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Compressive Sensing Based Imaging Via Belief Propagation, Preethi Modur Ramachandra
Compressive Sensing Based Imaging Via Belief Propagation, Preethi Modur Ramachandra
Masters Theses and Doctoral Dissertations
Multiple description coding (MDC) using Compressive Sensing (CS) mainly aims at restoring an image from a small subset of samples with reasonable accuracy using an iterative message passing decoding algorithm commonly known as Belief Propagation (BP). The CS technique can accurately recover any compressible or sparse signal from a lesser number of non-adaptive, randomized linear projection samples than that specified by the Nyquist rate. In this work, we demonstrate how CS-based encoding generates measurements from the sparse image signal and the measurement matrix. Then we demonstrate how a BP decoding algorithm reconstructs the image from the measurements generated. In our …