摘要
为了弥补金字塔变换算法分解时数据冗余较大、融合结果不理想的缺点,提出基于金字塔变换算法优化的遥感图像融合新算法。该算法运用金字塔分解构建金字塔序列,并根据先验知识赋予相应的权重系数,通过反复迭代重建遥感图像,再利用班德文克隆选择算法优化选择,在迭代可承受的范围内,自适应地修改选择权重系数,寻求和估计合适的融合参数来优化融合效果,从而避免金字塔变换算法的经验选择。为了突出本文算法的优点,实验运用金字塔变换法、遗传算法优化金字塔变换法和粒子群算法优化金字塔变换法进行比较,从视觉效果和数理统计两个方面分析评价融合质量。实验结果表明,本文算法更符合人类的视觉感知,有利于图像的分析和信息的提取。
To make up the shortcomings that data redundancy is large and the fusion result is not ideal when pyramid transform algorithm decomposes, a new algorithm of remote sensing image fusion optimized by pyramid transform algorithm is proposed. The proposed algorithm uses pyramid decomposition to build pyramid sequence. According to the relevant weight coefficient given by prior knowledge, the remote sensing image is reconstructed by iterating. Then through optimization selection of Baldwinian clonal selection algorithm, within the acceptable scope of iteration, the weight coefficient is adaptively modified and chose, and the suitable fusion parameter is sought and estimated to optimize fusion effects so as to avoid empirical selection of pyramid transform algorithm. In order to highlight the algorithmic merits, experiment applies pyramid transform optimization, pyramid transform optimization via genetic algorithm, and pyramid transform optimization via particle swarm optimization algorithm to make a comparison. Fusion quality is analyzed and evaluated from the two aspects of visual effect and mathematical statistics. Experimental result indicates that this arithmetic fusion result by the proposed method is consistent with human visual perception, and conducive to image analysis and information extraction.
出处
《激光与光电子学进展》
CSCD
北大核心
2017年第1期270-277,共8页
Laser & Optoelectronics Progress
基金
国家自然科学基金(41661088)
贵州省科技攻关项目(黔科合GY字[2015]3001)
贵州省重大应用基础研究项目(黔科合JZ字[2014]200201)
关键词
遥感
金字塔变换
班德文克隆选择算法
算法优化
图像融合
remote sensing
pyramid transform
Baldwinian clonal selection algorithm
algorithm optimization
image fusion
