Novel infrared image filtering algorithm for filtering out both Gaussian and salt-and-pepper noises

Different from the rare algorithms that can also filter out Gaussian and salt-and-pepper noises, our novel algorithm is based on grey relational analysis (GRA). In the paper, we explain in detail how the GRA effectively removes noises when images are corrupted by Gaussian and salt-and-pepper noises. We explain how the GRA is related to edge detection and how to select sequences according to four operators in 3 × 3 neighborhood pixels of the image. Based on this, we calculate the grey relational degrees between the two sequences. Using the grey relational filtering-out algorithm to compare the four directions of grey relational degrees, we distinguish the noise pixels from the non-noise pixels, the processing of which produces images without noise. We also make an experiment on noise removal from a visible light image and an infrared image respectively by adding Gaussian noise and salt-and-pepper noise. The experimental results show that our filtering-out algorithm can relatively effectively remove the Gaussian noise and salt-and-pepper noise in both visible light image and infrared image.