CN101917624B - Method for reconstructing high resolution video image - Google Patents
Method for reconstructing high resolution video image Download PDFInfo
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- CN101917624B CN101917624B CN 201010238674 CN201010238674A CN101917624B CN 101917624 B CN101917624 B CN 101917624B CN 201010238674 CN201010238674 CN 201010238674 CN 201010238674 A CN201010238674 A CN 201010238674A CN 101917624 B CN101917624 B CN 101917624B
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Abstract
The invention discloses a method for reconstructing a high resolution video image, comprising the following steps: inputting a video image sequence; interpolating the input video image sequence; establishing a motion vector set for interpolated points in the interpolated video image sequence; acquiring motion compensation weight numbers and weighted motion compensation values of the interpolated points for each motion vector in the motion vector set; accumulating the motion compensation weight numbers and the weighted motion compensation values corresponding to the motion vector set of the interpolated points to acquire accumulative total value of motion compensation weight number; normalizing the accumulative total value of the weighted motion compensation values of the interpolated points by the accumulative total value of motion compensation weight number so as to acquire pixel values of the interpolated points; and outputting the interpolated high resolution video image after the interpolation result satisfies the requirement on super resolution video image quality. The method of the invention has strong robustness on shielding and cover and other phenomena in the video and can be applied to the fields, such as reconstruction of the high resolution video image and the like.
Description
Technical field
The present invention relates to the computer image processing technology field, particularly a kind of method for reconstructing high resolution video image that becomes spatial filter based on non local mean time.
Background technology
The high resolution image reconstruction method is rebuild with single width or multiple image exactly and is obtained high-resolution image.It is to utilize the image of several low resolution to recover high-resolution image that the method that has much existed is arranged.But existing high resolution image reconstruction method generally all needs moving target is carried out accurately estimation, is a very difficult job but localized region carries out high-precision estimation, especially in the situation that existence is blocked and noise.
Summary of the invention
Purpose of the present invention is intended to solve at least above-mentioned technological deficiency, has proposed especially a kind of method for reconstructing high resolution video image that becomes spatial filter based on non local mean time.
For achieving the above object, one aspect of the present invention proposes a kind of method for reconstructing high resolution video image, may further comprise the steps: the inputted video image sequence; Described sequence of video images to input carries out interpolation; To being set up the motion vector collection by the difference point in the described sequence of video images of interpolation; To each motion vector that described motion vector is concentrated, obtain motion compensation weights and the weighted motion compensated value of interpolated point; Accumulate described interpolated point corresponding to the motion compensation weights of motion vector collection and weighted motion compensated value to obtain motion compensation weights aggregate-value; Adopt the aggregate-value of the weighted motion compensated value of the described interpolated point of motion compensation weights aggregate-value normalization, obtain the pixel value of described interpolated point; After interpolation result satisfies the requirement of super-resolution video image quality, the high resolution video image after the output interpolation.
Method of the present invention has very strong robustness to the phenomenons such as covering of blocking that occur in the video, can be used for the fields such as reconstructing high resolution video image.
The aspect that the present invention adds and advantage in the following description part provide, and part will become obviously from the following description, or recognize by practice of the present invention.
Description of drawings
Above-mentioned and/or the additional aspect of the present invention and advantage are from obviously and easily understanding becoming the description of embodiment below in conjunction with accompanying drawing, wherein:
Fig. 1 is the method for reconstructing high resolution video image flow chart based on non local mean time change spatial filter of the embodiment of the invention.
Embodiment
The below describes embodiments of the invention in detail, and the example of described embodiment is shown in the drawings, and wherein same or similar label represents same or similar element or the element with identical or similar functions from start to finish.Be exemplary below by the embodiment that is described with reference to the drawings, only be used for explaining the present invention, and can not be interpreted as limitation of the present invention.
Because the present invention does not need explicit estimation, its motion estimation and compensation form by implicit expression is recovered high-resolution video image simultaneously, therefore the present invention can effectively avoid complicated estimation, can consider fully for the correlation between the image of interpolation simultaneously.
As shown in Figure 1, the method for reconstructing high resolution video image flow chart based on non local mean time change spatial filter for the embodiment of the invention may further comprise the steps:
Step S101, the inputted video image sequence.
Step S102 carries out interpolation to the sequence of video images of inputting.In an embodiment of the present invention, can adopt the methods such as existing bilinearity, bicubic spline that the sequence of video images of inputting is carried out interpolation.
Step S103 sets up the motion vector collection to the interpolated point in the sequence of video images of interpolation.Specifically comprise:
Two field picture with current interpolation in the video flowing is designated as current frame image I
t, t is the frame label of current frame image in video flowing, and motion vector collection V (x, y, u, v, j) is set up in all interpolated points of present image, and wherein, (x, y) is the coordinate of interpolated point, and (u, v, j) is corresponding to this motion of point vector.
Step S104 to each motion vector, obtains motion compensation weights and the weighted motion compensated value of interpolated point.Specifically comprise:
At first, weights normalization coefficient and the equal assignment of non-normalized filtered value with interpolated point coordinate place is 0.Region of search shape W, comparison domain shape B, nuclear width h are set and calculate the norm parameter p according to the incoming frame sequence again.In one embodiment of the invention, the shape of region of search can be set to sphere, cylinder, circle, arbitrary polyhedron or arbitrary polygon.
Then, calculate under current motion vector (u, v, j) zone centered by (x, y, t) and the distance between the interregional pixel value centered by (x+u, y+v, t+j) by following formula:
S(x，y，u，v，j)＝||B(x，y，t)-B(x+u，y+v，t+j)||
p。
At last, calculate under current motion vector (u, v, j) the motion compensation weights at coordinate place, present frame interpolated point by following formula:
Step S105, the accumulation interpolated point corresponding to the motion compensation weights of motion vector collection and weighted motion compensated value to obtain motion compensation weights aggregate-value.
Step S106, the aggregate-value of the weighted motion compensated value of employing motion compensation weights aggregate-value normalization interpolated point, the pixel value of acquisition interpolated point.Specifically comprise:
At first, calculate corresponding under the motion vector (u, v, j) by following formula, the weights normalization coefficient at (x, y) coordinate place: a (x, y)=a (x, y)+ω (x, y, u, v, j), wherein, a (x, y) is normalization coefficient.
Then, under current biasing coordinate and analogy image label j, upgrade the non-normalized filtered value at each coordinate place of current frame image by following formula:
Wherein,
Be the value after the non-normalized processing, I
T+jIt is the t+j frame image information;
At last, the region of search coordinate that current biasing coordinate is corresponding is masked as to be processed, and calculates the value of current frame image after the normalized of current interpolation coordinate points by following formula:
Step S107 judges whether interpolation result satisfies the requirement of super-resolution video image quality.If judge to meet the demands then execution in step S108, do not meet the demands then execution in step S104 if judge.
Step S108, the high resolution video image after the output interpolation.
Method of the present invention has very strong robustness to the phenomenons such as covering of blocking that occur in the video, can be used for the fields such as reconstructing high resolution video image.
Although illustrated and described embodiments of the invention, for the ordinary skill in the art, be appreciated that without departing from the principles and spirit of the present invention and can carry out multiple variation, modification, replacement and modification to these embodiment, scope of the present invention is by claims and be equal to and limit.
Claims (3)
1. a method for reconstructing high resolution video image is characterized in that, may further comprise the steps:
The inputted video image sequence;
Described sequence of video images to input carries out interpolation;
The motion vector collection is set up in interpolated point in the described sequence of video images of interpolation, wherein, comprising:
Two field picture with current interpolation in the video flowing is designated as current frame image I
t, wherein, t is the frame label of current frame image in video flowing; With
Motion vector collection V (x, y, u, v, j) is set up in all interpolated points of present image, and wherein, (x, y) is the coordinate of interpolated point, and (u, v, j) is corresponding to this motion of point vector;
To each motion vector that described motion vector is concentrated, obtain motion compensation weights and the weighted motion compensated value of interpolated point;
Accumulate described interpolated point corresponding to the motion compensation weights of motion vector collection and weighted motion compensated value to obtain motion compensation weights aggregate-value, wherein, comprising:
Weights normalization coefficient and the equal assignment of non-normalized filtered value at interpolated point coordinate place are initially 0;
Region of search shape W, comparison domain shape B, nuclear width h are set and calculate the norm parameter p according to the incoming frame sequence;
Calculate under current motion vector (u, v, j) by following formula, the zone centered by (x, y, t) with the distance between (x+u, y+v, t+j) interregional pixel value:
S (x, y, u, v, j)=|| B (x, y, t)-B (x+u, y+v, t+j) ||
pWith
Calculate under current motion vector (u, v, j) the motion compensation weights at coordinate place, present frame interpolated point by following formula:
Adopt the aggregate-value of the weighted motion compensated value of the described interpolated point of described motion compensation weights aggregate-value normalization, obtain the pixel value of described interpolated point;
After interpolation result satisfies the requirement of high resolution video image quality, the high resolution video image after the output interpolation.
2. method for reconstructing high resolution video image as claimed in claim 1 is characterized in that, described region of search be shaped as sphere, cylinder, circle, polyhedron or polygon.
3. method for reconstructing high resolution video image as claimed in claim 1 is characterized in that, the aggregate-value of the weighted motion compensated value of described employing motion compensation weights aggregate-value normalization interpolated point, and the pixel value that obtains the interpolated point further comprises:
By the weights normalization coefficient of following formula calculating corresponding to (x, y) coordinate place under the motion vector (u, v, j): a (x, y)=a (x, y)+ω (x, y, u, v, j), wherein, a (x, y) is normalization coefficient;
Under current biasing coordinate and analogy image label j, upgrade the non-normalized filtered value at each coordinate place of current frame image by following formula:
Wherein,
Be the value after the non-normalized processing, I
T+jIt is the t+j frame image information; With
The region of search coordinate that current biasing coordinate is corresponding is masked as to be processed, and calculates the value of current frame image after the normalized of current interpolation coordinate points by following formula:
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| CN102905138A (en) * | 2011-07-27 | 2013-01-30 | 苏州科雷芯电子科技有限公司 | High-resolution reconstruction method of video |
| CN103167218B (en) * | 2011-12-14 | 2016-04-06 | 北京大学 | A kind of super resolution ratio reconstruction method based on non-locality and equipment |
| CN103458154B (en) * | 2012-05-31 | 2016-03-30 | 北京大学 | A kind of super-resolution method of video and device |
| CN104182931B (en) * | 2013-05-21 | 2017-04-26 | 北京大学 | Super resolution method and device |
| CN103500445B (en) * | 2013-09-22 | 2016-05-04 | 华南理工大学 | A kind of super-resolution processing method of color video |
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| EP1237377A2 (en) * | 1997-06-09 | 2002-09-04 | Hitachi, Ltd. | Image decoding |
| CN1874499A (en) * | 2006-05-12 | 2006-12-06 | 北京理工大学 | High dynamic equipment for reconstructing image in high resolution |
| CN101489031A (en) * | 2009-01-16 | 2009-07-22 | 西安电子科技大学 | Adaptive frame rate up-conversion method based on motion classification |
| CN101674478A (en) * | 2009-10-19 | 2010-03-17 | 浙江大学 | Video super-resolution method based on compressed domain |
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| US8406569B2 (en) * | 2009-01-19 | 2013-03-26 | Sharp Laboratories Of America, Inc. | Methods and systems for enhanced dynamic range images and video from multiple exposures |
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|---|---|---|---|---|
| EP1237377A2 (en) * | 1997-06-09 | 2002-09-04 | Hitachi, Ltd. | Image decoding |
| CN1874499A (en) * | 2006-05-12 | 2006-12-06 | 北京理工大学 | High dynamic equipment for reconstructing image in high resolution |
| CN101489031A (en) * | 2009-01-16 | 2009-07-22 | 西安电子科技大学 | Adaptive frame rate up-conversion method based on motion classification |
| CN101674478A (en) * | 2009-10-19 | 2010-03-17 | 浙江大学 | Video super-resolution method based on compressed domain |
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