Transform domain adaptive compressive sensing of specific objects

Abhijit Mahalanobis

doi:10.1117/12.884486

3 June 2011 Transform domain adaptive compressive sensing of specific objects

Abhijit Mahalanobis

Proceedings Volume 8056, Visual Information Processing XX; 80560Q (2011) https://doi.org/10.1117/12.884486
Event: SPIE Defense, Security, and Sensing, 2011, Orlando, Florida, United States

Abstract

We have previously shown in reference [3] that images of particular objects of interest can be recovered from compressive measurements by minimizing a L2-norm criterion that incorporates prior knowledge of the signal such as its expected spectra. The basis in which the signal is reconstructed was also noted to be an important consideration in the formulation of the solution. In this paper, we further improve this technique by representing the image in a multi-scale domain so that select bands of the transform can be adapted to reference signals from other sources, while improving the overall quality of reconstruction of the full image. It is shown by means of an example that the adaptation not only reduces the overall mean square error of the reconstruction, but also helps to correctly resolve features in the high-resolution image that are not accurately reconstructed by the open-loop algorithm.

Citation Download Citation

Abhijit Mahalanobis "Transform domain adaptive compressive sensing of specific objects", Proc. SPIE 8056, Visual Information Processing XX, 80560Q (3 June 2011); https://doi.org/10.1117/12.884486

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