测绘地理信息2024,Vol.49Issue(3) :59-62.DOI:10.14188/j.2095-6045.2022197

适用于遥感影像可视化的非线性拉伸降位算法

A Nonlinear Stretching and Gray-Scale Conversion Algorithm for Remote Sensing Image Visualization

李相坤 左斌 高放 李一挥 赵园薇 翟雨微 张鹏
测绘地理信息2024,Vol.49Issue(3) :59-62.DOI:10.14188/j.2095-6045.2022197

适用于遥感影像可视化的非线性拉伸降位算法

A Nonlinear Stretching and Gray-Scale Conversion Algorithm for Remote Sensing Image Visualization

李相坤 1左斌 2高放 3李一挥 1赵园薇 1翟雨微 1张鹏1
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作者信息

  • 1. 长光卫星技术股份有限公司,吉林长春,130102
  • 2. 北京市遥感信息研究所,北京,100192
  • 3. 长光卫星技术股份有限公司,吉林长春,130102;吉林大学计算机科学与技术学院,吉林长春,130012
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摘要

由于遥感影像文件的灰度级通常为16位,计算机显示遥感影像时需对其降位为8位影像并进行增强,以得到良好的视觉效果.传统的影像降位方法受极值影响易导致局部区域曝光过度、对比度或亮度过低等情况.为此,本文提出了一种适用于遥感影像可视化的非线性拉伸降位算法.首先利用多尺度的方法统计影像各波段的累计直方图;然后根据统计的平均值计算非线性拉伸参数;最后对影像进行降位.从整体上改善遥感影像显示的对比度与亮度,使降位后的影像具有良好的全局视觉效果,利于后续解译判读.利用吉林一号系列卫星影像进行实验,结果表明,该方法的视觉效果与定量评价指标均优于传统方法.

Abstract

The remote sensing images are generally 16-bit,which requires image enhancement and the conversion to 8-bit for good visual effect. Traditional image stretching and en-hancing methods tend to cause overexposure or low contrast and brightness in certain parts of the image. To this end,this paper proposes a nonlinear stretching and enhancing algorithm for remote sensing image visualization. Firstly,cumulative histograms for each band of the image are counted through a multi-scale way. Then the nonlinear stretching parameters are computed based on average values of the histograms. Finally,the presented algorithm performs stretching on the image and converts it . This method can improve the contrast and bright-ness of the remote sensing image from the holistic perspective and obtain good visual overall effect,which is beneficial for later interpretation. Experiments on Jilin-1 satellites images are performed and the results show that the proposed algo-rithm surpasses other methods in terms of visual effect and quantitative evaluation.

关键词

遥感影像可视化/影像降位/非线性拉伸/多尺度

Key words

remote sensing image visualization/gray-scale conversion/nonlinear stretching/multi-scale

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基金项目

长春市科技发展计划(21ZGG14)

国家重点研发计划(2020YFA0714104)

出版年

2024
测绘地理信息
武汉大学

测绘地理信息

CSTPCD
影响因子:0.563
ISSN:1007-3817
参考文献量9
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