Self-Healing Imager Based on Detection and Conciliation of Defective Pixels

Abstract

This paper presents imager self-healing method based on detection and correction of defective pixels in the produced image file. The proposed method uses a neighborhood analysis with simple arithmetic operations including distance between the to-be-tested pixel and its neighbor pixels. A 2-dimensional 3 by 3 gray-scale image matrix around the to-be-tested pixel is used to estimate an expected pixel value and a weighted average. This average value is used as an adaptive threshold of the difference value between expected and actual pixel values. The performances in terms of sensibility, specificity, predictive values, and phi-coefficient of the produced results on a set of 144 distorted images (24 references images $\times$ 6 distortion types), are compared to another dead pixel detection methods performances. Experimental results demonstrated that our proposal produces the best results.