Date of Award

Spring 2013

Degree Type

Thesis

Degree Name

Master of Applied Science (MASc)

Department

Electrical and Computer Engineering

Supervisor

Xiaolin Wu

Language

English

Abstract

In many scientific, medical and defense applications of image/video compression, an l∞ error bound is required. However, pure l∞-optimized image coding, colloquially known as near-lossless image coding, is prone to structured errors such as contours and speckles if the bit rate is not sufficiently high; moreover, previous l∞-based image coding methods suffer from poor rate control. In contrast, the l2 error metric aims for average fidelity and hence preserves the subtlety of smooth waveforms better than the l∞ error metric and it offers fine granularity in rate control; but pure l2-based image coding methods (e.g., JPEG 2000) cannot bound individual errors as l∞-based methods can. This thesis presents a new compression approach to retain the benefits and circumvent the pitfalls of the two error metrics.

McMaster University Library


Download

Share

COinS