Distributed perceptual compressed sensing framework for multiview images. Issue 10 (1st May 2016)

• Record Type: Journal Article
• Authors: Elsayed, S.; Elsabrouty, M.; Muta, O.; Furukawa, H.
• Is Part Of: Electronics letters. Volume 52:Issue 10(2016)
• Page Start: 821
• Page End: 823
• Publication Date: 2016-05-01
• Subjects: compressed sensing -- image reconstruction; distributed perceptual compressed sensing framework -- CS -- multiview image signals -- signal prediction -- disparity estimation -- compensation techniques -- reconstruction performance -- perceptual‐based CS framework; Electronics -- Periodicals; 621.381
• DOI: 10.1049/el.2016.0477
• Languages: English
• ISSNs: 0013-5194

Abstract

Abstract : A perceptual‐based compressed sensing (CS), which focuses the measurements and the recovery on the visually important low‐frequency coefficients, is applied for multi‐view image signals. High correlation among different views is exploited to generate signal prediction using disparity estimation and compensation techniques. A residual‐based recovery is utilised as a joint recovery for the non‐reference images to enhance the reconstruction performance. The proposed framework shows remarkable performance improvement over the conventional CS with joint recovery as well as the perceptual‐based CS with independent recovery.