ABSTRACT
Lapped orthogonal transforms are good candidates for processing signals from several engineering disciplines, including speech and image. The goal of transformations is to achieve data compression. These transforms were introduced by H. S. Malvar and D. H. Staelin in 1988. Jean Ville suggested in 1948 that signals can be studied in two different ways. In one technique, the signal is split into several successive blocks in time domain, and then each block is individually analyzed in the frequency domain. Orthogonal transforms are a valuable tool in the art and science of data compression. The goal of data compression is to represent discrete signals with a small expected number of bits per sample. In the method of data compression via orthogonal transforms, blocks of discrete signals of fixed length are transformed. In order to achieve data compression, the spectral coefficients are quantized, and then encoded for a more efficient representation. Quantization process is essentially nonlinear, and hence irreversible.
