S33: calculate average: by step S31 obtains clear zone binary image o ' (x, y) with minRGB1 image respective pixel
Point is multiplied, and the result obtained is designated as o " (x, y), it may be assumed that
O " (x, y)=minRGB1 o ' (x, y)；
By o, " (x, y) all pixel values of image add up, and the result obtained is designated as k, calculate minRGB1 image according to below equation
Clear zone average M ':
M '=k/k '；
S34: determine fusion parameters m:
(1) when clear zone average M ' is more than or equal to first threshold P, fusion parameters m choose by detection clear zone decision: when
When bright area area accounts for ratio t of total image area more than Q%, mainly adjust bright area, adjust parameter m and take X, X
More than 0.5；Otherwise take 0；
(2) when clear zone average M ' is less than first threshold P, mainly adjusting dark areas, fusion parameters m takes 1；
S35: Intelligent Fusion: the lookbf1 obtained in fusion parameters m that step S34 is obtained, step S1 and step S2
In the Mlookbf2 that obtains substitute into below equation and merge:
Out=m lookbf1+ (1-m) Mlookbf2；
Wherein, out is fusion results, and m is calculated fusion parameters.
The value of described first threshold P is 200, and the value of Q is 40, and the value of X is 0.6, and the value of z takes 10.
The single frames width of a kind of automatic identification clear zone and dark space dynamically strengthens system, corresponding with method, including:
Picture frame acquisition module: for each two field picture in settlement in video streaming；
Low brightness area adjusting module: for being adjusted low brightness area, including capture vegetarian refreshments minima being sequentially connected with
Modules A, negate submodule A, bilateral filtering submodule A and the submodule A that tables look-up；The described submodule A that tables look-up includes that table generates
Unit A and table query unit A；
High-brightness region adjusting module: for being adjusted high-brightness region, negates submodule B including be sequentially connected with, take
Pixel minima submodule B, negate submodule C, bilateral filtering submodule B, table look-up submodule B and negate submodule D；
The described submodule B that tables look-up includes table signal generating unit B and table query unit B；
Intelligent Fusion module: the knot that the result for being produced by low brightness area adjusting module produces with high-brightness region adjusting module
Fruit carries out Intelligent Fusion.
Brightness detection sub-module that described Intelligent Fusion module includes being sequentially connected with, areal calculation submodule, mean value computation submodule
Block, fusion parameters determine submodule and Intelligent Fusion submodule.
The key point of the present invention:
1, image highlight area reverse process method；
2, the method generating form；
3, the computational methods of fusion parameters.
Claims (7)
1. an automatic identification clear zone and the dynamic Enhancement Method of single frames width of dark space, it is characterised in that: capture each frame figure in video streaming
As img, each two field picture is carried out following steps:
S1: adjust low brightness area, including following sub-step:
S11: take the minima of original image img each pixel color component, the result obtained is designated as minRGB1；
S12: negated by the minRGB1 obtained in step S11, it may be assumed that 255-minRGB1, the result obtained is designated as MminRGB1；
S13: the MminRGB1 obtained in step S12 is substituted into two-sided filter, and result is designated as bf1；
S14: result step S13 obtained is tabled look-up, and result is designated as lookbf1；Wherein, the generation of form is as follows
Generate:
E1=a(b-x)./b
Table=ye1
In formula, a, b are adjustable parameter；E1 is intermediate object program, and table is the form generated, and the value of x, y is respectively as follows:
X=0,1,2,3 ... 255
Y=0,1,2,3 ... 255；
Owing to denominator can not be 0, therefore, 0 in y is modified to 1 and substitutes into calculating again；
S2: adjust high-brightness region, including following sub-step:
S21: being negated by original image img, result is designated as img2, it may be assumed that img2=255-img；
S22: in the result images that will obtain in step S21, each pixel takes color component minima, result is designated as min2；
S23: result step S22 obtained negates, and result is designated as Mmin2, i.e. Mmin2=255-min2；
S24: the two-sided filter that result step S23 obtained substitutes into, result is designated as bf2；
S25: result step S24 obtained is tabled look-up, and result is designated as lookbf2；Wherein, the generation of form is according to step S14
Mode produce；
S26: result step S25 obtained negates, result is designated as M lookbf2, i.e. M lookbf2=255-lookbf2；
S3: Intelligent Fusion, result Mlookbf2 result lookbf1 produced in step S1 and step S2 produced is according to such as lower section
Formula merges:
Out=m lookbf1+ (1-m) Mlookbf2；
In formula, out is fusion results, and m is fusion parameters, and span is [0,1], when m is less, mainly adjusts highlight regions；
When m is bigger, adjust low brightness area.
A kind of automatic identification clear zone the most according to claim 1 and the dynamic Enhancement Method of single frames width of dark space, it is characterised in that: step
In rapid S1, the span of a is [1,5], and the span of b is [1,255].
A kind of automatic identification clear zone the most according to claim 1 and the dynamic Enhancement Method of single frames width of dark space, it is characterised in that: institute
The interval less for m stated for [0,0.5), interval less for described m is [0.5,1].
A kind of automatic identification clear zone the most according to claim 1 and the dynamic Enhancement Method of single frames width of dark space, it is characterised in that: institute
Step S3 stated includes following sub-step:
S31: detection clear zone: the minRGB1 of step S11 is substituted into below equation and calculates, obtain high luminance area area image o (x, y):
O (x, y)=1/ (1+r (x, y)-z)；
In formula, (x y) represents that (z is parameter to pixel for x, the value of minRGB1 y) at coordinate to r；Then traversal high luminance area area image
O (x, y), to each pixel o (x, y) carries out binary conversion treatment: when L (x, y) value more than or equal to M time, o ' (x, y)=1,
When L (x, y) value less than M time, o ' (x, y)=0, it may be assumed that
In formula, (x, y) is binary image to o ', and M is the average of image minRGB1, and acquiring method is cumulative minRGB1 image
All pixel values, then the number of pixels divided by minRGB1 image；
S32: reference area: (x, y) all pixel values of image add up, and the result obtained is designated as k ', k ' for image highlight area by o '
Area；If minRGB1 image pixel number is k ", then calculating clear zone accounts for the ratio of minRGB1 image size is t:
T=k '/k "；
S33: calculate average: (x, y) with minRGB1 image corresponding pixel points phase by the clear zone binary image o ' that obtains in step S31
Taking advantage of, the result obtained is designated as o " (x, y), it may be assumed that
O " (x, y)=minRGB1 o ' (x, y)；
By o, " (x, y) all pixel values of image add up, and the result obtained is designated as k, calculate the bright of minRGB1 image according to below equation
District average M ':
M '=k/k '；
S34: determine fusion parameters m:
(1) when clear zone average M ' is more than or equal to first threshold P, choosing by the decision in detection clear zone of fusion parameters m: work as clear zone
When territory area accounts for ratio t of total image area more than Q%, mainly adjusting bright area, adjustment parameter m takes X, X and is more than
0.5；Otherwise take 0；
(2) when clear zone average M ' is less than first threshold P, mainly adjusting dark areas, fusion parameters m takes 1；
S35: Intelligent Fusion: in the lookbf1 obtained in fusion parameters m that step S34 is obtained, step S1 and step S2
To Mlookbf2 substitute into below equation merge:
Out=m lookbf1+ (1-m) Mlookbf2；
Wherein, out is fusion results, and m is calculated fusion parameters.
A kind of automatic identification clear zone the most according to claim 4 and the dynamic Enhancement Method of single frames width of dark space, it is characterised in that: institute
The value of first threshold P stated is 200, and the value of Q is 40, and the value of X is 0.6, and the value of z takes 10.
6. the single frames width of a kind of automatic identification clear zone as described in any one in Claims 1 to 5 and dark space dynamically strengthens system, and it is special
Levy and be: including:
Picture frame acquisition module: for each two field picture in settlement in video streaming；
Low brightness area adjusting module: for low brightness area being adjusted, including the capture vegetarian refreshments minima submodule being sequentially connected with
A, negate submodule A, bilateral filtering submodule A and the submodule A that tables look-up；It is single that the described submodule A that tables look-up includes that table generates
Unit A and table query unit A；
High-brightness region adjusting module: for being adjusted high-brightness region, negates submodule B, capture element including be sequentially connected with
Point minima submodule B, negate submodule C, bilateral filtering submodule B, table look-up submodule B and negate submodule D；Institute
The submodule B that tables look-up stated includes table signal generating unit B and table query unit B；
Intelligent Fusion module: for the result that low brightness area adjusting module produces is entered with the result that high-brightness region adjusting module produces
Row Intelligent Fusion.
A kind of automatic identification clear zone the most according to claim 6 and the dynamic Enhancement Method of single frames width of dark space, it is characterised in that: institute
The Intelligent Fusion module stated includes the brightness detection sub-module being sequentially connected with, areal calculation submodule, mean value computation submodule, melts
Close parameter determination submodule and Intelligent Fusion submodule.
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Application publication date: 20160817 |