IJSRP, Volume 4, Issue 5, May 2014 Edition [ISSN 2250-3153]
Sunita S Biswal, Krishna Kalpita, Dipak R. Swain
Principal Component analysis (PCA) is one of the statistical methods employed in image compression. Presented paper deals with four different types of PCA algorithms those are 2D-PCA, 3D-PCA, 2D -Kernel PCA (2D-KPCA) and 3D-KPCA. A comparative study is made for all four types of PCA based on their PSNR values. These algorithms are also tested on several standard test images. It has been found that the quality of reconstructed image of 3DKPCA is better than other types of PCA based image compression.