1. A method for image processing, comprising: at an image processor provided with a single two-dimensional detection image comprising a plurality of pixels, each of the pixels being associated with a scalar value representing a relative likelihood that a target is located in a subject pixel, the two-dimensional detection image and associated scalar values being the output of a detection filter for the target applied to a three-dimensional hyperspectral data cube representing a hyperspectral scene collected at a single time: selecting a region of the two-dimensional detection image; for each subset in a plurality of sets of pixels in the selected region, computing a mean of the scalar values of the pixels in the subset; selecting from the plurality of sets of pixels in the selected region, a first subset of pixels in the selected region containing artifacts therein; comparing the mean of scalar values of the pixels in the first subset with the mean of the scalar values of the pixels in a second subset; adjusting the scalar value of each pixel in the first subset based upon the comparing; and reconstructing the provided two-dimensional detection image into a reconstructed two-dimensional image based upon the adjusted scalar value of each pixel in the first subset, such that a variance of scalar values of the pixels in the reconstructed two-dimensional image is lower than a variance of scalar values of the pixels in the two-dimensional detection image.