Paper
24 June 1994 Assessment of image coding by information theory
Zia-ur Rahman, Carl L. Fales, Friedrich O. Huck
Author Affiliations +
Abstract
The task of image coding is to improve the efficiency of visual communication channels. This entails minimizing the amount of data required to transmit the information about the radiance field. We assess this task in the context of visual communication channel design including image gathering, coding, and Wiener restoration which results in channel designs with significantly improved performance. Conventional assessments are limited to the digital transmission channel beginning at the output of the image-gathering device and ending at the input to the image-display device. Our end-to-end assessment, in addition, incorporates these two devices. This assessment combines Shannon's communication theory with Wiener's restoration filter and with the critical design factors of the image gathering and display devices. This provides the metrics needed to quantify and optimize the end-to-end performance of the visual communication channel. The results are described.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zia-ur Rahman, Carl L. Fales, and Friedrich O. Huck "Assessment of image coding by information theory", Proc. SPIE 2239, Visual Information Processing III, (24 June 1994); https://doi.org/10.1117/12.179290
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Quantization

Signal to noise ratio

Image compression

Image restoration

Visual communications

Visualization

Image processing

RELATED CONTENT


Back to Top