Hybrid Deep Learning for Image Denoising: Balancing Noise Removal and Detail Preservation with Game Theory
Image denoising aims to suppress noise while preserving fine details, a challenge for multimedia and computer vision applications.
image restoration
A new Lattice Boltzmann method for a Gray–Scott based model applied to image restoration and contrast enhancement
The aim of this work is to propose a new numerical approach to image restoration and contrast enhancement based on a reaction-diffusion model (Gray–Scott model). For noise removal, a Lattice Boltzmann technique is used. This method is usually used in fluid dynamics experiments. Since pixels motion can be compared to fluids motion, the presented technique also indicates a good performance in processing noisy images. The efficiency and performance of the proposed algorithm are verified by several numerical experiments.