<title>Fast image coding of interval interpolating wavelets</title>

Abstract

We presents the interval interpolating wavelet transform for fast image compression. Comparing with the common used wavelet coding, this method is more systematically stable, with less computing complexity and the inherent parallel processing. In theory, it has the nearly optimal minimax compression characteristics. The simulation shows that the interval interpolating wavelet transform are more qualified and remove the artificial blocking effects (which is serious by DCT). The interval wavelets is introduced to deal with the boundary points of the fmite localized image. This method do not only improve the compress rate, but also delete the quantization aliasing ofthe boundary pixels.Wavelet compression has been studied widely[21(3U71['°l. The tree-structure decomposition, multiscale representation, self-similarity and obvious directional filtering among the different scales offer the large background of so-called "zero-tree" coding51. Wavelet transform reveals the aspects of human perception in (1)

Generalized symmetric interpolating wavelets

“…The theory of interpolating wavelets based on a subdivision scheme has attracted much attention recently [ 1,9,12,13,17,22,27,29,40,42,[45][46][47][48][49][54][55][56]65,66]. Because the digital sampling space is exactly homomorphic to the multiscale spaces generated by interpolating wavelets, the wavelet coefficients can be obtained from linear combinations of discrete samples rather than from traditional inner product integrals.…”