An adaptive noise smoothing filter for remotely-sensed images with microphonic noise
CHENG SHI · International Journal of Remote Sensing · 1989
In this paper we consider the restoration of airborne scanner images with microphonic noise. According to the practical generation process of micro-phonic noise, the noise can be assumed multiplicative and to be a stationary Markov random sequence. An adaptive noise smoothing filter, based on the Kalman filter and NMNV (non-stationary mean and non-stationary variance) image model, is developed. The microphonic noise in airborne scanner images can be effectively filtered out by this adaptive filter. Results of the algorithm on simulation and realistic images are shown.