<title>Adaptive filtering image preprocessing for smart FPA technology</title>

Abstract

This paper discusses two applications of adaptive filters for image processing on parallel architectures. The first, based on the results of previously accomplished work, summarizes the analyses of various adaptive filters implemented for pixel-level image prediction. FIR filters, fixed and adaptive IIR filters, and various variable step size algorithms were compared with a focus on algorithm complexity against the ability to predict future pixel values. A gaussian smoothing operation with varying spatial and temporal constants were also applied for comparisons of random noise reductions. The second application is a suggestion to use memory-adaptive IIR filters for detecting and tracking motion within an image. Objects within an image are made of edges, or segments, with varying degrees of motion. An application has been previously published that describes FIR filters connecting pixels and using correlations to determine motion and direction. This implementation seems limited to detecting motion coinciding with FIR filter operation rate and the associated harmonics. Upgrading the FIR structures with adaptive IIR structures can eliminate these limitations. These and any other pixel-level adaptive filtering application require data memory for filter parameters and some basic computational capability. Tradeoffs have to be made between chip real estate and these desired features. System tradeoffs will also have to be made as to where it makes the most sense to do which level of processing. Although smart pixels may not be ready to implement adaptive filters, applications such as these should give the smart pixel designer some long range goals.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.