An Infrared Image Super-resolution Method Based on Edge Sharpening

An infrared image and super-resolution technology, which is applied in the field of infrared image super-resolution algorithms in the field of digital imaging technology, can solve the problems of excessive infrared image noise, low output image quality, and inability to guarantee estimation accuracy, and achieves improved details, The effect of visual enhancement

Active Publication Date: 2021-07-20
ZHEJIANG UNIV
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although it has fast processing time at low computational complexity, the step-by-step approach cannot guarantee accurate estimation, especially in the presence of noise
Some literatures propose to use the method of neural network to super-resolve infrared images, but the output image quality is not high due to the large noise of infrared images.

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
  • An Infrared Image Super-resolution Method Based on Edge Sharpening
  • An Infrared Image Super-resolution Method Based on Edge Sharpening
  • An Infrared Image Super-resolution Method Based on Edge Sharpening

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment

[0044] The specific implementation of the present invention includes two stages, stage one and stage two. In the first stage, the infrared image is input into the network, and the image is convolved with nine convolution kernels with a step size of 1 and a size of 3*3*64 and a convolution kernel with a step size of 1 and a size of 3*3*1. Product operation, and then add the input infrared image pixel by pixel to generate a Gaussian denoising image; at the same time, use five convolution kernels with a step size of 1 and a size of 3*3*64 and a step size of 1 and a size of 3 The *3*1 convolution kernel performs a convolution operation on the image to generate an edge image. Then use 5 convolution kernels with a step size of 1 and a size of 3*3*64 and a convolution kernel with a step size of 1 and a size of 3*3*1 to convolve the Gaussian denoising image generated in stage one, Get the final output image.

[0045] According to the resolution requirements of different magnificatio...

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 infrared image super-resolution method based on edge sharpening. Use the infrared camera to obtain infrared images, and establish an infrared super-resolution neural network structure. The network includes two sub-networks, image processing and image edge processing. For the infrared image input into the network, the image processing network is mainly used to restore the structural information of the image, and the edge processing network It is used to restore the detailed edge information of the image; the image processing network is divided into two stages, the first stage realizes infrared image denoising and restores the structural information of the image, and the second stage realizes image super-resolution and realizes more image detail structures Information recovery. Based on the requirement of digital infrared image super-resolution, the invention realizes high-magnification infrared image super-resolution through separate processing of image structure and edge information.

Description

technical field [0001] The invention belongs to an infrared image super-resolution algorithm in the technical field of digital imaging, and in particular relates to an infrared image super-resolution method based on edge sharpening. [0002] technical background [0003] With the development of infrared detection technology, infrared imaging technology is used for target recognition to improve the intelligent detection and detection and recognition capabilities of targets. The output quality is not good, which reduces the recognition and detection ability of the target single-frame infrared image. [0004] A high-resolution image can provide more detail than its low-resolution counterpart. These details should be critical in all areas. Due to the limitations of hardware devices, super-resolution has been widely used in many imaging devices. Super-resolution is the digital magnification of an image without changing the focal length of the lens, thus resulting in a loss of i...

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): G06T3/40G06T5/00G06N3/04G06N3/08
CPCG06T3/4053G06T3/4046G06T3/4007G06T5/002G06T5/003G06T2207/10048G06T2207/20081G06T2207/20084G06T2207/20192G06N3/08G06N3/045
Inventor 冯华君杨一帆徐之海李奇陈跃庭
Owner ZHEJIANG 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