A method for image processing at an image processor, wherein the method is provided with a two-dimensional detection image (54; 200A-200E) comprising a plurality of pixels (60, 62), each pixel having a scalar value representing a relative likelihood that a target (202A; 202B) is located in a subject pixel, the two-dimensional detection image (54; 200A-200E) and associated scalar values being the output of a detection filter for the target (202A; 202B) applied to a three-dimensional hyperspectral data cube (58; 302) representing a hyperspectral scene, the method comprising: selecting a region of the two-dimensional detection image (54; 200A-200E) including sensor artifacts that appear as a plurality of striped columns in the two-dimensional image; computing a mean of the scalar values of the pixels in the selected region; selecting from a plurality of sets of pixels in the selected region, a first subset of pixels in the selected region comprising at least one striped column including artifacts (204A-204E) therein; comparing the scalar value of each pixel in the first subset including the at least one striped column with the computed mean of the selected region; adjusting (308e-308f) the scalar value of each pixel in the at least one striped column in the first subset towards the computed mean of the selected region based upon the comparing, wherein the scalar values of those pixels less than the computed mean of the selected region are increased towards the computed mean and the scalar values of those pixels that are greater than the computed mean of the selected region are decreased towards the computed mean of the selected region; repeating the steps of comparing and adjusting on further selected subsets of pixels in the selected region until all striped columns in the selected region have been compared and adjusted; 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 and further selected subsets, wherein a variance of scalar values of the pixels in the reconstructed image is lower than a variance of scalar values of the pixels in the two-dimensional detection image. selecting a region of the two-dimensional detection image (54; 200A-200E) including sensor artifacts that appear as a plurality of striped columns in the two-dimensional image; computing a mean of the scalar values of the pixels in the selected region; selecting from a plurality of sets of pixels in the selected region, a first subset of pixels in the selected region comprising at least one striped column including artifacts (204A-204E) therein; comparing the scalar value of each pixel in the first subset including the at least one striped column with the computed mean of the selected region; adjusting (308e-308f) the scalar value of each pixel in the at least one striped column in the first subset towards the computed mean of the selected region based upon the comparing, wherein the scalar values of those pixels less than the computed mean of the selected region are increased towards the computed mean and the scalar values of those pixels that are greater than the computed mean of the selected region are decreased towards the computed mean of the selected region; repeating the steps of comparing and adjusting on further selected subsets of pixels in the selected region until all striped columns in the selected region have been compared and adjusted; 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 and further selected subsets, wherein a variance of scalar values of the pixels in the reconstructed image is lower than a variance of scalar values of the pixels in the two-dimensional detection image.