Robust multiresolution techniques for image reconstruction

Michael Liebling

doi:10.1117/12.701352

27 February 2007 Robust multiresolution techniques for image reconstruction

Michael Liebling

Proceedings Volume 6437, Photons Plus Ultrasound: Imaging and Sensing 2007: The Eighth Conference on Biomedical Thermoacoustics, Optoacoustics, and Acousto-optics; 64371C (2007) https://doi.org/10.1117/12.701352
Event: SPIE BiOS, 2007, San Jose, California, United States

Abstract

The reconstruction of images from projections, diffraction fields, or other similar measurements requires applying signal processing techniques within a physical context. Although modeling of the acquisition procedure can conveniently be carried out in the continuous domain, actual reconstruction from experimental measurements requires the derivation of discrete algorithms that are accurate, efficient, and robust. In recent years, wavelets and multiresolution approaches have been applied successfully for common image processing tasks bridging the gap between discrete and continuous representations. We show that it is possible to express many physical problems in a wavelet framework, thereby allowing the derivation of efficient algorithms that take advantage of wavelet properties, such as multiresolution structure, sparsity, and space-frequency decompositions. We review several examples of such algorithms with applications to X-ray tomography, digital holography, and confocal microscopy and discuss possible future extensions to other modalities.

Citation Download Citation

Michael Liebling "Robust multiresolution techniques for image reconstruction", Proc. SPIE 6437, Photons Plus Ultrasound: Imaging and Sensing 2007: The Eighth Conference on Biomedical Thermoacoustics, Optoacoustics, and Acousto-optics, 64371C (27 February 2007); https://doi.org/10.1117/12.701352

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