A NEW HYBRID SCHEME FOR TIKHONOV REGULARIZATION BASED MODEL FOR SIGNAL RESTORATION HAVING ADDITIVE NOISE

Abstract

Signal restoration plays an important role in signal processing and computer vision. In this article, we proposed a new Hybrid meshless scheme, which is the combination of a local meshless scheme and a domain decomposition method for signal restoration having additive Gaussian noise. These combined properties used in the proposed hybrid scheme divide the signal domain into local domains, which easily control the discontinuous jumps in derivatives in small domains and hence produce good restoration results as compared to other mesh-based and meshless schemes. The experimental results will demonstrate that the proposed hybrid scheme outperforms mesh-based and meshless schemes in terms of SNR values, computational times, and iterations required for convergence in image restoration