Parametric faults detection and concealment on imager with FPGA implementation

International audience; This paper presents an online and integrated solution for self-healing of parametric faults on an image sensor. This self-healing is based on the detection and concealment of the parametric faults in the image sensor. Three detection methods are considered. The first one is based on the distance between the pixel under test and its neighboring pixels, the second method is based on the median of the block of pixels around the pixel under test, and the third method is based on the local dispersion parameters in the image. The concealment method is based on the median filter, which consists of the substitution of the defective value by the median value of the pixel block. The metrics used for comparison of the experimental results are phi-coefficient, peak signal to noise ratio (PSNR) and a full reference image quality assessment method based on machine learning techniques (FrIQA). The detection and concealment processes are implemented on an FPGA platform to evaluate the computational complexity and to confirm the feasibility of integrating the proposed solutions in an image sensor.