Unlock instant, AI-driven research and patent intelligence for your innovation.

Method of rebuilding under-sampled image based on minimal second-order total generalized variation

An image reconstruction and undersampling technology, applied in image enhancement, image data processing, instruments, etc., can solve the problems of large amount of calculation, ladder effect, high processing power and power consumption, and achieve simplified calculation, good intelligence, and good effect. ideal effect

Inactive Publication Date: 2015-05-13
HAINAN UNIVERSITY
View PDF3 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This algorithm is popular because it can better preserve feature information such as edges and contours, but it often leads to a staircase effect during image reconstruction.
Moreover, this method has a large amount of calculation, requires too much processing power and power consumption, and is not suitable for video sensor system applications.

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
  • Method of rebuilding under-sampled image based on minimal second-order total generalized variation
  • Method of rebuilding under-sampled image based on minimal second-order total generalized variation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0020] In order to make the purpose of the present invention, implementation scheme and advantage clearer, the specific implementation of the present invention is described in further detail below, and the concrete process of the present invention is as follows figure 1 shown.

[0021] (1) The image capturing part of the invention is obtained by the image acquisition device of the video sensor network.

[0022] (2) Calculate the second-order total generalized variation of the undersampled image. For an undersampled image ρ, calculate its second-order total generalized variation TGV, denoted as TGV 2 (ρ), where Ω denotes a bounded vector field where υ∈Ω, Represents the gradient operator, Represents the first derivative of the image, is a symmetric gradient operator, β 1 and beta 0 Is a non-negative weight, used for the first and second derivatives of the balance function, in the second derivative Smaller smooth regions, TGV 2 (ρ) converted to measure in the seco...

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 method of rebuilding an under-sampled image based on a minimal second-order total generalized variation. The method comprises the following steps: (1) calculating a second-order total generalized variation of the under-sampled image; (2) obtaining a minimal value of a TGV norm through a conjugate gradient method; and (3) carrying out rectangular projection and error correction processing on each iteration result, so as to obtain an applicable parameter integration used for image rebuilding. The method provided by the invention can obtain a more accurate rebuilding result.

Description

technical field [0001] The present invention generally relates to a method of reconstructing undersampled images. Since the processing capability or environmental influence of systems such as video sensors is often insufficient to obtain adequately sampled images, this invention more specifically relates to a method for solving the problem of image undersampling caused by environmental influence and insufficient communication capabilities in video sensor networks. Background technique [0002] With the continuous development of sensor networks, video surveillance and recognition systems based on sensor networks have become a hot topic in recent years, followed by various intelligent applications of video sensor systems such as object detection and tracking, etc., are Fundamentals of environmental and emergency monitoring. However, due to the limited network transmission capacity of wireless and underwater environments, sufficient sampling data cannot be obtained in some env...

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
Inventor 黄向党羊秋玲
Owner HAINAN UNIVERSITY