Paper Info
Title
A Framework to Design Novel SVD Based Color Image Compression
Abstract
It is well known that the images, often used in variety of computer applications, are difficult to store and transmit. One possible solution to overcome this problem is to use a data compression technique where an image is viewed as a matrix and then the operations are performed on the matrix. In this paper, image compression is achieved by using Singular Value Decomposition (SVD) technique on the image matrix. The advantage of using the SVD is the property of energy compaction and its ability to adapt to the local statistical variations of an image. Further, the SVD can be performed on any arbitrary, square, reversible and non reversible matrix of m x n size. In this paper, SVD is utilized to compress and reduce the storage space of an image. In addition, the paper investigates the effect of rank in SVD decomposition to measure the quality in terms of Compression Ratio and PSNR.
Year
DOI
Venue
2009
10.1109/EMS.2009.100
Athens
Keywords
Field
DocType
data compression technique,svd decomposition,non reversible matrix,singular value decomposition,local statistical variation,design novel svd,energy compaction,compression ratio,computer application,image compression,image matrix,color image,image reconstruction,chromium,psnr,statistical analysis,matrix decomposition,image quality,svd,data compression
Iterative reconstruction,Computer vision,Singular value decomposition,Matrix (mathematics),Matrix decomposition,Algorithm,Image quality,Compression ratio,Artificial intelligence,Data compression,Image compression,Mathematics
Conference
ISSN
ISBN
Citations 
2473-3539
978-0-7695-3886-0
2
PageRank 
References 
Authors
0.36
6
2
Name
Order
Citations
PageRank
Satish Kumar Singh122417.23
Shishir Kumar27817.06