Image deconvolution for enhancing IR images in order to detect defects in metallic plates

In this paper, infrared (IR) imaging technique is used in conjunction with image deconvolution algorithms in order to enhance detection capabilities of the NDT personnel in detecting defects such as cracks, voids, and pitting. The main idea utilized here is the fact that the heat distribution remains fairly homogenous in a healthy metal and can be seen as a flat surface under IR imaging camera. However, things change drastically if there is a discontinuity in the homogenous metal, such as defects. This change is exploited in this work as an output of a defect function which produces this output when healthy metal image is given as an input to it. H_¿ deconvolution methodology has been utilized here to isolate (deconvolve) the defect function and be able to regenerate the output image without any other obscuring elements. This can enhance the detection capability of the IR camera as well as the NDT personnel.