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Sensors 2017, 17(5), 1070; doi:10.3390/s17051070

A Method of Sky Ripple Residual Nonuniformity Reduction for a Cooled Infrared Imager and Hardware Implementation

School of Optoelectronics, Beijing Institute of Technology, Key Laboratory of Photo-electronic Imaging Technology and System, Ministry of Education of China, Beijing 100081, China
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Academic Editor: A. G. Unil Perera
Received: 16 March 2017 / Revised: 24 April 2017 / Accepted: 5 May 2017 / Published: 8 May 2017
(This article belongs to the Special Issue Infrared Detectors)

Abstract

Cooled infrared detector arrays always suffer from undesired ripple residual nonuniformity (RNU) in sky scene observations. The ripple residual nonuniformity seriously affects the imaging quality, especially for small target detection. It is difficult to eliminate it using the calibration-based techniques and the current scene-based nonuniformity algorithms. In this paper, we present a modified temporal high-pass nonuniformity correction algorithm using fuzzy scene classification. The fuzzy scene classification is designed to control the correction threshold so that the algorithm can remove ripple RNU without degrading the scene details. We test the algorithm on a real infrared sequence by comparing it to several well-established methods. The result shows that the algorithm has obvious advantages compared with the tested methods in terms of detail conservation and convergence speed for ripple RNU correction. Furthermore, we display our architecture with a prototype built on a Xilinx Virtex-5 XC5VLX50T field-programmable gate array (FPGA), which has two advantages: (1) low resources consumption; and (2) small hardware delay (less than 10 image rows). It has been successfully applied in an actual system. View Full-Text
Keywords: ripple fixed pattern noise; nonuniformity correction; fuzzy classification; FPGA ripple fixed pattern noise; nonuniformity correction; fuzzy classification; FPGA
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MDPI and ACS Style

Li, Y.; Jin, W.; Li, S.; Zhang, X.; Zhu, J. A Method of Sky Ripple Residual Nonuniformity Reduction for a Cooled Infrared Imager and Hardware Implementation. Sensors 2017, 17, 1070.

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