Image Denoising Using Hybrid Model with Edge Preserving Capability
Bo Chen, Jianhuang Lai, Pong Chi Yuen · 2006
The use of partial differential equations in image processing and computer vision has increased dramatically in recent years. The paper address to image denoising. A new model is introduced by extending alphabetaomega (ABO)-model in order to get high fidelity of the denoised images. To solve the model efficiently and reliably, we suggest a simple and symmetrical difference schemes and incorporate them with the essentially nondissipative difference (ENoD) schemes. We remove the impulse and Gaussian noises from different images and compare the PSNR values of the results with traditional filters. Numerical experimental results have shown the new model's effectiveness in restoring images, especially in edge preservation and enhancement