Remote sensing image noise reduction using wavelet coefficients based on OMP

In recent years, many approaches have been put forward to reduce the noise of a remote sensing image. In this paper, we present an improved method WCOMP based on OMP algorithm for the remote sensing image denoising. We introduce coefficients of wavelet transform into a greedy strategy, combine OMP algorithm with SVD decomposition to train these coefficients with the redundant dictionary of discrete cosine transform (DCT) to achieve the sparse representation of the image, and then reconstruct this image. The goal of our method is to improve the final performance of the image noise reduction. The experiment results show that the WCOMP method performs better than the conventional image denoising methods such as wavelet, Contourlet and K-SVD. Our proposed method can more effectively filter out the noise and keep the original image useful information, compared with these conventional denoising methods.