A new algorithm for detecting and correcting bad pixels in infrared images
Restrepo Girón, Andrés David
Loaiza Correa, Humberto
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An image processing algorithm detects and replaces abnormal pixels individually, highlighting them amongst their neighbours in a sequence of thermal images without affecting overall texture, like classical filtering does. Bad pixels from manufacture or constant use of a CCD device in an IR camera are thus detected and replaced with a very good success rate, thereby reducing the risk of bad interpretation. Some thermal sequences from CFRP plates, taken by a Cincinnati Electronics InSb IR camera, were used for developing and testing this algorithm. The results were compared to a detailed list of bad pixels given by the manufacturer (about 70% coincidence). This work becomes relevant considering that the number of papers on this subject is low; most of them talk about astronomical image pre-processing. Moreover, thermographic non-destructive testing (TNDT) techniques are gaining popularity in Colombia at introductory levels in industrial sectors such as energy generation and transmission, sugar production and military aeronautics.