Foveated Compressed Sensing

Author

Ciocoiu, Iulian B.

Author_Institution

Fac. of Electron., Telecommun., & Inf. Technol., Gheorghe Asachi Tech. Univ., Iasi, Romania

fYear

2011

Firstpage

29

Lastpage

32

Abstract

Combining the principles behind Compressed Sensing theory with the possibility of implementing variable spatial resolution by means of an operator inspired by the human visual system may yield significant compression performances on both 1D and 2D signals. The solution provides spatially variable quality of the reconstructed information, enabling better approximation of specific regions of interest. Two distinct algorithms are compared in terms of reconstruction error and compression ratio on a set of ECG records and natural images.

Keywords

data compression; discrete wavelet transforms; image coding; image reconstruction; 1D signals; 2D signals; ECG records; compression ratio; foveated compressed sensing; human visual system; natural images; reconstruction error; Compressed sensing; Discrete wavelet transforms; Electrocardiography; Image coding; Image reconstruction; Matching pursuit algorithms; Signal resolution; compressed sensing; foveation; mask; wavelets;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuit Theory and Design (ECCTD), 2011 20th European Conference on

Conference_Location

Linkoping

Print_ISBN

978-1-4577-0617-2

Electronic_ISBN

978-1-4577-0616-5

Type

conf

DOI

10.1109/ECCTD.2011.6043336

Filename

6043336