A NEW TOTAL VARIATION REGULARIZATION-BASED MODEL FOR ADDITIVE NOISE REMOVAL USING GLOBAL MESHLESS COLLOCATION SCHEME

Abstract

In this work, we proposed a new Total Variation (TV) regularization-based model for additive noise removal problems using the Global Meshless Collocation Scheme (GMCS). This new approach not only solves the associated Partial Differential Equation (PDE) connected to the proposed model for the smooth solution regarding image restoration, and preservation of edge but also for minimization of the staircase effect due to which the image looks blocky. The experimental result demonstrates that the proposed model and meshless scheme seek to improve computational efficiency and noise removal accuracy in terms of visual efficiency and Peak-Signal-to-Noise-Ratio (PSNR) values compared to other traditional-based methods