Image restoration method based on similar convex set projection algorithm

A convex set projection and image restoration technology, applied in the field of image restoration based on convex set projection algorithm, can solve the problem of not considering the influence of restoration results, and achieve the effect of simple structure, noise suppression, and high noise resolution

Inactive Publication Date: 2020-06-09
XIDIAN UNIV
View PDF0 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, none of the existing image restoration networks considers the in

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 restoration method based on similar convex set projection algorithm
  • Image restoration method based on similar convex set projection algorithm
  • Image restoration method based on similar convex set projection algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0048] The embodiments and effects of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0049] refer to figure 1 , the implementation steps of the present invention are as follows:

[0050] Step 1) Construct training sample set and test sample set:

[0051] (1a) Obtain the high-resolution (HR) image in the DIV2K public data set, obtain N image blocks with a resolution size of S×S through HR, and down-sample each image block through bicubic to obtain the corresponding low-resolution image resolution (LR) image blocks. Among them, N≥200000, S=19;

[0052] (1b) Obtain HR images in Set5, Set14, BSD100, Urban100, and Manga109 public datasets, and downsample them through bicubic to obtain corresponding LR images.

[0053] Step 2) Build the displayed feature denoising module:

[0054] refer to figure 2 , constructing the displayed feature denoising module includes a soft threshold module (ST block) and an adaptive soft thr...

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 restoration algorithm based on a similar convex set projection algorithm, which is used for solving the problem that a large amount of noise exists in an existing image restoration network feature map. The method comprises the following steps: 1) constructing a training sample set and a test sample set; 2) constructing a displayed feature denoising module; 3) constructing an image restoration network model PL-DSR based on a similar convex set projection algorithm; 4) training the PL-DSR network model; 5) testing the PL-DSR network model; 6) generating a restored image. A displayed feature denoising module is constructed on the basis of a traditional convex set projection algorithm and used for suppressing noise in a feature map and introducing the noise into a classical EDSR network, and an image restoration network PL-DSR based on a similar convex set projection algorithm is constructed. The network can effectively suppress noise in the feature map, extract structured clearer features, further improve the recovery effect and the visual sensory experience of people while reducing the complexity of the model, and can be used for completing later manufacturing and processing of photography and movie and television works.

Description

technical field [0001] The invention belongs to the technical field of digital image processing, and specially designs an image restoration method based on a similar convex set projection algorithm to restore degraded images, which can be used to complete the post-production processing of photography and film and television works. Background technique [0002] An important branch in the field of computer vision is image generation, which includes image restoration, image coloring, image semantic segmentation, image or video style conversion, etc. In the field of computer vision, image restoration is an ill-conditioned inverse problem, that is, in the case of specifying a low-resolution image, the prior knowledge of the degradation process is used to establish an image degradation model and restore the original high-resolution image. [0003] Traditional image restoration models mainly include: 1) algorithms based on interpolation (nearest neighbor method, bilinear interpolat...

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
IPC IPC(8): G06T5/00
CPCG06T5/002G06T2207/20081G06T2207/20084G06T2207/20192
Inventor 武宇喆牛毅石光明
Owner XIDIAN UNIV
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

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap