Paper
24 June 1994 Real-time adaptive imager
Steven E. Strang, George B. Westrom, Richard D. Holben
Author Affiliations +
Abstract
Most image systems fail when subjected to a scene with areas of high and low intensity. The human vision system is remarkable in its ability to detect objects in deep shadows even in the presence of intensely illuminated areas. This paper describes a nonlinear theory, intensity dependent summation (IDS), which optimizes the information in a scene independent of the intensity and variation in the illumination. The IDS model is a spatially adaptive bandpass filter that is locally adaptive and robust to signal noise. For each input pixel, a spread function is generated whose height and area vary with the input pixel intensity. The output pixel intensity is the sum of all overlapping spread functions. This paper describes a large window convolver whose coefficients are a nonlinear function of the individual pixel intensity. The convolver implements the IDS model as well as more conventional linear filters. The adaptive imager (convolver) described produces a 16-bit output image at RS-170 video rate.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Steven E. Strang, George B. Westrom, and Richard D. Holben "Real-time adaptive imager", Proc. SPIE 2239, Visual Information Processing III, (24 June 1994); https://doi.org/10.1117/12.179280
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Visual process modeling

Convolution

Video

Imaging systems

Image processing

Point spread functions

Photodetectors

RELATED CONTENT

Research on emotion recognition in network video
Proceedings of SPIE (October 13 2022)
Motion magnification using the Hermite transform
Proceedings of SPIE (December 22 2015)
System for parsing MPEG videos
Proceedings of SPIE (December 20 1999)

Back to Top