A Denoising algorithm for remote sensing images with impulse noise
Eun Suk Chang, Chih‐Cheng Hung, Wenping Liu, Jihao Yina · 2016
Noise detection and suppression is one of the important issues in digital image processing. In this study, we develop a new algorithm for detection and suppression of the impulse noise in remote sensing images. The algorithm, called Moran's I Spatial Autocorrelation filter (MSAF), is based on the Standard Median Filter and Moran's I which is used to measure the spatial autocorrelation. Our experimental results show that the MSAF has improved outcomes in terms of Peak Signal-to- Noise Ratio (PSNR) and Mean Square Error (MSE) compared to other filtering algorithms including the Standard Median Filter (SMF), Center Weighted Median Filter (CWMF), Adaptive Center Weighted Median Filter (ACWMF), Decision Based Filter (DBF), Signal-Dependent Rank Ordered Mean Filter (SDROMF) and Modified Decision Based Unsymmetric Trimmed Median Filter (MDBUTMF).