Image prior is the key to solving ill-posed problems in image restoration. Since the extreme channels prior deblurring algorithm easily produces ringing artifacts and is unable to suppress noise when the image has significant noise，we take advantage of the total variation based method that can remove noise while preserving edge features， and propose an effective blind image denoising and deblurring model based on total variation before the extreme channels prior. First of all， we introduce the total variational model in the dark channel and the bright channel to protect the edge of the image and eliminating noise or ringing artifacts. Second， the half quadratic splitting technique is used to solve the non-convex problem of the model and estimate the clear image. Finally， the blur kernel of the image is estimated by the iterative multi-scale blind deconvolution. Experimental results show that the proposed model can effectively protect the edge details of the image and eliminate the ringing artifacts while suppressing the noise. Compared with the representative methods in recent years， the robustness， subjective visual effects and objective evaluation indexes of the model are significantly improved.