Colour image coding with wavelets and matching pursuit

Abstract

This thesis considers sparse approximation of still images as the basis of a lossy compression system. The Matching Pursuit (MP) algorithm is presented as a method particularly suited for application in lossy scalable image coding. Its multichannel extension, capable of exploiting inter-channel correlations, is found to be an efficient way to represent colour data in RGB colour space. Known problems with MP, high computational complexity of encoding and dictionary design, are tackled by finding an appropriate partitioning of an image. The idea of performing MP in the spatio-frequency domain after transform such
as Discrete Wavelet Transform (DWT) is explored. The main challenge, though, is to
encode the image representation obtained after MP into a bit-stream. Novel approaches
for encoding the atomic decomposition of a signal and colour amplitudes quantisation are
proposed and evaluated. The image codec that has been built is capable of competing
with scalable coders such as JPEG 2000 and SPIHT in terms of compression ratio.

Date of Award	2013
Original language	English
Supervisor	Ian T. Nabney (Supervisor)