An Iterative Non-local Denoising Method of SAR Image Based on Multi-resolution

Synthetic aperture radar (SAR) is an advanced remote sensor, which can observe the earth's surface in all weather conditions, widely used in military reconnaissance and disaster rescue. However, due to the coherent summation of the return echoes and the random electromagnetic interference, a SAR image will be significantly affected by the noise, reducing the readability of the image. To deal with this issue, in this paper, we propose an iterative non-local denoising method based on multi-resolution. First, the cascade downsampling is performed to get the multi-resolution sub-images. Then, the 2D discrete cosine transform is applied to each fragment segmented from the sub-images. After that, grouping the similar fragments by using the pHash algorithm. And the basic denoising image can be obtained by performing collaborative filtering and aggregating. Finally, a denoising image can be acquired after iterating processing. Real airborne SAR data is used to validate the effectiveness of the proposed method.