The total variation image debluring model (ROF) based on energy functional opened up a new area of research on image processing

particularly on the application of partial differential equations. The defects of the ROF model have prompted many scholars to study the improved model and its algorithm. These scholars have achieved good Results. This study presents a TV image denoising model based on energy functionals and HVS. The existence of solutions for the denoising model in this paper is proven by using the comparison principle of the partial differential equation

and the Euler-Lagrange equation of the model is given using the variation principle. In terms of the numerical calculation of the model

this study discusses the discrete form of numerical approximation solution through artificial time algorithm

finite difference Methods

and numerous image denoising MATLAB experiments. Finally

the two indexes of noise quality are evaluated based on the peak signal-to-noise ratio (PSNR) and mean structural similarity (MSSIM). The (0.5~1) dB PSNR and the (0.05~0.3) MSSIM present an improvement based on the experimental data and Results. From the analysis of denoising

the TV image denoising model based on energy functionals and HVS can maintain the image edge and texture features and is thus superior to conventional TV denoising models.