1. A method for detecting faint perturbations of interest in an image comprising: estimating a local mean and variance for each of a plurality of pixels in the image; analyzing, using a processor, a local region of the image, an image mean, and an image variance using a filter bank, thereby generating a plurality of response vectors; determining a likelihood of a local perturbation in the image using a probability distribution based on the plurality of response vectors; and making a classification decision of the local perturbation, wherein the probability distribution is calculated, for each of the plurality of response vectors, as p b ⁡ ( i b , μ b , σ b 2 ) = 1 2 ⁢ σ b 2 ⁢ ⅇ - ( i b + μ b ) / 2 ⁢ σ b 2 ⁡ ( i b μ b ) k b / 4 - 1 / 2 ⁢ I k b / 2 - 1 ⁡ ( i b ⁢ μ b σ b 2 ) , i b ≧0, and wherein k b is 1 if q b =0, otherwise k b is 2, and I k is a modified Bessel function of a first kind.