Enhanced Image Compression Algorithm for Image Processing Applications

Due to the increasing traffic caused by multimedia information and digitized form of representation of images; image compression has become a necessity. New algorithms for image compression based on wavelets have been developed which offers considerable improvement in picture quality at high compression ratios. To achieve lowest errors per compression rate and highest perceptual quality, the existing image compression algorithms are need to be modified. In this paper, with the objective of achieving high image compression ratio with minimum number of errors, the features of existing image compression algorithms like Haar Wavelet Transform are increased and named as Modified Fast Haar Wavelet Transform (MFHWT). The Set Partitioning In Hierarchical Trees (SPIHT) along with Run Length Encoding (RLE) increases the compression ratio without degrading the image quality. Also, the modified algorithm reduces the number of computations in Haar transform, which decreases the processing time. The proposed work was simulated using MALAB and the results shows that the compression ratio increases without affecting the Peak Signal to Noise Ratio (PSNR) standards. KeywordsImage Compression, DWT, MFHWT, ESPIHT, RLE