Extending SAR Image Despckling methods for ViSAR Denoising

Synthetic Aperture Radar (SAR) is widely used in different weather conditions for various applications such as mapping, remote sensing, urban, civil and military monitoring. Recently, a new radar sensor called Video SAR (ViSAR) has been developed to capture sequential frames from moving objects for environmental monitoring applications. Same as SAR images, the major problem of ViSAR is the presence of speckle noise. In this paper, the performance of several image-based denosing methods are studied for despeckling of ViSAR frames through “Frame-by-Frame”, “Averaging” and “3D” schemes. In “Frame-by-Frame” scheme, each video frame is denoised inpdependently of the other frames; whereas, in “Averaging” scheme, the denoised images are averaged along a time window. In “3D” scheme, denoising is performed on 3D blocks in space-time (x-y-t) domain. In addition to these schems, a novel extension on SAR-BM3D method, called ViSAR Incremental BM3D (ViSAR-IBM3D) approache is proposed for video denoising. The SAR-BM3D method performs denoising in two steps. At the first step, it uses wavelet denosing to primitively denoise the original image; in the next step, this image in combination with the original image are used to estimate the final denoised image. The main challenge of SAR-BM3D method is high time complexity especially for video frames. Here, in ViSAR-IBM3D, we benefit from the correlation between the frames of video and utilize the denoised images in previous frame to despckle the current frame. The proposed method can remarkably reduce the time complexity and improve preserving the details and the contrast of the denoised frames. The experimental results evaluated on real-world ViSAR video as well as video with simulated noises show that the proposed 3D filtering scheme and the proposed ViSAR-IBM3D method achieve better denoising performance than the other ones.