Lossless Image Compression Using New Biorthogonal Wavelets

Abstract

Even though a large number of wavelets exist, one needs new wavelets for their specific applications. One of the basic wavelet categories is orthogonal wavelets. But it was hard to find orthogonal and symmetric wavelets. Symmetricity is required for perfect reconstruction. Hence, a need for orthogonal and symmetric arises. The solution was in the form of biorthogonal wavelets which preserves perfect reconstruction condition. Though a number of biorthogonal wavelets are proposed in the literature, in this paper four new biorthogonal wavelets are proposed which gives better compression performance. The new wavelets are compared with traditional wavelets by using the design metrics Peak Signal to Noise Ratio (PSNR) and Compression Ratio (CR). Set Partitioning in Hierarchical Trees (SPIHT) coding algorithm was utilized to incorporate compression of images.