Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Image denoising method based on image rotation and partitioning singular value decomposition

A singular value decomposition and image rotation technology, which is applied in the field of image processing, can solve problems such as low denoising accuracy and incomplete image information, and achieve the effects of meeting real-time requirements, easy processing, and making up for discontinuities

Inactive Publication Date: 2017-08-22
XI'AN POLYTECHNIC UNIVERSITY
View PDF7 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide an image denoising method based on image rotation and block singular value decomposition, which solves the problems of incomplete image information and low denoising accuracy in existing denoising methods

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
  • Image denoising method based on image rotation and partitioning singular value decomposition
  • Image denoising method based on image rotation and partitioning singular value decomposition
  • Image denoising method based on image rotation and partitioning singular value decomposition

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments, but the present invention is not limited to these embodiments.

[0045] The principle of the image denoising method of the present invention is as follows: figure 1 As shown, the specific steps are as follows:

[0046] Step 1: Perform block rotation on the original input image;

[0047] (1) The image is first divided into blocks, and the size of the original image with noise is set to be 1 1 × I 2 , the original noisy image is divided into non-overlapping square blocks, and the size of each divided square block is m×m (it can also be divided into rectangular blocks with a size of m×n). Since the main image information contained in each image block is different, the divided image blocks need to be rotated by blocks, and the determination of the rotation angle in the process of image rotation is often a critical issue.

[0048](2) The...

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 discloses an image denoising method based on image rotation and partitioning singular value decomposition. Firstly partitioning rotation is performed on an original input image; then the rotated image blocks are searched, and similarity matching is performed according to the image blocks; and finally two-dimensional and one-dimensional singular value decomposition is performed inside and outside the successfully matched similar blocks, and 1D SVD inverse transformation and 2D SVD inverse transformation are performed on the contracted projection coefficient by using the soft and hard compromise threshold contraction matrix projection coefficient so that final image denoising can be realized. According to the method, partitioning rotation is performed on the image before denoising so that image information attenuation in the block can be eliminated, the processing time can be shortened, different dimensions of singular value decomposition can be performed inside and outside the image and the anti-noise performance can be enhanced based on the conventional SVD algorithm.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to an image denoising method based on image rotation and block singular value decomposition. Background technique [0002] With the popularity of all kinds of digital instruments and digital products, digital image processing has become a research hotspot in the intersection of digital technology and computer technology. Digital image processing refers to the digital processing of visual information using computer science research and production. The behavior of processing image information to meet human visual psychology or application needs. Most of us live in a complex environment, so that external factors will affect our lives. In the process of collecting original images, there are unknowable factors that will damage the collected images. Interference with the image, resulting in reduced image quality. However, how to effectively and accurately denoise images has become an im...

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 Applications(China)
IPC IPC(8): G06T5/00G06K9/62
CPCG06F18/23213G06T5/70
Inventor 李云红钟晓妮王震亚郑婷婷魏妮娜杨彭智
Owner XI'AN POLYTECHNIC UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com