Historical document often suffer from degradations, such as faint characters, smears and large background stains, that renders their binarization a challenging task. Motivated by the ideas that the text within document usually has a different intensity level compared with the surrounding background and the document background estimation is a way to effectively attenuate degraded regions, a new approach for the binarization of historical document is proposed in this paper. The proposed method contains three steps. First, we follow an inpainting procedure which using the Niblack binarization output to estimates the rough background. Then, image contrast normalization procedure is used to balance different types of historical document degradation by using the rough document background estimation. Finally, the document text is enhanced and segmented by an existing binarization technology from the normalized historical document images. The proposed approach has been tested on the DIBCO and H-DIBCO datasets of history document images and outperforms state-of-the-art techniques.