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Mutual information plays crucial role of similarity measure in some applications such as image registration and image template matching. Therefore estimating the joint probability distribution of underlying image or template is the main problem Non-Parametric window (NP) method considers the images as continuous two-dimensional signals and results an appropriate joint probability distribution. In this paper we employ a triangle distribution with a large support instead of uniform distribution in the original NP. This gives a more precise estimation of joint probability distribution. As a result the compared mutual information is more robust and reliable. Experimental results show the superiority of the proposed method in image template matching with small window size.