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A New Alternating Minimization Algorithm for Total Variation Image Reconstruction
We propose, analyze and test an alternating minimization algorithm for recovering images from blurry and noisy observa- tions with total variation (TV) regularization. This algorithm arises from a new half-quadratic model ...
Sparse Signal Reconstruction via Iterative Support Detection
We present a novel sparse signal reconstruction method "ISD", aiming to achieve fast reconstruction and a reduced requirement on the number of measurements compared to the classical L1 minimization approach. ISD addresses ...
A Fast Algorithm for Edge-Preserving Variational Multichannel Image Restoration
We generalize the alternating minimization algorithm recently proposed in  to effciently solve a general, edge-preserving, variational model for recovering multichannel images degraded by within- and cross-channel ...