A Real Video Restoration Method Based on Local Strategy

A strategy and video technology, applied in image enhancement, instrumentation, graphics and image conversion, etc.

Active Publication Date: 2017-03-15
上海厉鲨科技有限公司
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method can overcome the shortcomings of amplifying noise and introducing ringing effects in the traditional method, and has a good restoration effect on the edges and details of the video frame.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Real Video Restoration Method Based on Local Strategy
  • A Real Video Restoration Method Based on Local Strategy
  • A Real Video Restoration Method Based on Local Strategy

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0021] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0022] In image restoration, the image degradation model can be expressed by the following formula:

[0023]

[0024] Among them, g(x,y) is the original image, It is a convolution operation, k(x,y) represents the blur kernel that blurs the image, also called the point spread function, n(x,y) is additive noise, and f(x,y) is a known degraded image.

[0025] A video sequence is composed of several frames of images, and each frame can be regarded as a relatively independent image extracted from the video. Therefore, the image degradation model can also describe the degradation process of video frames. The task of video frame restoration is to obtain a clear video frame g(x,y) based on the known degraded video frame f(x,y). In the restoration of real video, the blur kernel is usually unknown, and for each pixel in the moving foreground, its blur kernel is ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a real video recovery method based on local strategies and belongs to the field of image processing and pattern recognition. The real video recovery method based on the local strategies is characterized by comprising, firstly, extracting the moving foregrounds of the neighboring two frames of a real video, matching the feature points of the moving foregrounds and accordingly estimating the blurring kernels of every pixel point in the foregrounds; secondly, for eliminating object motion blur of space change inside the video, providing an ADM (adaptive delta modulation) algorithm, namely, recovering all the overlapped local blocks and integrating the local blocks into clear video frames. The real video recovery method based on the local strategies can overcome the deficiencies of amplifying noise and introducing ringing effects in traditional methods and achieve good recovery effects on the edges and the details of the video frames.

Description

technical field [0001] The invention belongs to the field of image processing and pattern recognition, and in particular relates to a real video restoration technology. Background technique [0002] In recent years, with the development of multimedia technology and the continuous optimization of video acquisition equipment, video images have been widely used in various fields such as video surveillance, medical detection, radioactivity measurement, astronomical observation and remote sensing. However, in the process of video acquisition, transmission, storage and display, due to factors such as airflow disturbance, defocus, sensor noise, relative motion between the camera and the shooting object, etc., the quality of the video will be degraded and degraded, mainly manifested as video blur and distortion , additional noise, etc., which reduce the discernibility and usability of the video. In order to get high-quality video, we usually need to restore the blurred video. [0...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/40G06T5/00G06T3/00
Inventor 龚卫国杨文琳李伟红陈魏然
Owner 上海厉鲨科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products