Enhancement of SAR Imagery using DWT

This paper presents a new approach for the enhancement of Synthetic Radar Imagery using Discrete Wavelet Transform and its variants. Some of the approaches like nonlocal filtering (NLF) techniques, and multiscale iterative reconstruction (e.g., the BM3D method) do not solve the RE/SR imaging inverse problems in descriptive settings imposing some structured regularization constraints and exploits the sparsity of the desired image representations for resolution enhancement (RE) and superresolution (SR) of coherent remote sensing (RS). Such approaches are not properly adapted to the SR recovery of the speckle-corrupted low resolution (LR) coherent radar imagery. These pitfalls are eradicated by using DWT approach wherein the despeckled/deblurred HR image is recovered from the LR speckle/blurry corrupted radar image by applying some of the descriptive-experiment-design-regularization (DEDR) based re-constructive steps. Next, the multistage RE is consequently performed in each scaled refined SR frame via the iterative reconstruction of the upscaled radar images, followed by the discrete-wavelet-transform-based sparsity promoting denoising with guaranteed consistency preservation in each resolution frame. The performance of the method proposed is compared in terms of the number of iterations taken by it with other techniques existing in the literature.