Compressive Sensing based Image Reconstruction Algorithms – A Performance Review
Author(s):
Dr. Vasudha S, Anupama H, Dr. S Shanthala, Dr. H.R. Mahadevaswamy
Keywords:
Compressive Sensing, Matching Pursuit, Basis Pursuit, Greedy algorithm, Sparse representation, Smoothed L0 norm
Abstract
Compressive Sensing (CS) is a powerful high resolution image modelling technique which has been successfully applied in digital image processing and various computer vision applications. This paper will portrait the current image reconstruction algorithms, their drawbacks and an overview of performance metrics such as image quality and PSNR improvements. The performance metric modelling is carried to trade-off choice of reconstruction algorithm with the quality of the reconstructed image considering various applications.
Article Details
Unique Paper ID: 144669

Publication Volume & Issue: Volume 4, Issue 1

Page(s): 367 - 371
Article Preview & Download


Share This Article

Conference Alert

NCSST-2021

AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2021

SWEC- Management

LATEST INNOVATION’S AND FUTURE TRENDS IN MANAGEMENT

Last Date: 7th November 2021

Latest Publication

Go To Issue



Call For Paper

Volume 8 Issue 4

Last Date 25 September 2021

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews

Contact Details

Telephone:6351679790
Email: editor@ijirt.org
Website: ijirt.org

Policies

Important Links

Browse Rsearch papers