Most of business documents , in particular invoices , are composed of an existing color template and an added filled-in text by the users. The direct layout analysis without separating the preprinted form from the added text is difficult and not efficient. Previous works use both local features and global layout knowledge to separate the pre-printed forms and the added text. Although for real applications , they are even exposed to a great improvement. This paper presents the first pixel-based image registration of color business documents based on the NonLocal-Means (NLM) method. We prove that the NLM , commonly used for image denoising , can be also adapted to images registration at the pixel level. Our intuition tends to look for a similar neighbourhood from the first image I1 into the second image I2 and provide both an exact image registration with a precision at pixel level and noise removal. We show the feasibility of this approach on several color images of various invoices and forms in real situation and its application to the layout analysis. Applied on color documents , the proposed algorithm shows the benefits of the NLM in this context .