Date of Award
Master of Applied Science (MASc)
Electrical and Computer Engineering
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.
Wang, Heng, "High-fidelity Image Compression for High-throughput and Energy-efficient Cameras" (2010). Open Access Dissertations and Theses. Paper 4552.
McMaster University Library