返回
Saliency-directed image interpolation using particle swarm optimization
DOI:10.1016/j.sigpro.2009.11.019.png)
摘要
En 中文
In this study, a saliency-directed image interpolation approach using visual attention model and particle swarm optimization (PSO) is proposed. First, a block-based saliency map of an image to be interpolated is generated by the proposed visual attention model in an effective manner. Then, based on the block-based saliency map, bilinear interpolation and PSO interpolation are employed for the pixels in non-saliency blocks and saliency blocks, respectively, to obtain the final interpolation results. Various interpolation filtering mask weights are determined by off-line PSO, which are applicable for horizontal, vertical, and diagonal image interpolation types of saliency pixels in saliency blocks with arbitrary magnification factors (MFs). Based on the experimental results obtained in this study, the interpolation results of the proposed approach are better than those of four comparison methods. (C) 2009 Elsevier B.V. All rights reserved.
Keyword:
Saliency-directed image interpolation
Visual attention model
Particle swarm optimization (PSO)
Bilinear interpolation
Block-based saliency map
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
10.0K
被引数:
1.7W
机构
引用论文
Frequency response masking filter design using an oscillation search genetic algorithm
SIGNAL PROCESSING
IF3.6
Comparaison de la qualité de fromages à pâte pressée cuite fabriqués à partir de lait cru ou microfiltré
Le Lait
IF0

