Constrained optimization of filter banks in subband image coding

Abstract

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 image compression and peak signal-to-noise ratios (PSNRs).