Lossy Image Reconstruction using Adaptive Wavelet Filter Bank

In this paper we have used a previously reported adaptive filter bank structure for image decomposition and lossy reconstruction. We used a robust 2D windowed LS (LSW) adaptation algorithm to change the filter parameters and to adapt them to the local image properties. To improve the coding gain of the lossy image compression scheme, quantization of the adapted filter parameters has been explored. We used a CDF-based method followed by an optimization procedure to find the best quantization values. The proposed method was applied to a number of synthetic and real world images. Reconstructed images were perceptually superior, achieving lower square error norm when compared to the well-known fixed wavelet scheme.