Affiliation:
1. Pimpri Chinchwad Polytechnic, Pune, Maharashtra, India
Abstract
This paper presents study of assorted lossy compression techniques. the 2 techniques are Wavelet Difference Reduction (WDR) based compression and Singular Value Decomposition (SVD) based compression and SVD based compression reduces the psycho visual redundancies present within the image through rank reduction technique. WDR may be a lossy compression technique. It gains compression by taking the discrete wavelet transform of the input image so encodes the transform values using difference compression method. Singular Value Decomposition (SVD) is one in every of the simplest compression techniques. SVD based compression technique gives better visual quality at higher singular values. Various compression parameters like PSNR, MSE and compression ratio are evaluated for the assorted techniques. during this survey, compare how SVD is applied to colour images, the technique of compression and maintain the standard of the image using SVD and also the algorithm to compress a picture using image processing tool MATLAB and compared the WDR SVD lossy compression techniques.
Reference15 articles.
1. T. Ozcelik, J. Brailean, and A. Katsaggelos, Image and video compression algorithms based on recovery techniques using mean field annealing," Proceedings of the IEEE, vol. 83, no. 2, pp. 304-316, 1995.
2. M.-Y. Shen and C.-C. J. Kuo, Review of postprocessing techniques for compression artifact removal," Journal of Visual Communication and Image Representation, vol. 9, no. 1, pp. 2-14, 1998.
3. K. Bredies and M. Holler, Artifact-free jpeg decompression with total generalized variationin VISAPP (1), pp. 12-21, 2012.
4. K. Mounika, D. Sri Navya Lakshmi, K. Alekya, SVD based image compression,International Journal of Engineering Research and General Science Volume 3, Issue 2, March-April,2015”.
5. Rowayda A. Sadek, SVD Based Image Processing Applications: State of The Art, Contributions and Research Challenges,” (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 3, No. 7, 2012”.