WDR coding based image compression technique using PCA

Abstract

Image compression is the technique of reducing the number of bits required to represent a digital image, which can be accomplished by reducing the redundant and visually irrelevant information present in the images. In this study, a Wavelet Difference Reduction (WDR) coding based image compression technique is proposed which uses Principal Component Analysis (PCA). These techniques are combined in order to achieve high compression ratio with an acceptable degradation in the compressed images. The input image is first compressed using PCA. Few of the Principal Components are used to reconstruct the image. The reconstructed image obtained by PCA is further used as an input data for WDR compression. Since WDR is a wavelet based coding technique so it exploits local characteristics of the image and leads to high Compression Ratio (CR). Here, PCA and WDR are combined because PCA gives high image quality but low CR on the other hand WDR works opposite of it as it gives high CR. The proposed technique is applied on several test images and results are compared with WDR and JPEG2000 techniques. Results clearly show that the proposed technique is better than the existing techniques in terms of both objective and subjective fidelity criteria.