One of the amazing properties of human vision is its ability to feel the depth of the scenes
being viewed. This is made possible by a process named stereopsis, which is the ability of
our brain to fuse together the stereo image pair seen by two eyes. As a stereo image pair is a
direct result of the same scene being viewed by a slightly different perspective they open up a
new paradigm where spatial redundancy could be exploited for efficient transmission and
storage of stereo image data.
This thesis introduces three novel algorithms for stereo image compression. The first
algorithm improves compression by exploiting the redundancies present in the so-called
disparity field of a stereo image pair. The second algorithm uses a pioneering block coding
strategy to simultaneously exploit the inter-frame and intra-frame redundancy of a stereo
image pair, eliminating the need of coding the disparity field. The basic idea behind the
development of the third algorithm is the efficient exploitation of redundancy in smoothly
textured areas that are present in both frames, but are relatively displaced from each other
due to binocular parallax. Extra compression gains of up to 20% have been achieved by the
use of these techniques.
The thesis also includes research work related to the improvement of the MPEG-4 video
coding standard, which is the first audiovisual representation standard that understands a scene as a composition of audio-visual objects. A linear extrapolation based padding
technique that makes use of the trend of pixel value variation often present near object
boundaries, in padding the exterior pixels of the reference video object has been proposed.
Coding gains of up to 7% have been achieved for coding boundary blocks of video objects.
Finally a contour analysis based approach has been proposed for MPEG-4 video object
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.