Adaptive enhancement with speckle reduction for SAR images using mirror-extended curvelet and PSO

Speckle and low contrast can cause image degradation, which reduces the detectability of targets and impedes further investigation of synthetic aperture radar (SAR) images. This paper presents an adaptive enhancement method with speckle reduction for SAR images using mirror-extended curvelet (ME-curvelet) transform and particle swarm optimization (PSO). First, an improved enhancement function is proposed to nonlinearly shrink and stretch the curvelet coefficients. Then, a novel objective evaluation criterion is introduced to adaptively obtain the optimal parameters in the enhancement function. Finally, a PSO algorithm with two improvements is used as a global search strategy for the best enhanced image. Experimental results indicate that the proposed method can reduce the speckle and enhance the edge features and the contrast of SAR images better with comparison to the wavelet-based and curvelet-based non-adaptive enhancement methods.