@inproceedings{c7760a60216843ca9409d1b8ee3bba55,
title = "Efficient super-resolution driven by saliency selectivity",
abstract = "This paper presents a low-complexity saliency detector targeted towards efficient selective Super-Resolution (SR). As a result, an improved efficient ATtentive-SELective Perceptual (AT-SELP) framework is presented. The proposed AT-SELP scheme results in a reduced computational complexity for iterative SR algorithms without any perceptible loss in the desired enhanced image/video quality. A perceptually significant set of active pixels is selected for processing by the SR algorithm based on a local contrast sensitivity threshold model and the proposed low complexity saliency detector. Simulation results show that the proposed AT-SELP scheme results in a 15-40% reduction in computational complexity over an efficient Selective Perceptual (SELP) SR scheme without degradation in the visual quality.",
keywords = "Contrast sensitivity, MAP-estimation, Masking, Super-resolution, Visual attention",
author = "Sadaka, {Nabil G.} and Lina Karam",
year = "2011",
doi = "10.1109/ICIP.2011.6115645",
language = "English (US)",
isbn = "9781457713033",
series = "Proceedings - International Conference on Image Processing, ICIP",
pages = "1197--1200",
booktitle = "ICIP 2011",
note = "2011 18th IEEE International Conference on Image Processing, ICIP 2011 ; Conference date: 11-09-2011 Through 14-09-2011",
}