This paper is devoted to creation of novel CMOS APS imagers with focal plane parallel image preprocessing for smart technical vision and electro-optical systems based on neural implementation. Using analysis of main biological vision features, the desired artificial vision characteristics are defined. Image processing tasks can be implemented by smart focal plane preprocessing CMOS imagers with neural networks are determined. Eventual results are important for medicine, aerospace ecological monitoring, complexity, and ways for CMOS APS neural nets implementation.
To reduce real image preprocessing time special methods based on edge detection and neighbored frame subtraction will be considered and simulated. To select optimal methods and mathematical operators for edge detection various medical, technical and aerospace images will be tested. The important research direction will be devoted to analogue implementation of main preprocessing operations (addition, subtraction, neighbored frame subtraction, module, and edge detection of pixel signals) in focal plane of CMOS APS imagers. We present the following results: the algorithm of edge detection for analog realization, and patented focal plane circuits for analog image reprocessing (edge detection and motion detection).
CMOS APS Active Pixel Sensors (APS) are very important among others because of their possible technical innovations leading to ultra-low power image acquisition or efficient on-chip image preprocessing. The design of the novel CMOS is presented in the first part of the paper. The general principle of analog interpixel subtraction is described. The edge detection algorithm for analog realization and patented focal plane circuits for analog image preprocessing (signals subtraction, addition, and edge detection) are described. Implementation of the image processing tasks (focal plane preprocessing and subsequent image processing) can be done
effectively only with the consideration of known transfer characteristics of the imager itself. In the second part of the
paper we present analysis of those characteristics. Geometrical Point Spread Function (PSF) depends on the certain
geometric shape of active area in the particular design of CMOS APS. In this paper the concept of Modulation Transfer
Function (MTF) analysis is generalized to be applicable to the sampled structures of CMOS APS. Recalling theoretical
results we have analytically derived the detector MTF in the closed form for some special active area shapes.
This paper is devoted to creation of novel CMOS APS imagers with focal plane parallel image preprocessing. The general principle of analog subtraction is described. The important research direction devoted to analogue implementation of main preprocessing operations (addition, subtraction, neighbored frame subtraction, module, and edge
detection of pixel signals) in focal plane of CMOS APS imagers. The following results are presented: the algorithm of edge detection for analog realization, and patented focal plane circuits for analog image reprocessing (signals subtraction, additional, edge detection).
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