Prefiltering and Patch Ordering-based SAR Image Despeckling via Sparse Domain Filtering

In order to suppress speckle noise in synthetic aperture radar (SAR) image and obtain high quality SAR image, this paper proposes a novel method of SAR image denoising by prefiltering the patches before patch ordering. This method firstly performs logarithmic transformation on the SAR image. Then, some dissimilar patches are removed by prefilter before patch ordering. It can avoid unnecessary calculations, suppressing the introduced artificial texture. Finally, ordered patches are filtered by sparse representation. The final denoised image can be reconstructed from the filtered patches via inverse permutation, subimage averaging and exponential transformation. The experimental results of simulated images and real SAR images show that the denoising method proposed in this paper reaches the level of the existing good denoising algorithms in terms of peak signal to noise ratio (PSNR)、structural similarity index (SSIM) and equivalent numbers of looks (ENL). The denoised image has reached the level of the existing good algorithms in visual effect. This method can well maintain the image details and at the same time suppress speckle noise in SAR image.