1. A method of target detection from hyper-spectral image data comprising a plurality of pixels comprising target spectra of target material and background spectra of background material, the method comprising: determining first filter coefficients using circuit means performing constrained linear programming optimization based on the hyper-spectral image data, the target spectra, and an estimated background spectra; applying a filter comprising the first filter coefficients to the hyper-spectral image data to obtain first filtered pixels; identifying first target pixels from the first filtered pixels; and estimating the estimated background spectra based on the following relationship: x _ = 1 p ⁢ ∑ i = 0 p ⁢ x i where p is a total number of non-excluded pixels, x i is a vector comprising spectra of an i th non-excluded pixel, and x is a vector comprising an averaged spectra of the non-excluded pixels.