Amalgamation of Singular Value Decomposition to JPEG for Enhanced Performance
ABSTRACT The demand of digital information compression is increasing dramatically because of the dominance of multimedia technology and the limitations of the physical media for handling huge amount of information. Compression reduces the storage and transmission burdens of raw information by reducing the ubiquitous redundancy without losing its entropy significantly. The image manipulation that occupies a significant position in multimedia technology necessitated the development of joint photographic experts group (JPEG) compression technique, which has proved its usefulness so far. Until recently, to minimize the blocking artifact, inherently present in JPEG at higher compression ratios, JPEG2000 is devised that makes use of wavelet function. In this work, a new approach to JPEG compression technique is proposed that enhanced the compression performances in comparison with aforesaid JPEG techniques. The new technique considers both discrete cosine transform (DCT) and singular value decomposition (SVD) method in the transform and reconstruction sides instead of using DCT only. The incorporation of SVD with nearest neighborhood approach has improved the compression performances significantly. A rigorous comparison of the various compression indices are made to validate the proposed algorithm. This approach is named as 'Hybrid JPEG' (HJPEG) in this paper. The benchmark still image 'LENA' is used for performance comparison.
Chapter: Matrix Computations01/1986; Johns Hopkins University Press.
Article: Discrete Cosine Transform[Show abstract] [Hide abstract]
ABSTRACT: A discrete cosine transform (DCT) is defined and an algorithm to compute it using the fast Fourier transform is developed. It is shown that the discrete cosine transform can be used in the area of digital processing for the purposes of pattern recognition and Wiener filtering. Its performance is compared with that of a class of orthogonal transforms and is found to compare closely to that of the Karhunen-Loève transform, which is known to be optimal. The performances of the Karhunen-Loève and discrete cosine transforms are also found to compare closely with respect to the rate-distortion criterion.IEEE Transactions on Computers 02/1974; C-23(1-C-23):90 - 93. DOI:10.1109/T-C.1974.223784 · 1.47 Impact Factor
- HA) compressed images are shown in the figure. Digital Image Processing, Addision-weseky, All of them have PCR of 30 % and PSNR (dB) of 1993..