Image restoration and enhancement based on tunable forward-and-backward diffusion
Yi Wang, Ruiqing Niu, Xin Yu, Liangpei Zhang, Huanfeng Shen · Optical Engineering · 2010
In order to improve signal-to-noise ratio (SNR) and contrast-to-noise ratio, we introduces a novel tunable forward-and-backward (TFAB) diffusion approach for image restoration and edge enhancement. In the TFAB algorithm, an alternative forward-and-backward (FAB) diffusion process is presented, where it is possible to better modulate all aspects of the diffusion behavior and it shows better algorithm behavior compared to the existing FAB diffusion approaches. In addition, there is no necessity to laboriously determine the value of the gradient threshold. We believe the TFAB diffusion to be an adaptive mechanism for image restoration and enhancement. Qualitative experiments, based on various general digital images and a magnetic resonance image, show significant improvements when the TFAB diffusion algorithm is used versus the existing anisotropic diffusion and the previous FAB diffusion algorithms for enhancing edge features and improving image contrast. Quantitative analyses, based on peak SNR and the universal image quality index, confirm the superiority of the proposed algorithm.