Lossless and lossy image compression using biorthogonal wavelet transforms with multiplierless operations

We present lossless and lossy image compression algorithms, based on biorthogonal wavelets, which provide high computational speed and excellent compression performance. A specific pair of spline biorthogonal wavelets are chosen, having dyadic rational filter coefficients; convolutions with these filters can be performed by using only arithmetic bit-shifting and integer addition operations. For lossless compression, we have investigated a new reversible embedded wavelet transform. For lossy compression, we have constructed two-dimensional reconstruction filter masks for carrying out bit-shifting to minimize data access operations when performing the inverse wavelet transform.

[1]  HyungJun Kim,et al.  Unified Image Compression Using Reversible and Fast Biorthogonal Wavelet Transform , 1996 .

[2]  Truong Q. Nguyen,et al.  Wavelets and filter banks , 1996 .

[3]  Ching-Chung Li,et al.  Fast reversible wavelet image compressor , 1996, Optics & Photonics.

[4]  Ahmad Zandi,et al.  CREW: Compression with Reversible Embedded Wavelets , 1995, Proceedings DCC '95 Data Compression Conference.

[5]  Ali Tabatabai,et al.  Sub-band coding of digital images using symmetric short kernel filters and arithmetic coding techniques , 1988, ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing.

[6]  Michel Barlaud,et al.  Image coding using wavelet transform , 1992, IEEE Trans. Image Process..

[7]  Jerome M. Shapiro,et al.  Embedded image coding using zerotrees of wavelet coefficients , 1993, IEEE Trans. Signal Process..

[8]  P. Vaidyanathan Multirate Systems And Filter Banks , 1992 .