Alaydin, Julide GulenGülen, Seden HazalTrocan, MariaTöreyin, Behçet Uğur2020-04-192020-04-1920142165-0608http://hdl.handle.net/20.500.12416/3370The purpose of the paper is to find the best quantizer allocation for compressed-sensed acquired images, by using a graph-cut quantizer allocation method. The compressed sensed acquisition is realized in a block-based manner, using a random projection matrix, and on the obtained block measurements a graph-cut-based quantizer allocation method is applied, in order to further reduce the bitrate associated to the measurements. Finally, the quantized measurements are reconstructed using a Smooth Projected Landweber recovery method. The proposed compression method for compressed sensed acquisition shows better results when compared to JPEG2000.eninfo:eu-repo/semantics/closedAccessConference Object23102313