In bilateral total variation regularization method(BTV), considering geometric distance and gray level similarity of the center pixel and the surrounding pixels, the method to get better reconstruction quality than Tikhonov regularization method and total variation regularization method (TV) is obtained. However, in BTV method, the regularization parameter λ is a fixed value, so the method cannot maintain the image edge texture information and suppress image noise at the same time. In order to solve this problem, an adaptive regularization reconstruction algorithm for image local texture feature is proposed, and based on gray level co-occurrence matrix(GLCM), the image local texture feature is extracted, the function relationship of regularization parameters and image local texture feature is established, so regularization parameter λ is adjusted adaptively according to image local texture feature. The experimental results show that compared with BTV, this algorithm can better reconstruct the image edge texture details and suppress the noise effectively.