Author

Heng Wang

Date of Award

11-2010

Degree Type

Thesis

Degree Name

Master of Applied Science (MASc)

Department

Electrical and Computer Engineering

Supervisor

Xiaolin Wu

Co-Supervisor

Sorina Dumitrescu

Language

English

Abstract

In this thesis, we propose a new encoder-friendly image compression strategy for high-throughput cameras and other scenarios of resource-constrained encoders. The encoder performs L∞-constrained predictive coding (DPCM coupled with uniform scalar quantizer), while the decoder solves an inverse problem of L2 restoration of L∞-coded images. Although designed for minimum encoder complexity (lower than distributed source coding and compressive sensing), the new codec outperforms state-of-the-art encoder-centric image codecs such as JPEG 2000 in PSNR for bit rates higher than 1.2 bpp, while maintaining much tighter L∞ error bounds as well. This is achieved by exploiting the tight error bound on each pixel provided by the L∞-constrained encoder and by locally adaptive image modeling.

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