In this paper, following the Compressed Sensing (CS) paradigm, we study the problem of recovering sparse or compressible signals from uniformly quantized measurements. We present ...
In this paper, we propose a novel variational framework for the reconstruction of dynamic objects from sparse and noisy tomographic data. Using an object-based scene model, we dev...
Wavelet-based statistical analysis methods for fMRI are able to detect brain activity without smoothing the data. Typically, the statistical inference is performed in the wavelet ...
In this paper, we analyze the perturbation in the reconstructed optical absorption images, resulting from the discretization of the forward and inverse problems. We show that the ...
Murat Guven, Birsen Yazici, Kiwoon Kwon, Eldar Gil...
Scatterometers have been launched primarily to measure ocean winds. The value of scatterometer data is increased by application of the SIR (Scatterometer Image Reconstruction) alg...