Compressed sensing of multiview images using disparity compensation

Compressed sensing is applied to multiview image sets and interimage disparity compensation is incorporated into image reconstruction in order to take advantage of the high degree of interimage correlation common to multiview scenarios. Instead of recovering images in the set independently from one another, two neighboring images are used to calculate a prediction of a target image, and the difference between the original measurements and the compressed-sensing projection of the prediction is then reconstructed as a residual and added back to the prediction in an iterated fashion. The proposed method shows large gains in performance over straightforward, independent compressed-sensing recovery. Additionally, projection and recovery are block-based to signicantly reduce computation time.

• Type: Journal
• Year: 2010
• Where: ICIP
• Authors: Maria Trocan, Thomas Maugey, Eric W. Tramel, James E. Fowler, Béatrice Pesquet-Popescu
• Keywords: Disparity Compensation, ICIP 2010, Image, Image Processing, Prediction