Real Time Image Enhancement with Resistive Grids

The dynamic range of modern image sensors can exceed the range of a video monitor by an order of magnitude or more. This means that fast and intelligent range compression and image enhancement must be interposed between the sensor and display for effective surveillance and target tracking. Digital hardware can enhance an image in real time, but the common method for range compression on digital hardware, linear filtering, can severely distort the image. We propose to research and develop integrated analog image processors with nearest-neighbor interconnect architectures that carry out nonlinear filtering for range compression and image enhancement at video rates. The nonlinear filtering intelligently compresses the range without distortion. Digital processors, which comsume orders of magnitude more power than this kind of processor, are not capable of applying a similarly effective and distortion-free algorithm in real time. Our Phase I effort will include the design, fabrication and test of circuits to improve the state of the art of such processors, and will include the demonstration and evaluation of an EXISTING low-resolution analog video image processor. Our approach will utilize commercial CMOS/bulk integrated circuit technology; products arising from this R&D can be fabricated reliably and economically by a number of vendors.