NDLI: Noncausal image prediction and reconstruction

Content Provider	IEEE Xplore Digital Library
Author	Marchand, J.F.P. Rhody, H.E.
Copyright Year	1997
Description	Author affiliation: Center for Imaging Sci., Rochester Inst. of Technol., NY, USA (Marchand, J.F.P.)
Abstract	Summary form only given. Prediction of the value of the pixels in an image is often used in image compression. The residual image, the difference between the image and its predicted value, can usually be coded with fewer bits than the original image. In linear prediction the value of each pixel of an image is estimated from the value of surrounding pixels using a predictor P. In noncausal prediction pixels surrounding the pixel to be predicted are used. In causal prediction only "earlier" pixels are used. Usually noncausal prediction offers better prediction than causal prediction because all pixels surrounding the pixel to be predicted are considered. The reconstruction of the image from the residual after noncausal prediction is more difficult than when causal prediction is used. This paper explores two methods of reconstruction for noncausal prediction: iterative reconstruction and direct reconstruction. As an example, the effect of quantization of the residual on the reconstructed image is considered. It shows an improved image quality using the noncausal predictor.
File Size	72822
File Format	PDF
ISBN	0818677619
ISSN	10680314
DOI	10.1109/DCC.1997.582114
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-03-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image reconstruction Pixel Image generation Image coding Quantization Image quality Image converters Iterative methods Convolution Communication channels
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications

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