In the most application situation, signal or image always is corrupted by additive noise. As a result there are mass
methods to remove the additive noise while few approaches can work well for the multiplicative noise. The paper
presents an improved MAP-based filter for multiplicative noise by adaptive window denoising technique. A Gamma
noise models is discussed and a preprocessing technique to differential the matured and un-matured pixel is applied to
get accurate estimate for Equivalent Number of Looks. Also the adaptive local window growth and 3 different denoise
strategies are applied to smooth noise while keep its subtle information according to its local statistics feature. The
simulation results show that the performance is better than existing filter. Several image experiments demonstrate its
theoretical performance.
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