Compressed sensing super resolution of color images. Saafin, W., Vega, M., Molina, R., & Katsaggelos, A. K. In 2016 24th European Signal Processing Conference (EUSIPCO), pages 1563-1567, Aug, 2016.
Paper doi abstract bibtex In this work we estimate Super Resolution (SR) images from a sequence of true color Compressed Sensing (CS) observations. The red, green, blue (RGB) channels are sensed separately using a measurement matrix that can be synthesized practically. The joint optimization problem to estimate the registration parameters, and the High Resolution (HR) image is transformed into a sequence of unconstrained optimization sub-problems using the Alternate Direction Method of Multipliers (ADMM). A new, simple, and accurate, image registration procedure is proposed. The performed experiments show that the proposed method compares favorably to existing color CS reconstruction methods at unity zooming factor (P), obtaining very good performance varying P and the compression factor simultaneously. The algorithm is tested on real and synthetic images.
@InProceedings{7760511,
author = {W. Saafin and M. Vega and R. Molina and A. K. Katsaggelos},
booktitle = {2016 24th European Signal Processing Conference (EUSIPCO)},
title = {Compressed sensing super resolution of color images},
year = {2016},
pages = {1563-1567},
abstract = {In this work we estimate Super Resolution (SR) images from a sequence of true color Compressed Sensing (CS) observations. The red, green, blue (RGB) channels are sensed separately using a measurement matrix that can be synthesized practically. The joint optimization problem to estimate the registration parameters, and the High Resolution (HR) image is transformed into a sequence of unconstrained optimization sub-problems using the Alternate Direction Method of Multipliers (ADMM). A new, simple, and accurate, image registration procedure is proposed. The performed experiments show that the proposed method compares favorably to existing color CS reconstruction methods at unity zooming factor (P), obtaining very good performance varying P and the compression factor simultaneously. The algorithm is tested on real and synthetic images.},
keywords = {compressed sensing;data compression;image coding;image colour analysis;image registration;image resolution;matrix algebra;optimisation;color image compressed sensing super resolution;SR image;CS observation;red,green,blue channel;RGB channel;measurement matrix;joint optimization problem;registration parameters, estimate;high resolution image;HR image;unconstrained optimization subproblem;alternate direction method of multiplier;ADMM;image registration procedure;unity zooming factor;compression factor;Image color analysis;Optimization;Image reconstruction;Europe;Compressed sensing;Image resolution;Color;Super resolution;compressed sensing;color images;image reconstruction;image enhancement},
doi = {10.1109/EUSIPCO.2016.7760511},
issn = {2076-1465},
month = {Aug},
url = {https://www.eurasip.org/proceedings/eusipco/eusipco2016/papers/1570252184.pdf},
}
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