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

Non-local depth image super-resolution rebuilding method based on minimum spanning tree (MST)

A super-resolution reconstruction and super-resolution technology, applied in the field of depth map super-resolution reconstruction, can solve the problems of high time complexity and difficult to satisfy

Active Publication Date: 2013-07-24
TIANJIN UNIV
View PDF1 Cites 35 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there is a common problem in the existing methods: the time complexity is high, it is difficult to meet the needs of practical applications, especially the applications with real-time requirements

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
  • Non-local depth image super-resolution rebuilding method based on minimum spanning tree (MST)
  • Non-local depth image super-resolution rebuilding method based on minimum spanning tree (MST)
  • Non-local depth image super-resolution rebuilding method based on minimum spanning tree (MST)

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0057] The technical scheme that the present invention takes comprises the following steps:

[0058] 1) Using Middlebury's data set (paired color map and depth map) as test data, the depth map is down-sampled according to the super-resolution ratio to obtain the initial low-resolution depth map that needs to be reconstructed, and then the initial depth map Perform a simple preprocessing step, that is, use Bicubic Interpolation to enlarge the downsampled depth map to its original size.

[0059] 2) Think of the color texture map as a connected undirected graph G=(V, E), the node V corresponds to all the pixels in the image, and the edge E corresponds to the connection between the nearest adjacent pixels in the image, so A standard 4-connected planar graph is obtained. Let s and r be a pair of adjacent nodes, and the weight of the edge connecting s and r is defined as follows:

[0060] ω(s,r)=ω(r,s)=|I(s)-I(r)| (1)

[0061] ω(s,r) is the weight of the edge connecting s and r, ...

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 belongs to the field of computer vision and image processing, and provides a rapid non-local super-resolution rebuilding method based on a minimum spanning tree (MST). Time complexity of an algorithm is reduced, meanwhile the quality of a rebuilding result is maintained, and a good balance between the time complexity and the quality is achieved. According to the technical scheme, the rapid non-local super-resolution rebuilding method based on the MST comprises the following steps: (1) obtaining an initial low-resolution depth image required to be rebuilt, then carrying out further simple pre-processing on the initial depth image, (2) obtaining a standard 4-connected planar graph, (3) obtaining the MST corresponding to an undirected connected graph in the step (2), and (4) rebuilding the coarse depth image after pre-processed according to the MST. The non-local super-resolution rebuilding method based on the MST is mainly applied in image processing.

Description

technical field [0001] The invention belongs to the field of computer vision and image processing, and specifically relates to a non-local minimum spanning tree (MST, Minimum Spanning Tree) super-resolution method for low-resolution depth maps, that is, a non-local super-resolution method based on minimum spanning tree A Depth Map Super-Resolution Reconstruction Method. Background technique [0002] Image Super Resolution (Image Super Resolution), that is, to improve the resolution of the original image by means of hardware or software, and the process of obtaining a high-resolution image through a series of low-resolution images is super-resolution reconstruction. The core idea of ​​super-resolution reconstruction is to trade temporal bandwidth (acquiring multi-frame image sequences of the same scene) for spatial resolution, and realize the conversion from temporal resolution to spatial resolution. [0003] The most direct way to improve the image resolution is to increase...

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): G06T3/40G06T7/00
Inventor 杨敬钰张群侯春萍
Owner TIANJIN UNIV
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