Fast Singular value decomposition based image compression using butterfly particle swarm optimization technique (SVD-BPSO)
D.J. Ashpin Pabi, N.Puviarasan, P.Aruna, ,
Affiliations Research Scholar, Department of Computer Science and Engineering, Annamalai University, 608 002, India
:10.22362/ijcert/2017/v4/i4/xxxx [UNDER PROCESS]
Image compression is an important research area in an image processing system. Due to the compression of data rates, this finds crucial in applications of information security for the fast transmission. Singular Value Decomposition (SVD) is a compression technique which performs compression by using a smaller rank to approximate the original matrix of an image. SVD offers good PSNR values with low compression ratios. Compression using SVD for different singular values (Sv) with an acceptable PSNR increases the encoding time (ET). To minimize the encoding time, in this paper a fast compression technique SVD-BPSO is proposed using singular value decomposition and butterfly particle swarm optimization (BPSO). Application of the concept of BPSO towards singular value decomposition reduces the encoding time and improves the transmission speed. The performance of the proposed SVD-BPSO compression method is compared with SVD without optimization technique. The simulation results showed that the method achieves good PSNR with the minimum encoding time.
D.J. Ashpin Pabi et.al, â€œFast Singular value decomposition based image compression using butterfly particle swarm optimization technique (SVD-BPSO)â€, International Journal Of Computer Engineering In Research Trends, 4(4):128-135, April-2017.
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