Paper
15 August 1989 Application of a Noise Adaptive Contrast Sensitivity Function to Image Data Compression
Scott Daly
Author Affiliations +
Abstract
The visual contrast sensitivity function (CSF) has found increasing use in image compression as new algorithms optimize the display-observer interface in order to reduce the bit rate and increase the perceived image quality. In most compression algorithms, increasing the quantization intervals reduces the bit rate at the expense of introducing more quantization error, a potential image quality degradation. The CSF can be used to distribute this error as a function of spatial frequency such that it is undetectable by the human observer. Thus, instead of being mathematically lossless, the compression algorithm can be designed to be visually lossless, with the advantage of a significantly reduced bit rate. However, the CSF is strongly affected by image noise, changing in both shape and peak sensitivity. This work describes a model of the CSF that includes these changes as a function of image noise level by using the concepts of internal visual noise, and tests this model in the context of image compression with an observer study.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Scott Daly "Application of a Noise Adaptive Contrast Sensitivity Function to Image Data Compression", Proc. SPIE 1077, Human Vision, Visual Processing, and Digital Display, (15 August 1989); https://doi.org/10.1117/12.952720
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Cited by 7 scholarly publications and 1 patent.
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KEYWORDS
Image compression

Visual process modeling

Visualization

Quantization

Image quality

Spatial frequencies

Data modeling

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