The problem of resolution enhancement has been recently attracted the image processing community both for its theoretical and applications relevance. Achieving an higher and higher resolution capability is the objective of imaging sensor technology, which is often paid in terms of high equipment costs. On the other hand, the advances in signal processing theory and equipment make solutions for resolution enhancement based on post-processing of low-resolutions acquisitions appealing. Some type of biomedical imaging systems, such as computer tomography or magnetic resonance, are specific examples that can benefit from super-resolution of images. In this paper, we review some advanced techniques available for single image super-resolution and propose a variation of one method based on sparse representations. Then, we compare the performance of each method when they are applied to the quality enhancement of low-resolution biomedical images.

Comparison of super-resolution methods for quality enhancement of digital biomedical images / Alessandro Lapini;Fabrizio Argenti;Alessandro Piva;Luca Bencini. - STAMPA. - (2014), pp. 1-5. (Intervento presentato al convegno 2014 8th International Symposium on Medical Information and Communication Technology (ISMICT) tenutosi a Florence, Italy nel 2-4 April 2014) [10.1109/ISMICT.2014.6825243].

Comparison of super-resolution methods for quality enhancement of digital biomedical images

LAPINI, ALESSANDRO;ARGENTI, FABRIZIO;PIVA, ALESSANDRO;
2014

Abstract

The problem of resolution enhancement has been recently attracted the image processing community both for its theoretical and applications relevance. Achieving an higher and higher resolution capability is the objective of imaging sensor technology, which is often paid in terms of high equipment costs. On the other hand, the advances in signal processing theory and equipment make solutions for resolution enhancement based on post-processing of low-resolutions acquisitions appealing. Some type of biomedical imaging systems, such as computer tomography or magnetic resonance, are specific examples that can benefit from super-resolution of images. In this paper, we review some advanced techniques available for single image super-resolution and propose a variation of one method based on sparse representations. Then, we compare the performance of each method when they are applied to the quality enhancement of low-resolution biomedical images.
2014
Proceedings of 2014 8th International Symposium on Medical Information and Communication Technology (ISMICT)
2014 8th International Symposium on Medical Information and Communication Technology (ISMICT)
Florence, Italy
2-4 April 2014
Alessandro Lapini;Fabrizio Argenti;Alessandro Piva;Luca Bencini
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/893919
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