RECONSTRUCTION OF PASSIVE MILLIMETER-WAVE IMAGES WITH GRAPH CUTS

We present in this paper a method to reconstruct passive millimeter-wave images. We formulate the Graph Cuts concept to estimate the image by performing a global optimization through all the samples of the passive millimeter-wave radiometer. Our scheme assigns labels for each pixel to be reconstructed by defining a cost function consisting of two terms. The first term reflects the cost that each pixel can have by taking a certain label value. The second term ensures that the image is piecewise smooth. For the latter, we assess the performance of several discontinuity cost models to find out which model is best suited to our problem. Compared to state of the art schemes, results show that our method leads to images with enhanced contrast and the shapes of the objects are better preserved. Compared to optimization schemes like belief propagation, the graph cuts scheme leads to improved temperature resolution and is more robust against label assignment.