Constrained Optimization Of Filter Banks In Subband Image Coding

The design of filter banks in subband image coding is critical for achieving high image quality. In this paper, we study the design from both the signal processing domain and the theory of wavelets. We formulate the design of filter banks as a two-stage nonlinear constrained optimization problem, each of which is solved by sequential quadratic programming (SQP). Using a wavelet image coding prototype, we show improved quality of the designed filter banks in terms of imagecompression and peak signal-to-noise ratios (PSNRs). INTRODUCTION Subband image coding is a transform-based coding technique that uses a subband transform to reduce or remove spatial redundancies. This transform can be represented by a filter bank (Figure 1) with an analysis subsystem, including filters H 0 (z), H 1 (z), and two decimators, followed by a synthesis subsystem, including filters F 0 (z), F 1 (z), and two interpolators. 2 2 2 2 x(n) H 1 (z) F 0 (z) F 1 (z) H 0 (z) x(n) y 1 (n) y 0 (n) Figure 1:..