Aiming at the shortcomings of the traditional total variational denoising methods, such as low peak SNR and low iteration efficiency, a new adaptive total variational denoising model is proposed in this paper. Firstly, the regular exponent of the total variational equation is improved by using differential curvature to distinguish noise points. Then, combined with the properties of level set curvature and gradient mode, the smooth region and edge region can achieve different denoising effects, so that the new model can preserve both edge and smooth noise. Experimental results show that compared with the current three mainstream models, the new model improves the peak signal to noise ratio (PSNR) by more than 1. 4 dB, reduces the mean absolute error by more than 2. 5, improves the iteration efficiency by at least 1. 6 times, and increases equally the structural similarity by 0. 13, which is more beneficial to practical application.