Paper
27 February 1996 Projection onto the narrow quantization constraint set for postprocessing of scalar quantized images
Dongsik Kim, Seop Hyeong Park
Author Affiliations +
Proceedings Volume 2727, Visual Communications and Image Processing '96; (1996) https://doi.org/10.1117/12.233223
Event: Visual Communications and Image Processing '96, 1996, Orlando, FL, United States
Abstract
Since the postprocessing of image data using a priori information depends on the constraints imposed on the decoded images, it is important to utilize constraints which are best suited to postprocessing techniques. Among the constraint sets, the quantization constraint set (QCS) is commonly used in various algorithms that are especially based on the theory of projection onto convex sets. In general, the QCS is the closure of the corresponding known quantization region, since such a QCS is the smallest set that is easily predictable at the decoder and always includes the original image before quantization. Our work, however, has revealed that the ordinary QCS is not optimal in the sense of minimum mean square error. Surprisingly, under certain conditions the optimal QCS is always obtained when the boundary of the QCS is narrower than that of the ordinary QCS. In this paper we propose the narrow quantization constraint set (NQCS) as a substitute for the ordinary QCS. We also present mathematical analysis and simulations which demonstrate that the NQCS works better than the ordinary QCS on natural images.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dongsik Kim and Seop Hyeong Park "Projection onto the narrow quantization constraint set for postprocessing of scalar quantized images", Proc. SPIE 2727, Visual Communications and Image Processing '96, (27 February 1996); https://doi.org/10.1117/12.233223
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Cited by 4 scholarly publications.
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KEYWORDS
Quantization

Distortion

Linear filtering

Image filtering

Mathematics

Projection systems

Video compression

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