CN105704398A - Video processing method - Google Patents
Video processing method Download PDFInfo
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- CN105704398A CN105704398A CN201610153366.1A CN201610153366A CN105704398A CN 105704398 A CN105704398 A CN 105704398A CN 201610153366 A CN201610153366 A CN 201610153366A CN 105704398 A CN105704398 A CN 105704398A
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- 238000003672 processing method Methods 0.000 title abstract 2
- 238000000034 method Methods 0.000 claims abstract description 36
- 238000012545 processing Methods 0.000 claims abstract description 23
- 230000000694 effects Effects 0.000 claims abstract description 9
- 230000008569 process Effects 0.000 claims description 18
- 230000002123 temporal effect Effects 0.000 claims description 9
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 230000006835 compression Effects 0.000 claims description 3
- 238000007906 compression Methods 0.000 claims description 3
- 238000012937 correction Methods 0.000 claims description 3
- 238000005530 etching Methods 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 3
- 238000013507 mapping Methods 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 3
- 238000012217 deletion Methods 0.000 abstract 1
- 230000037430 deletion Effects 0.000 abstract 1
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 1
Classifications
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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
- H04N23/95—Computational photography systems, e.g. light-field imaging systems
- H04N23/951—Computational photography systems, e.g. light-field imaging systems by using two or more images to influence resolution, frame rate or aspect ratio
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformation in the plane of the image
- G06T3/60—Rotation of a whole image or part thereof
- G06T3/608—Skewing or deskewing, e.g. by two-pass or three-pass rotation
-
- G06T5/73—
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/85—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using pre-processing or post-processing specially adapted for video compression
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/222—Studio circuitry; Studio devices; Studio equipment
- H04N5/262—Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
- H04N5/2628—Alteration of picture size, shape, position or orientation, e.g. zooming, rotation, rolling, perspective, translation
Abstract
The invention discloses a video processing method. The method comprises the following steps: an acquired video file is analyzed; each image A is drawn again according to the deflection angle of each image A, an image A1 corresponding to each image A is obtained, and all images A1 are synthesized into a video according to coordinate information and time information; the current target frame in the obtained video file is read, and judgment, deletion and storage on an I frame and a P frame are carried out; the noise degree of the obtained video file is extracted, the bit rate and the resolution rate are adjusted according to the noise degree, and the acquired video file is compressed according to the obtained bit rate and the resolution rate; and according to the pixel point edge strength of the obtained video file, a gray scale image for the video image is generated, and based on the gray scale image, sharpening processing is carried out on the video image, and a video after processing is acquired. Thus, the video processing efficiency can be improved, excessive sharpening and a mosaic phenomenon when the video is played can be avoided, and the video watching effects are improved.
Description
Technical field
The present invention relates to field of video processing, be specifically related to a kind of method for processing video frequency。
Background technology
Along with the development of information technology, people are more and more higher to the requirement of video-see effect。But, the restriction of bandwidth Network Based, video needs to reduce encoding rate and could be transmitted glibly。And then, how when low encoding rate, the viewing effect improving video becomes one of this area important technological problems。
Meanwhile, when P LOF in the video encoded by H264, will appear from mosaic phenomenon when playing video, affect Consumer's Experience。Therefore, in order to avoid mosaic phenomenon detect before video playback in video whether exist lose P frame situation very necessary。
Summary of the invention
For solving the problems referred to above, the invention provides a kind of method for processing video frequency, can the deflection angle of automatic decision image, the real-time process of video can not only be realized, also reduce the complexity of Video processing, and then improve the efficiency of Video processing, it is to avoid when playing video, mosaic phenomenon occurs, in order to improve Consumer's Experience；Simultaneously selectively the region that the edge strength should being sharpened in video image is high can be sharpened process, compared to the method that whole video image is sharpened process, it is to avoid doing over-sharpening, improve the viewing effect of video。
For achieving the above object, the technical scheme that the present invention takes is:
A kind of method for processing video frequency, comprises the steps:
S1, being obtained video file by capture apparatus, described video file includes multiple continuous print frame of video coordinate information corresponding with each frame of video and temporal information, and described coordinate information is uniquely corresponding with described temporal information；
S2, acquired video file is resolved, obtain at least two image A, determine the deflection angle of each image A, and the deflection angle according to each image A repaints each image A, obtain each image A1 corresponding for image A, then all image A1 are pressed coordinate information and temporal information synthetic video, the video after being processed；
Current goal frame in S3, read step S4 gained video file, wherein, described video file includes I frame and P frame；Judge whether current goal frame is P frame, if I frame, then store described current goal frame；If P frame, then obtain the sequence of current goal frame, and judge that whether the sequence of acquired current goal frame and predetermined sequence be identical, if identical, then store described current goal frame；If differing, then deleting all frames between described current goal frame and described current goal frame and reference frame, wherein, described reference frame is to be positioned at first I frame after described current goal frame in described video file；
S4, extraction step S3 gained the noise level of video file, according to described noise level, adjust bit rate and resolution, and with the acquired video file of the bit rate of gained and resolution compression；
S5, pixel edge strength according to each video image in the video file of step S4 gained, generate the gray-scale map of described video image, and based on described gray-scale map, described video image be sharpened process, it is thus achieved that the video after process。
Preferably, in described gray-scale map, the gray scale of each pixel is the edge strength of corresponding pixel points in described video image。
Preferably, described step S5 passes through arithmetic operators, it is determined that the edge strength of each pixel in described video image。
Preferably, described Edge contrast includes:
Described gray-scale map is carried out expansive working and/or Gaussian Blur operation, obtains intermediate image A；
Described intermediate image A is performed etching operation, obtains intermediate image A1；
Based on described intermediate image A1, described video image is sharpened process。
Preferably, when the sequence of described current goal frame differs with described predetermined sequence, next target frame described is described reference frame。
Preferably, described step S2 determines the deflection angle of each image A by multi-orientation Face or object identification, specifically includes
The image A of predetermined number is chosen from all image A；
Each selected image A is carried out multi-orientation Face or object identification；
Determine the deflection angle of each selected image A according to recognition result, and determine the deflection angle of each unselected image A according to the deflection angle of each selected image A。
Preferably, repaint each image A according to the deflection angle of each image A to specifically include
Deflection angle according to each image A calculates the supplementary deflection angle of each image A；
Supplementary deflection angle according to each image A repaints each image A。
Preferably, also include obtaining three-dimensional point cloud by conversion between coordinate information, rebuild accurate videometer surface model, carry out mapping without the texture of deformation to the videometer surface model of gained, make reconstruction effect closer to real three-dimensional scenic, be then introduced into video-splicing software, it is achieved the demarcation of camera, sensor image distortion correction, the projective transformation of image, match point are chosen, Panorama Mosaic, brightness and color equilibrium treatment, thus obtaining final video。
The method have the advantages that
Can the deflection angle of automatic decision image, the real-time process of video can not only be realized, also reduce the complexity of Video processing, and then improve the efficiency of Video processing, it is to avoid when playing video, mosaic phenomenon occurs, in order to improve Consumer's Experience；Simultaneously selectively the region that the edge strength should being sharpened in video image is high can be sharpened process, compared to the method that whole video image is sharpened process, it is to avoid doing over-sharpening, improve the viewing effect of video。
Detailed description of the invention
In order to make objects and advantages of the present invention clearly understand, below in conjunction with embodiment, 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。
Embodiments provide a kind of method for processing video frequency, comprise the steps:
S1, being obtained video file by capture apparatus, described video file includes multiple continuous print frame of video coordinate information corresponding with each frame of video and temporal information, and described coordinate information is uniquely corresponding with described temporal information；
S2, acquired video file is resolved, obtain at least two image A, determine the deflection angle of each image A, and the deflection angle according to each image A repaints each image A, obtain each image A1 corresponding for image A, then all image A1 are pressed coordinate information and temporal information synthetic video, the video after being processed；
Current goal frame in S3, read step S4 gained video file, wherein, described video file includes I frame and P frame；Judge whether current goal frame is P frame, if I frame, then store described current goal frame；If P frame, then obtain the sequence of current goal frame, and judge that whether the sequence of acquired current goal frame and predetermined sequence be identical, if identical, then store described current goal frame；If differing, then deleting all frames between described current goal frame and described current goal frame and reference frame, wherein, described reference frame is to be positioned at first I frame after described current goal frame in described video file；
S4, extraction step S3 gained the noise level of video file, according to described noise level, adjust bit rate and resolution, and with the acquired video file of the bit rate of gained and resolution compression；
S5, pixel edge strength according to each video image in the video file of step S4 gained, generate the gray-scale map of described video image, and based on described gray-scale map, described video image be sharpened process, it is thus achieved that the video after process。
In described gray-scale map, the gray scale of each pixel is the edge strength of corresponding pixel points in described video image。
Described step S5 passes through arithmetic operators, it is determined that the edge strength of each pixel in described video image。
Described Edge contrast includes:
Described gray-scale map is carried out expansive working and/or Gaussian Blur operation, obtains intermediate image A；
Described intermediate image A is performed etching operation, obtains intermediate image A1；
Based on described intermediate image A1, described video image is sharpened process。
When the sequence of described current goal frame differs with described predetermined sequence, next target frame described is described reference frame。
Described step S2 determines the deflection angle of each image A by multi-orientation Face or object identification, specifically includes
The image A of predetermined number is chosen from all image A；
Each selected image A is carried out multi-orientation Face or object identification；
Determine the deflection angle of each selected image A according to recognition result, and determine the deflection angle of each unselected image A according to the deflection angle of each selected image A。
Deflection angle according to each image A repaints each image A and specifically includes
Deflection angle according to each image A calculates the supplementary deflection angle of each image A；
Supplementary deflection angle according to each image A repaints each image A。
Also include obtaining three-dimensional point cloud by conversion between coordinate information, rebuild accurate videometer surface model, carry out mapping without the texture of deformation to the videometer surface model of gained, make reconstruction effect closer to real three-dimensional scenic, it is then introduced into video-splicing software, realize the demarcation of camera, sensor image distortion correction, the projective transformation of image, match point are chosen, Panorama Mosaic, brightness and color equilibrium treatment, thus obtaining final video。
Originally be embodied as can the deflection angle of automatic decision image, the real-time process of video can not only be realized, also reduce the complexity of Video processing, and then improve the efficiency of Video processing, it is to avoid when playing video, mosaic phenomenon occurs, in order to improve Consumer's Experience；Simultaneously selectively the region that the edge strength should being sharpened in video image is high can be sharpened process, compared to the method that whole video image is sharpened process, it is to avoid doing over-sharpening, improve the viewing effect of video。
The above is only the preferred embodiment of the present invention; it should be pointed out that, for those skilled in the art, under the premise without departing from the principles of the invention; can also making some improvements and modifications, these improvements and modifications also should be regarded as protection scope of the present invention。
Claims (8)
1. a method for processing video frequency, it is characterised in that comprise the steps:
S1, being obtained video file by capture apparatus, described video file includes multiple continuous print frame of video coordinate information corresponding with each frame of video and temporal information, and described coordinate information is uniquely corresponding with described temporal information；
S2, acquired video file is resolved, obtain at least two image A, determine the deflection angle of each image A, and the deflection angle according to each image A repaints each image A, obtain each image A1 corresponding for image A, then all image A1 are pressed coordinate information and temporal information synthetic video, the video after being processed；
Current goal frame in S3, read step S4 gained video file, wherein, described video file includes I frame and P frame；Judge whether current goal frame is P frame, if I frame, then store described current goal frame；If P frame, then obtain the sequence of current goal frame, and judge that whether the sequence of acquired current goal frame and predetermined sequence be identical, if identical, then store described current goal frame；If differing, then deleting all frames between described current goal frame and described current goal frame and reference frame, wherein, described reference frame is to be positioned at first I frame after described current goal frame in described video file；
S4, extraction step S3 gained the noise level of video file, according to described noise level, adjust bit rate and resolution, and with the acquired video file of the bit rate of gained and resolution compression；
S5, pixel edge strength according to each video image in the video file of step S4 gained, generate the gray-scale map of described video image, and based on described gray-scale map, described video image be sharpened process, it is thus achieved that the video after process。
2. a kind of method for processing video frequency according to claim 1, it is characterised in that in described gray-scale map, the gray scale of each pixel is the edge strength of corresponding pixel points in described video image。
3. a kind of method for processing video frequency according to claim 1, it is characterised in that described step S5 passes through arithmetic operators, it is determined that the edge strength of each pixel in described video image。
4. a kind of method for processing video frequency according to claim 1, it is characterised in that described Edge contrast includes:
Described gray-scale map is carried out expansive working and/or Gaussian Blur operation, obtains intermediate image A；
Described intermediate image A is performed etching operation, obtains intermediate image A1；
Based on described intermediate image A1, described video image is sharpened process。
5. a kind of method for processing video frequency according to claim 1, it is characterised in that when the sequence of described current goal frame differs with described predetermined sequence, next target frame described is described reference frame。
6. a kind of method for processing video frequency according to claim 1, it is characterised in that described step S2 determines the deflection angle of each image A by multi-orientation Face or object identification, specifically includes
The image A of predetermined number is chosen from all image A；
Each selected image A is carried out multi-orientation Face or object identification；
Determine the deflection angle of each selected image A according to recognition result, and determine the deflection angle of each unselected image A according to the deflection angle of each selected image A。
7. a kind of method for processing video frequency according to claim 1, it is characterised in that repaint each image A according to the deflection angle of each image A and specifically include
Deflection angle according to each image A calculates the supplementary deflection angle of each image A；
Supplementary deflection angle according to each image A repaints each image A。
8. a kind of method for processing video frequency according to claim 1, it is characterized in that, also include obtaining three-dimensional point cloud by conversion between coordinate information, rebuild accurate videometer surface model, carry out mapping without the texture of deformation to the videometer surface model of gained, make reconstruction effect closer to real three-dimensional scenic, it is then introduced into video-splicing software, realize the demarcation of camera, sensor image distortion correction, the projective transformation of image, match point are chosen, Panorama Mosaic, brightness and color equilibrium treatment, thus obtaining final video。
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| CN201610153366.1A CN105704398A (en) | 2016-03-11 | 2016-03-11 | Video processing method |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106228513A (en) * | 2016-07-18 | 2016-12-14 | 黄河科技学院 | A kind of Computerized image processing system |
| CN106507091A (en) * | 2016-11-14 | 2017-03-15 | 墨宝股份有限公司 | A kind of method of utilization 3D animations shooting and producing true man's theme Showmov piece |
| CN107390278A (en) * | 2017-07-08 | 2017-11-24 | 贵州理工学院 | A kind of radioactivity mineral exploration method |
| CN107424218A (en) * | 2017-07-25 | 2017-12-01 | 成都通甲优博科技有限责任公司 | A kind of sequence chart bearing calibration tried on based on 3D and device |
| CN108305218A (en) * | 2017-12-29 | 2018-07-20 | 努比亚技术有限公司 | Panoramic picture processing method, terminal and computer readable storage medium |
| CN109167980A (en) * | 2018-11-01 | 2019-01-08 | 苏州旷视智能科技有限公司 | For remote high definition video processing method |
| CN113079334A (en) * | 2020-01-06 | 2021-07-06 | 宏碁股份有限公司 | Computer system and image compensation method thereof |
| WO2022087826A1 (en) * | 2020-10-27 | 2022-05-05 | 深圳市大疆创新科技有限公司 | Video processing method and apparatus, mobile device, and readable storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106228513A (en) * | 2016-07-18 | 2016-12-14 | 黄河科技学院 | A kind of Computerized image processing system |
| CN106507091A (en) * | 2016-11-14 | 2017-03-15 | 墨宝股份有限公司 | A kind of method of utilization 3D animations shooting and producing true man's theme Showmov piece |
| CN107390278A (en) * | 2017-07-08 | 2017-11-24 | 贵州理工学院 | A kind of radioactivity mineral exploration method |
| CN107424218A (en) * | 2017-07-25 | 2017-12-01 | 成都通甲优博科技有限责任公司 | A kind of sequence chart bearing calibration tried on based on 3D and device |
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| CN108305218A (en) * | 2017-12-29 | 2018-07-20 | 努比亚技术有限公司 | Panoramic picture processing method, terminal and computer readable storage medium |
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| CN109167980A (en) * | 2018-11-01 | 2019-01-08 | 苏州旷视智能科技有限公司 | For remote high definition video processing method |
| CN113079334A (en) * | 2020-01-06 | 2021-07-06 | 宏碁股份有限公司 | Computer system and image compensation method thereof |
| WO2022087826A1 (en) * | 2020-10-27 | 2022-05-05 | 深圳市大疆创新科技有限公司 | Video processing method and apparatus, mobile device, and readable storage medium |
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Effective date of registration: 20190717 Address after: 710000 No. 69 Xingshan Temple East Street, Yanta District, Xi'an City, Shaanxi Province Applicant after: Shaanxi Xueqian Normal University Address before: 712000 Wenlin Road, Weicheng District, Xianyang City, Shaanxi Province Applicant before: Xianyang Normal University |
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