An adaptive Total Variation (TV)denoisingmethod based on noise detectionis proposed to restore the natural images corrupted by both additive Gaussian noise and randomvalued impulse noise. The improved image restoration method uses a twostage iterative framework: identification of pixels corrupted by impulse noise and TV based image restoration. Firstly, the local statistical value, i.e. Rank Ordered Absolute Difference(ROAD) is used to adaptively detect the pixels corrupted by impulse noise that contains no valid information. Secondly, the L2TV method is used to restore noise images. The two steps are processed iteratively to obtain the denoisedimages. The introduction of impulse noise level parameters in the noise estimation process has the advantage of being able to detect the impulse noise more accurately. The L2TV denoising method can remove the Gaussian noise well. The combination of the two effectively solves the problem that the TV algorithm misjudges image impulse noise as edge and results in false edge. Compared withthe stateoftheart methods, the proposed imagedenoising method, named TVROAD algorithm, can achieve superior restoration results and preserve image detail features.