1. A method for reconstructing an image from an image detector, the method comprising the steps of: (a) receiving an input image from the image detector, wherein the image detector comprises a grid containing input data; (b) defining a plurality of kernels across the grid, each kernel corresponding to a kernel function and having a first size and a first shape selected from a plurality of possible shapes for defining a footprint within the grid for encompassing a portion of the input data; (c) determining a signal-to-noise ratio and a goodness-of-fit for each kernel, wherein the goodness-of-fit is determined as a global goodness-of-fit weighted by each kernel function mapped into a data space; (d) identifying and eliminating each rejectable kernel from the grid when the signal-to-noise ratio and the goodness-of-fit for the rejectable kernel fail to meet a predetermined minimum criteria; (e) identifying each no-pass kernel where the signal-to-noise ratio and goodness-of-fit exceed the predetermined minimum criteria but fail to meet a predetermined pass criteria; (f) defining a plurality of second iteration kernels at each no-pass kernel location, each second iteration kernel having a second shape selected from the plurality of possible shapes and a second size smaller than the first size; (g) identifying each acceptable kernel where the signal-to-noise ratio and the goodness-of-fit meet the predetermined criteria; (h) selecting at each location with an acceptable kernel an optimal shape from the plurality of possible shapes, wherein the optimal shape has the highest SNR contained within the kernel when compared to kernels having other shapes; (i) repeating steps (c) through (h) with progressively smaller kernels until all remaining kernels meet the predetermined pass criteria; and (j) providing an output image comprising a map of the remaining kernels.