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A Pan-Sharpening Method Based on Evolutionary Optimization and IHS Transformation

机译:基于进化优化和IHS变换的泛推方法

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摘要

In many remote sensing applications, users usually prefer a multispectral image with both high spectral and high spatial information. This high quality image could be obtained by pan-sharpening techniques which fuse a high resolution panchromatic (PAN) image and a low resolution multispectral (MS) image. In this paper, we propose a new technique to do so based on the adaptive intensity-hue-saturation (IHS) transformation model and evolutionary optimization. The basic idea is to reconstruct the target image through a parameterized adaptive IHS transformation. An optimization objective is thus introduced by considering the relations between the fused image and the original PAN and MS images. The control parameters are optimized by an evolutionary algorithm. Experimental results show that our new approach is practical and performs much better than some state-of-the-art techniques according to the performance metrics.
机译:在许多遥感应用中,用户通常更喜欢同时具有高光谱和高空间信息的多光谱图像。可以通过将高分辨率全色(PAN)图像和低分辨率多光谱(MS)图像融合在一起的泛锐化技术来获得此高质量图像。在本文中,我们提出了一种基于自适应强度-色相-饱和度(IHS)转换模型和进化优化的新技术。基本思想是通过参数化的自适应IHS转换来重建目标图像。因此,通过考虑融合图像与原始PAN和MS图像之间的关系来引入优化目标。通过进化算法优化控制参数。实验结果表明,根据性能指标,我们的新方法是实用的,并且其性能比某些最新技术要好得多。

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  • 来源
    《Mathematical Problems in Engineering》 |2017年第9期|8269078.1-8269078.8|共8页
  • 作者

    Chen Yingxia; Zhang Guixu;

  • 作者单位

    East China Normal Univ, Dept Comp Sci, 500 Dongchuan Rd, Shanghai 200241, Peoples R China;

    East China Normal Univ, Dept Comp Sci, 500 Dongchuan Rd, Shanghai 200241, Peoples R China;

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  • 正文语种 eng
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