A novel thresholding technique in the curvelet domain for improved speckle removal in SAR images

Speckle noise is the grainy salt-and-pepper pattern present in radar imagery caused by the interaction of out-of-phase waves with a target. Speckle degrade the spatial resolution, contrast of the image, decreases object detectability and causes inconvenience to the SAR (Synthetic Aperture Radar) image interpreter. Reduction of speckle can be carried out for proper interpretation and object detection. In this work, an improved thresholding technique in the curvelet domain is proposed to reduce the speckle in SAR images and preserve the details of the image. The results of denoised images are compared visually and statistically. The performance of the proposed technique is better compared with improved thresholding technique in the wavelet domain, curvelet denoising and curvelet cycle spin technique.