Hybrid gradient-domain image denoising

Abstract Presented is a new gradient-domain denoising method based on hybrid diffusion (thresholding) functions, combining signal gradient detection (SGD) and signal local directional variance (SLDV). In the process of denoising, the contribution of SGD and SLDV is adaptive to the contents of image. The test results presented here demonstrate that the proposed hybrid method is always on par or exceeding the current state-of-the-art gradient-domain image denoising algorithm which is named as gradient-based Wiener filter (GWF) based on SLDV and the classical Gaussian regularization anisotropic diffusion (GRAD) based on SGD, both visually and quantitatively. At the same time, the comparison compared to other reported results with related local spatial domain diffusion-based methods further verifies the good performance of the proposed method.