The multitude of visual media based applications demands sophisticated compression and indexing techniques for efficient storage, transmission, and retrieval of images and video. Wavelet transform has emerged as a powerful tool for efficient compression of images and video sequences. However, there is a need for significant enhancements in the motion estimation process in order to design an efficient wavelet-based video coder. More importantly, there has been little work done in the area of image and video indexing in the wavelet domain. These are crucial for consideration of wavelets as a potential candidate for multimedia applications. Hence there is an impending need for investigating joint compression and indexing approaches in the wavelet transform domain which is the principal focus of this thesis.

In this thesis, we have proposed several novel coding and indexing techniques in the wavelet domain. The proposed coding techniques emphasize efficient motion estimation techniques for a wavelet-based video coder, which include bi-directional motion estimation, fine-to-coarse motion estimation, and variable block-size motion estimation. The proposed indexing techniques include moment-based indexing, fast wavelet histogram indexing, indexing based on distribution of wavelet coefficients, illumination invariant indexing, and robust video segmentation. An efficient video storage and archival system has been developed by combining all proposed techniques. The novelty of the coding and indexing techniques is that both employ a set of key features that describe the content of the visual data. This results in superior performance with lower storage space requirement, and reduced computational complexity.