Real-time adaptive imager
Steven E. Strang, George B. Westrom, Richard D. Holben · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1994
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.