CN101212560A - Method for improving video image sharpness point by point - Google Patents

Method for improving video image sharpness point by point Download PDF

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CN101212560A
CN101212560A CNA2007101728001A CN200710172800A CN101212560A CN 101212560 A CN101212560 A CN 101212560A CN A2007101728001 A CNA2007101728001 A CN A2007101728001A CN 200710172800 A CN200710172800 A CN 200710172800A CN 101212560 A CN101212560 A CN 101212560A
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edge
value
noise
fdrequency component
video image
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袁野
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SHANGHAI SUPER VALUE ACTION GROUP CO Ltd
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SHANGHAI SUPER VALUE ACTION GROUP CO Ltd
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Abstract

The invention provides a processing method for point-to-point improving definition of a video image; firstly, a brightness graph of the read video image is calculated; then high and low frequency component are calculated; the high frequency component is divided into a small-amplitude high-frequency noise, a discontinuous noise point, a detail and a large edge; then corresponding processing is carried out to obtain a new high frequency component; finally, a enhanced brightness graph is obtained; by using the method for point-to-point improving definition of the video image of the invention, possible noise can be restricted, enhancement extent of the detail and the edge can be processed point-to-point, which enhances outline and detail of the image and at the same time makes the image softer and more definite.

Description

Pointwise improves the processing method of video image clarity
Technical field
The present invention relates to a kind of processing method that improves video image clarity, specifically, relate to the processing method that a kind of pointwise that is applied to television equipment improves video image clarity.
Background technology
What is called promotes clearness and can be described as sharpening, and purpose is to make fuzzy image become more clear.Why fuzzy video image is, because lost high fdrequency component in signals transmission, from the frequency spectrum angle analysis, image blurring essence is that its high fdrequency component is attenuated, thereby can come picture rich in detail by high-pass filtering exactly.The basic thought that promotes clearness is exactly the radio-frequency component that reasonably improves image.
Enhancing definition algorithm commonly used generally has two kinds, and the differential method and high-pass filtering method are respectively the Processing Algorithm of spatial domain and frequency domain.The spatial domain method is more representational to be had, Laplce's algorithm, and the SOBEL algorithm, methods such as unsharp masking, frequency domain is representational small wave converting method.These methods can both improve the definition of image effectively, but individual common characteristic is arranged, and have also amplified noise in the time of enhancing, also occur tangible white edge sometimes.
Application number provides a kind of method and apparatus that strengthens image definition for 03110774.5 Chinese patent, it is copied into two groups with one group of image, one group is carried out ladder/edge and strengthens, one group is carried out structure and strengthens, be combined into the image that definition improves with two groups by certain way then, this method need be extracted the above video image of two width of cloth, detects dynamic and non-dynamic area then, obtain multiple series of images combination, the computing more complicated of getting up; Application number is that 01800628.0 Chinese patent has proposed a kind of circuit and method that is applied to the enhancing image of television equipment, it has improved the higher shortcoming of executory cost in the prior art, under the situation that does not reduce quality of output signals, reduced cost, remove low pass filter, and provide at least one adjustment unit to adjust high frequency enhancing degree; The weak point of these technical schemes is realization complexity, has ignored The noise, and does not have according to the characteristics processing of the interior pixel of neighborhood on every side with carrying out pointwise.
Summary of the invention
Main purpose of the present invention provides the processing method that a kind of pointwise improves video image clarity, it can suppress possible noise by the character of identification picture element, and the enhancing degree at details and edge is handled in pointwise, when making picture strengthen profile and details, softer exquisiteness.
For achieving the above object, the invention provides the processing method that a kind of pointwise improves video image clarity, it comprises following steps: at first, the video image that reads in is calculated luminance graph; Then, calculate high and low frequency component f H(i, j) and f L(i, j); Subsequently, with high fdrequency component f H(i j) is divided into small size high-frequency noise, discontinuous noise spot, details and big edge, handles accordingly then, obtains new high fdrequency component; At last, obtain luminance graph after the enhancing.
Pointwise of the present invention improves the processing method of video image clarity, and wherein the step that high fdrequency component is divided and handled further comprises: remove tiny noise; The high fdrequency component f that keeps single pixel line H(i j), removes the noise of non-edge point; Calculate pointwise reinforcing coefficient k value.In more detail, the step of removing tiny noise further comprises: set a threshold value, judge described high fdrequency component f H(whether i is j) less than threshold value; If think that then the high fdrequency component less than described threshold value is a noise, with high fdrequency component f H(i j) is changed to 0, to curb small size high-frequency noise.
Pointwise of the present invention improves the processing method of video image clarity, wherein keeps the high fdrequency component f of single pixel line H(i, j) and the step of removing the noise of non-edge point further comprise the high fdrequency component f that judges other H(whether i is j) over half above the template sum; If then think marginal point, otherwise think noise, with high fdrequency component f H(i j) is changed to 0.
Pointwise of the present invention improves the processing method of video image clarity, and the step of wherein calculating pointwise reinforcing coefficient k value further comprises: judge high fdrequency component f H(whether i j) belongs to details obscures district, i.e. T 1＜f H(i, j)≤T 2If,, then the k value is k ( i , j ) = k 1 T 2 - T 1 × f H ( i , j ) - k 1 T 1 T 2 - T 1 ; Judge high fdrequency component f H(whether i j) belongs to detail areas, i.e. T 2＜f H(i, j)≤T 3If,, then the k value is k ( i , j ) = k 3 - k 1 T 3 - T 2 × f H ( i , j ) + k 1 T 3 - k 3 T 2 T 3 - T 2 ; Judge high fdrequency component f H(whether i j) belongs to detail edges district, i.e. T 3＜f H(i, j)≤T 4If,, then the k value is k ( i , j ) = k 2 - k 3 T 4 - T 3 × f H ( i , j ) + k 3 T 4 - k 2 T 3 T 4 - T 3 ; Judge high fdrequency component f H(whether i j) belongs to big marginal zone, i.e. T 4＜f H(i, j)≤T 5If,, then the k value is k ( i , j ) = - k 2 T 5 - T 4 × f H ( i , j ) + k 2 T 5 T 5 - T 4 ; In other cases, the k value be k (i, j)=0; K wherein 1, k 2, k 3Be the amplitude of k value, k 1Be to be hard to tell the details or the gain of noise, this gain should be less; k 2Be the gain that strengthens big edge, the dynamics that the big edge of control chart picture strengthens; k 3Be the gain that strengthens details, the dynamics that the control image detail strengthens; And T 1Be noise threshold; T 2Be the details threshold value, promptly greater than its details thought; T 3Be the little edge threshold of details, promptly less than its details thought, greater than its little edge of thinking; T 4Be edge threshold, promptly less than its little edge of thinking, greater than its big edge of thinking; T 5Be the super large edge threshold,, need not to strengthen greater than its super large thought edge.
Pointwise of the present invention improves the processing method of video image clarity, and the step of wherein obtaining the luminance graph after the enhancing further comprises: the useful signal of thinking edge and details is strengthened judging whether to belong to white edge; If, adjust output brightness value f then to the white edge control and treatment Out(i, j).Wherein, described step to white edge control and treatment and adjustment output brightness is formulated as: f out ( i , j ) = W + f ( i , j ) 2 , Wherein, W is near peaked value, greater than its f in the brightness space Out(i j) then thinks and belongs to white edge.
Adopting pointwise of the present invention to improve the processing method of video image clarity can be according to the content pointwise ground analyzing and processing of video image, at first distinguish the character of pending pixel according to high fdrequency component, be to belong to noise, details, little edge, big edge or super large edge, then according to different attribute, carry out processing in various degree, as belong to noise, then remove; Belong to details or edge, then carry out enhancing in various degree, it can suppress noise, strengthens the expressive ability of details, control crossing of big edge and strengthen, and add white edge control, feasible video pictures after this method strengthens, more clear, softer, there is not the appearance of white edge.
Description of drawings
To the description of a preferred embodiment of the present invention, can further understand purpose, specific structural features and the advantage of its invention by following in conjunction with its accompanying drawing.Wherein, accompanying drawing is:
Fig. 1 is the flow chart of a preferred embodiment of the pointwise of the present invention processing method that improves video image clarity;
Fig. 2 be the pointwise of the present invention processing method that improves video image clarity a preferred embodiment in the k value with f H(i, j) curve synoptic diagram of Bian Huaing.
Embodiment
Following according in conjunction with Fig. 1 and Fig. 2, specify a better embodiment of the present invention.
As shown in Figure 1, improve the schematic flow sheet of a preferred embodiment of the processing method of video image clarity for pointwise of the present invention.
Step S1, the video image that reads in is calculated luminance graph, the N that promptly reads in view data is capable, in order to be illustrated more clearly in the present invention, in the present embodiment, suppose only to handle at gray level image, therefore only need to calculate from video image the luminance graph of gray level image, this brightness can be the Y in the YUV model, the V in the HSV model, and the brightness f that derives of the I in the HIS model or other brightness-formula (i, j).
Step S2 calculates the high and low frequency component, in the present embodiment,, do not need view picture figure is handled because noise and edge all have the local feature, and with N * N template the high and low frequency component f of unit computed image H(i, j) and f L(i, j); Can select rational high pass filter or low pass filter for use, but will guarantee:
f H(i，j)＝f(i，j)-f L(i，j) (1)
Then, to high fdrequency component f H(i j) discerns also enhancement process.
Step S3 sets a threshold value, judges this high fdrequency component f H(whether i is j) less than threshold value; In this way, then proceed to step S4, think that promptly the high fdrequency component less than this threshold value is a noise, f H(i j) is changed to 0, to curb small size high-frequency noise, is formulated as:
f H(i，j)＝0 if|f H(i，j)|≤T 1 (2)
T 1Be noise threshold, optional 0.5～2, select 1 usually for use.
Step S5 keeps the high fdrequency component f of single pixel line H(i j), removes the noise of non-edge point.In the present embodiment, when the line of single pixel passes this template, probably the point that high frequency is bigger in the template seldom, but as long as the high fdrequency component on the diagonal of template center point above certain value, promptly can think has single pixel line to pass through, and keeps its high fdrequency component.Judge other high fdrequency component f H(i, j) whether over half above the template sum, if, then think marginal point, otherwise think noise, proceed to step S6, make high fdrequency component f H(i is 0 j).Can adopt following formulae express:
if(n(i，j)≥N&(|f H(i，j)|＞T s&|f H(i-1，j)|＞T s&|f H(i+1，j)|＞T s)|
(|f H(i，j)|＞T s&|f H(i-1，j-1)|＞T s&|f H(i+1，j+1)|＞T s)|
(|f H(i，j)|＞T s&|f H(i，j-1)|＞T s&|f H(i，j+1)|＞T s)| (3)
(|f H(i，j)|＞T s&|f H(i+1，j-1)|＞T s&|f H(i-1，j+1)|＞T s))
LineFlag＝1
else
LineFlag＝0
Figure S2007101728001D00051
Wherein, T nBe the threshold value that the edge pixel of neighborhood is counted, optional usually (N * N+1)/2; T sFor the high frequency threshold value of single pixel line, select 2 usually; N (i, j) for be the center with this some N * N to put the medium-high frequency component be not 0 picture element number.
Subsequently, calculate pointwise reinforcing coefficient k value, please consult Fig. 2 simultaneously, the k value is with f H(i j) adjusts and can understand in conjunction with Fig. 2.Work as f H(i j) hour, belongs to the noise range, need not strengthen, should denoising, and [T 1, T 2] be the confusion region of details and noise, noise in this way, it is inappropriate choosing bigger enhancing amplitude, the k value should be selected lessly; [T 2, T 3] be detail areas, select big a little k value, can make details more outstanding, [T 3, T 4] be the detail edges district, select big a little k value, [T 4, T 5] be big marginal zone, at this moment the slightly little k value of choosing can prevent that picture from changing too greatly.This k value is chosen mode, makes noise and details transition nature.Here, T 2For the details threshold value, optional 2～4 greater than its details thought, select 2 usually for use.T 3Be the little edge threshold of details, optional 3～5, select 3 usually for use.T 4Be edge threshold, optional 25～30 less than its little edge of thinking greater than its big edge of thinking, select 30 usually for use.T 5Be the super large edge threshold, the super large the thought edge greater than it need not strengthen, and is optional 40～60, selects 50 usually for use.
Step S7 judges f H(whether i j) belongs to details obscures district, if high fdrequency component satisfies T 1＜f H(i, j)≤T 2, then proceed to step S8, choose the k value according to following formula:
k ( i , j ) = k 1 T 2 - T 1 × f H ( i , j ) - k 1 T 1 T 2 - T 1 - - - ( 4 )
Step S9 judges f H(whether i j) belongs to detail areas, if high fdrequency component satisfies T 2＜f H(i, j)≤T 3, then proceed to step S10, choose the k value according to following formula:
k ( i , j ) = k 3 - k 1 T 3 - T 2 × f H ( i , j ) + k 1 T 3 - k 3 T 2 T 3 - T 2 - - - ( 5 )
Step S11 judges f H(whether i j) belongs to the detail edges district, if high fdrequency component satisfies T 3＜f H(i, j)≤T 4, then proceed to step S12, choose the k value according to following formula:
k ( i , j ) = k 2 - k 3 T 4 - T 3 × f H ( i , j ) + k 3 T 4 - k 2 T 3 T 4 - T 3 - - - ( 6 )
Step S13 judges f H(whether i j) belongs to big marginal zone, if high fdrequency component satisfies T 4＜f H(i, j)≤T 5, then proceed to step S14, choose the k value according to following formula:
k ( i , j ) = - k 2 T 5 - T 4 × f H ( i , j ) + k 2 T 5 T 5 - T 4 - - - ( 7 )
Step S15, and in other cases, it is as follows that the k value is chosen mode:
k(i，j)＝0 (8)
K wherein 1, k 2, k 3Be the amplitude of k value, k 1Be the maximum gain in details obscures district, select fixed value 0.5 for use; k 2Be the gain that strengthens big edge, the dynamics that the big edge of control chart picture strengthens, optional 0～1.5, select 1 usually for use; k 3Be the gain that strengthens details, the dynamics that the control image detail strengthens.Optional 1～4, select 2 usually for use.
At last, obtain luminance graph after the enhancing.
Step S16 strengthens the useful signal of thinking edge and details:
f out(i，j)＝f L(i，j)+k(i，j)*f H(i，j) (9)
Step S17 judges whether to belong to white edge, if, then proceed to step S18 to the white edge control and treatment, adjust Fout(i, j) value:
f out ( i , j ) = W + f ( i , j ) 2 - - - ( 10 )
Wherein W be in the brightness space relatively near peaked value, think greater than it we to belong to white edge that in the YcbCr space, W is the value between 200～235; And in the HSV space, W is the value between 220～255; If figure image intensifying degree is too high or intrinsic brightness is just very high, the white edge profile appears possibly, and visual sense feeling is bad, undesirable white edge, i.e. f occur in order to prevent image Out(i, j)＞W, need replacement f Out(i j) makes it to be unlikely to too white.
In sum, the processing method that pointwise of the present invention improves video image clarity can identify noise, thereby noise is not strengthened; Can also carry out enhancing in various degree according to the difference of every some high fdrequency component, therefore can avoid the generation of white edge.
Of particular note, the processing method that pointwise of the present invention improves video image clarity is not limited to step execution sequence defined in the foregoing description, although the present invention is had been described in detail with reference to preferred embodiment, those of ordinary skill in the art is to be understood that, can make amendment or be equal to replacement the present invention, and not breaking away from the spirit and scope of the present invention, it all should be encompassed in the middle of the claim scope of the present invention.

Claims (10)

1. the processing method of a pointwise raising video image clarity is characterized in that, comprises following steps:
The video image that reads in is calculated luminance graph;
Calculate high and low frequency component f H(i, j) and f L(i, j);
With high fdrequency component f H(i j) is divided into small size high-frequency noise, discontinuous noise spot, details and big edge, handles accordingly then, obtains new high fdrequency component;
Obtain the luminance graph after the enhancing.
2. pointwise according to claim 1 improves the processing method of video image clarity, it is characterized in that, wherein to high fdrequency component f H(i, j) step of dividing and handling comprises in more detail:
Remove tiny noise;
The high fdrequency component f that keeps single pixel line H(i j), removes the noise of non-edge point;
Calculate pointwise reinforcing coefficient k value.
3. pointwise according to claim 2 improves the processing method of video image clarity, it is characterized in that the step of wherein removing tiny noise further comprises:
Set a threshold value, judge described high fdrequency component f H(whether i is j) less than threshold value;
If think that then the high fdrequency component less than described threshold value is a noise, with high fdrequency component f H(i j) is changed to 0, to curb small size high-frequency noise.
4. pointwise according to claim 2 improves the processing method of video image clarity, it is characterized in that, wherein keeps the high fdrequency component f of single pixel line H(i, j) and the step of removing the noise of non-edge point further comprise:
Judge other high fdrequency component f H(whether i is j) over half above the template sum;
If then think marginal point, otherwise think noise, with high fdrequency component f H(i j) is changed to 0.
5. pointwise according to claim 2 improves the processing method of video image clarity, it is characterized in that the step of wherein calculating pointwise reinforcing coefficient k value further comprises:
Judge high fdrequency component f H(whether i j) belongs to details obscures district, i.e. T 1＜f H(i, j)≤T 2If,, then the k value is k ( i , j ) = k 1 T 2 - T 1 × f H ( i , j ) - k 1 T 1 T 2 - T 1 ;
Judge high fdrequency component f H(whether i j) belongs to detail areas, i.e. T 2＜f H(i, j)≤T 3If,, then the k value is k ( i , j ) = k 3 - k 1 T 3 - T 2 × f H ( i , j ) + k 1 T 3 - k 3 T 2 T 3 - T 2 ;
Judge high fdrequency component f H(whether i j) belongs to detail edges district, i.e. T 3＜f H(i, j)≤T 4If,, then the k value is k ( i , j ) = k 2 - k 3 T 4 - T 3 × f H ( i , j ) + k 3 T 4 - k 2 T 3 T 4 - T 3 ;
Judge high fdrequency component f H(whether i j) belongs to big marginal zone, i.e. T 4＜f H(i, j)≤T 5If,, then the k value is k ( i , j ) = - k 2 T 5 - T 4 × f H ( i , j ) + k 2 T 5 T 5 - T 4 ;
In other cases, the k value be k (i, j)=0;
K wherein 1, k 2, k 3Be the amplitude of k value, k 1Be to be hard to tell the details or the gain of noise, this gain should be less; k 2Be the gain that strengthens big edge, the dynamics that the big edge of control chart picture strengthens; k 3Be the gain that strengthens details, the dynamics that the control image detail strengthens; And T 1Be noise threshold; T 2Be the details threshold value, promptly greater than its details thought; T 3Be the little edge threshold of details, promptly less than its details thought, greater than its little edge of thinking; T 4Be edge threshold, promptly less than its little edge of thinking, greater than its big edge of thinking; T 5Be the super large edge threshold,, need not to strengthen greater than its super large thought edge.
6. pointwise according to claim 1 improves the processing method of video image clarity, it is characterized in that, the step of wherein obtaining the luminance graph after the enhancing further comprises:
The useful signal of thinking edge and details is strengthened;
Judge whether to belong to white edge;
If, adjust output brightness value f then to the white edge control and treatment Out(i, j).
7. pointwise according to claim 6 improves the processing method of video image clarity, it is characterized in that, described step to white edge control and treatment and adjustment output brightness is formulated as:
f out ( i , j ) = W + f ( i , j ) 2
Wherein, W is near peaked value, greater than its f in the brightness space Out(i j) then thinks and belongs to white edge.
8. pointwise according to claim 7 improves the processing method of video image clarity, it is characterized in that in the YcbCr space, W is the value between 200～235; In the HSV space, W is the value between 220～255.
9. pointwise according to claim 2 improves the processing method of video image clarity, it is characterized in that, keeps the high fdrequency component f of single pixel line H(i j) and remove the step of the noise of non-edge point, can be expressed as with formula:
if(n(i，j)≥N&(|f H(i，j)|＞T 3&|f H(i-1，j)|＞T 3&|f H(i+1，j)|＞T 3)|
(|f H(i，j)|＞T 3&|f H(i-1，j-1)|＞T 3&|f H(i+1，j+1)|＞T 3)|
(|f H(i，j)|＞T 3&|f H(i，j-1)|＞T 3&|f H(i，j+1)|＞T 3)|
(|f H(i，j)|＞T 3&|f H(i+1，j-1)|＞T 3&|f H(i-1，j+1)|＞T 3))
LineFlag＝1
else
LineFlag＝0
Figure S2007101728001C00031
Wherein, T nBe the threshold value that the edge pixel of neighborhood is counted, T 3Be the high frequency threshold value of single pixel line, (i is that (i, j) to put the medium-high frequency component be not 0 picture element number for N * N of the center with some j) to n.
10. pointwise according to claim 9 improves the processing method of video image clarity, it is characterized in that described T nFor (N * N+1)/2.
CNA2007101728001A 2007-12-21 2007-12-21 Method for improving video image sharpness point by point Pending CN101212560A (en)

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Cited By (6)

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CN101706954B (en) * 2009-11-13 2014-10-29 北京中星微电子有限公司 Image enhancement method and device thereof as well as image low frequency component computing method and device thereof
CN104657941A (en) * 2013-11-25 2015-05-27 炬芯（珠海）科技有限公司 Image edge self-adaptive enhancing method and device
CN106127712A (en) * 2016-07-01 2016-11-16 上海联影医疗科技有限公司 Image enchancing method and device
CN107464229A (en) * 2017-08-15 2017-12-12 天津津航技术物理研究所 A kind of infrared image numerical details Enhancement Method for suppressing noise
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Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101706954B (en) * 2009-11-13 2014-10-29 北京中星微电子有限公司 Image enhancement method and device thereof as well as image low frequency component computing method and device thereof
CN104657941A (en) * 2013-11-25 2015-05-27 炬芯（珠海）科技有限公司 Image edge self-adaptive enhancing method and device
CN104657941B (en) * 2013-11-25 2017-08-15 炬芯（珠海）科技有限公司 A kind of image border self-adapting enhancement method and device
US10290108B2 (en) 2015-12-31 2019-05-14 Shanghai United Imaging Healthcare Co., Ltd. Methods and systems for image processing
US11049254B2 (en) 2015-12-31 2021-06-29 Shanghai United Imaging Healthcare Co., Ltd. Methods and systems for image processing
US11880978B2 (en) 2015-12-31 2024-01-23 Shanghai United Imaging Healthcare Co., Ltd. Methods and systems for image processing
CN106127712A (en) * 2016-07-01 2016-11-16 上海联影医疗科技有限公司 Image enchancing method and device
CN106127712B (en) * 2016-07-01 2020-03-31 上海联影医疗科技有限公司 Image enhancement method and device
CN107464229A (en) * 2017-08-15 2017-12-12 天津津航技术物理研究所 A kind of infrared image numerical details Enhancement Method for suppressing noise
CN113344831A (en) * 2021-05-26 2021-09-03 中国农业大学 Image enhancement method and device

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