许丽娜, 肖奇, 何鲁晓. 考虑人类视觉特征的融合图像评价方法[J]. 武汉大学学报 ( 信息科学版), 2019, 44(4): 546-554. DOI: 10.13203/j.whugis20170168
引用本文: 许丽娜, 肖奇, 何鲁晓. 考虑人类视觉特征的融合图像评价方法[J]. 武汉大学学报 ( 信息科学版), 2019, 44(4): 546-554. DOI: 10.13203/j.whugis20170168
XU Lina, XIAO Qi, HE Luxiao. Fused Image Quality Assessment Based on Human Visual Characteristics[J]. Geomatics and Information Science of Wuhan University, 2019, 44(4): 546-554. DOI: 10.13203/j.whugis20170168
Citation: XU Lina, XIAO Qi, HE Luxiao. Fused Image Quality Assessment Based on Human Visual Characteristics[J]. Geomatics and Information Science of Wuhan University, 2019, 44(4): 546-554. DOI: 10.13203/j.whugis20170168

考虑人类视觉特征的融合图像评价方法

Fused Image Quality Assessment Based on Human Visual Characteristics

  • 摘要: 图像质量评价是遥感图像融合必不可少的环节,对融合图像的客观评价具有较好的研究价值,好的客观评价指标应尽量与主观评价一致。针对全色图像和多光谱图像的融合质量评价,在考虑人类视觉系统的多通道分解和对比度敏感特性的基础上,首先修改颜色失真和结构相似度来分别评价光谱信息和空间信息,然后综合两者作为融合图像的整体评价。以SPOT5图像和高分二号卫星图像为原始数据,对7种融合图像的质量进行了评价。实验表明,对于高分辨率的遥感图像,这种引入了人类视觉特征的融合评价方法与主观评价有很好的一致性。

     

    Abstract: Image quality assessment plays an important role in remote sensing image fusion. Research on objective evaluation methods is of great value in this field. Because the fused images will be observed by human finally, the best objective evaluation index of image quality should be consistent with the subjective evaluation. After the human visual characteristics are introduced into, image quality evaluation method can get better result. Therefore, based on the multi channels decomposition and contrast sensitivity characteristics of human visual system, this paper proposes a new method to evaluate the fusion quality of panchromatic image and multispectral image. Firstly, the color distortion and structural similarity are modified to evaluate the spectral information and spatial information respectively. Secondly, they are integrated as the overall evaluation of fused image. According to the experiment evaluating quality of different fused images by SPOT image data and GF-2 image data, it proves that the proposed method is in good agreement with the subjective evaluation when the remote sensing image is high resolution data.

     

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