The knowledge of the noise level within an image is a valuableinformation for many image processing applications. Estimating the noise level function (NLF) requires the identification of homogeneous regions, upon which the noise parameters are computed. Sutour et al. have proposed a method to estimate this NLF based on the search for homogeneous regions of square shape. We generalize this method to the search for homogeneous regions with arbitrary shape thanks to the tree of shapes representation of the image under study, thus allowing a more robust and precise estimation of the noise level function.