Previsualized image vector quantization with optimized pre- and postprocessors

Xie, Zongbo; Stockham, Thomas G.

doi:10.1109/26.111447

Cited by 2 publications

(1 citation statement)

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“…Other perceptually-based pre-and postprocessing work includes the work in Ref. 194 which incorporates a visual model as part of the distortion metric in a vector quantization coding scheme. The preprocessing step consists of a visual model and preemphasis filter while the postprocessing step consists of a deemphasis filter and the inverse visual model.…”

Section: Pre-and Postprocessing For Image Compressionmentioning

confidence: 99%

Image and Video Compression: A Review

Podilchuk

Safranek

1997

Selected Topics in Electronics and Systems

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The area of image and video compression has made tremendous progress over the last several decades. The successes in image compression are due to advances and better understanding of waveform coding methods which take advantage of the signal statistics, perceptual methods which take advantage of psychovisual properties of the human visual system (HVS) and object-based models especially for very low bit rate work. Recent years have produced several image coding standards-JPEG for still image compression and H.261, MPEG-I and MPEG-II for video compression. While we have devoted a special section in this paper to cover international coding standards because of their practical value, we have also covered a large class of nonstandard coding technology in the interest of completeness and potential future value. Very low bit rate video coding remains a challenging problem as does our understanding of the human visual system for perceptually optimum compression.The wide range of applications and bit rates, from video telephony at rates as low as 9.6 kbps to HDTV at 20 Mbps and higher, has acted as a catalyst for generating new ideas in tackling the different challenges characterized by the particular application. The area of image compression will remain an interesting and fruitful area of research as we focus on combining source coding with channel coding and multimedia networking.

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Section: Pre-and Postprocessing For Image Compressionmentioning

confidence: 99%