An image enhancement methodology and FPGA-based implementation combining fuzzy logic and image convolution for an infrared imaging system

Ajay Kumar; S. Sarkar; R. P. Agarwal

doi:10.1117/12.665166

16 May 2006 An image enhancement methodology and FPGA-based implementation combining fuzzy logic and image convolution for an infrared imaging system

Ajay Kumar, S. Sarkar, R. P. Agarwal

Author Affiliations +

Proceedings Volume 6207, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVII; 62070X (2006) https://doi.org/10.1117/12.665166
Event: Defense and Security Symposium, 2006, Orlando (Kissimmee), Florida, United States

Abstract

Modern infrared imaging systems are designed based on highly sensitive infrared focal plane arrays (IRFPA), in which most of the preprocessing is done on the focal plane itself. In spite of many advances in the design of IRFPAs, it has inherent non-uniformities and instabilities, which limits its sensitivity, dynamic range and other advantages. Whenever there is little or no thermal variation in the scene, the thermal imager suffers from its inability to separate out the target of interest from its background. Thus, most of the infrared imagery suffers from poor contrast and high noise. A methodology for contrast enhancement that combines the fuzzy based processing and spatial processing is proposed. Fuzzy based processing improves the image where there are inaccuracies and uncertainties in the image, where as spatial processing is used for improving the contrast and enhancing the details. This results the overall improvement in the image quality under all conditions. This algorithm has been tested on the field-recorded data and is observed that this technique offers excellent results for thermal imager operating in both 3-5 μm and 8-12 μm wavelength regions.

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Ajay Kumar, S. Sarkar, and R. P. Agarwal "An image enhancement methodology and FPGA-based implementation combining fuzzy logic and image convolution for an infrared imaging system", Proc. SPIE 6207, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVII, 62070X (16 May 2006); https://doi.org/10.1117/12.665166

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