Single Image Resolution Enhancement

 

Executive Summary

 

Super-resolution is the process of increasing the resolution of a low-resolution image.  Manifold techniques have been used for super-resolution to enhance image, photo, or video quality, but they are often computationally demanding due to the complexity of the underlying algorithm.  MSU researchers have developed a novel method for single image super-resolution, requiring little computational complexity and meeting highest quality standards at a significantly lower cost.

 

Description of Technology

 

This technology is an algorithm for linear approximation of a lower dimension manifold using sparse subspace clustering for the purpose of super-resolution or the up-scaling of a single image.  Our technology yields comparable if not better image enhancement results than current technique with significantly less computational requirements, thus lowering computational cost.

 

Key Benefits

  • Fast – less computational time processing images
  • Low cost – very cost-effective due to less computational complexity and shorter processing time

 

Applications

  • Image Super Resolution – cameras, etc.
  • High definition TV – upscaling video, lower resolution content
  • Image/Video quality enhancement
  • Medical Imaging – tomography, MRI etc.
  • Satellite imaging

 

IP Status: 

 

Software copyright

 

Licensing Rights Available

 

Full licensing available

 

Inventors: Chinh Dang, Hayder Radha

 

Tech ID: TEC2014-0006

 

Patent Information:

For Information, Contact:

Raymond DeVito
Technology Manager
Michigan State University
devitora@msu.edu
Keywords: