Advanced motion modeling for three-dimensional video coding

Driven by new multimedia applications and the growing demand for more flexible and efficient transmission of video, a new approach to video coding has been recently proposed as an alternative to classical hybrid schemes. Instead of sequential frame-based predictive processing, the new approach is based on spatio-temporal 3D transforms, open-loop non-predictive processing, and embedded quantization and coding. This thesis investigates motion modeling for this new coding environment, as well as the impact of such modeling on both coder design and performance.; The first aspect of this thesis deals with video coding based on 3D discrete cosine transform (DCT). We analyze 3D DCT spectrum properties of a globally translating image and show how to use its characteristic footprint for fast and efficient video coding. Previous approaches to 3D DCT video coding have lead to rather modest compression gains due to a limited use of motion characteristics in the transform domain. We develop a coefficient scanning order that adapts to motion, unlike the fixed zig-zag scanning of JPEG. We combine this adaptive scanning with a new 3D quantization model to design a low-complexity 3D DCT video coder. The new coder consistently outperforms MPEG-2 both subjectively and objectively (by more than 1.5 dB) at about 25% reduced complexity, while approaching the performance of MPEG-4 (within 0.8 dB) at less than half computational complexity.; The second aspect of this thesis involves the role of motion in emerging video coders based on 3D discrete wavelet transform (DWT) and motion-compensated temporal filtering (MCTF). Motion invertibility, central to the optimality of lifted MCTF implementation, is first investigated. We introduce a metric for invertibility error between two motion fields. We develop advanced motion inversion methods and demonstrate their effectiveness in improving the update lifting step. Experimental results confirm that a better motion inversion, quantified by lower invertibility error, leads to an increase in coding gain up to 0.5 dB over simpler inversion techniques. We propose a new method for occlusion-aware modeling and estimation of motion fields and use it to create an adaptive 3D DWT coding structure. Implicit modeling of occluded/uncovered areas, combined with the use of longer wavelet kernels, improves both the prediction and update lifting steps and results in the overall compression gain of up to 1 dB over a non-adaptive coder. (Abstract shortened by UMI.)...