1. An image rendering method comprising the steps of: (a) performing, using a processor, a noisy estimation of a given view of a given scene of an image using a Monte-Carlo stochastic renderer, wherein general information of each ray sample is stored, (b) calculating a similarity measure between two sets of samples cast from two pixels of said scene and their neighbors, and (c) generating an output image wherein each pixel color is a weighted combination of the pixel colors generated from the step (a) with weights based on the similarity measure of the step (b) between the respective set of samples cast from the pixels and their neighbors; wherein a color histogram is associated with each pixel containing the colors of all rays that hit the pixel; wherein the sample data sets S x and S y cast from pixels x and y, with respective h x k and h y k binned histograms with n b bins, are compared using the Chi-Square distance, namely d χ 2 ⁡ ( S x , S y ) = ∑ k = 1 n b ⁢ ( n y n x ⁢ h x k - n x n y ⁢ h y k ) 2 h x k + h y k where n y =Σh y k and n x=Σh x k are the total number of samples in each set; and wherein, in order to take into account spatial coherence, the previous distance can be extended to patches as follows, d χ 2 ⁡ ( P x , P y ) = ∑  z  ≤ w ⁢ d χ 2 ⁡ ( S x + z , S y + z ) .