Department of Applied Sciences of the College of Staten Island, City University of New York, 130, Stuyvesant Place, Staten Island, NY 10301, USA
Abstract:
Digital monochromatic images are encoded using a novel minimum mean square error (MSE) linear predictive transform (LPT) coding formulation. The new formulation is appealing for two important reasons. First, it leads to simple coder implementation with a satisfactory signal-to-noise ratio (SNR). Second, it provides a general theoretical framework from which minimum MSE predictive coding and minimum MSE transform coding arise as special cases. Some specific results of this paper that illustrate the previous ideas are: a simple and generally suboptimum two-dimensional LPT coder operating at 2 bit pixer−1 has approximately one third the complexity of a 4 × 4 Hadamard coder while yielding a better SNR; an optimum 2D LPT coder operating at 2 bit pixer−1 has approximately one sixth the complexity of a 4 × 4 Karhunen-Loeve transform (KLT) coder while yielding a better SNR.