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Noise estimation for color visualization of multispectral images

机译:多光谱图像颜色可视化的噪声估计

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We study a technique for improving visualization quality of noisy multispectral images. Contrast form visualization approach is considered, which guarantees a non-zero contrast in the output image when there is a difference between the spectra of the object and the background in the input image. The improvement is based on channel weighting according to estimation of the noise level. We show this approach to reduce noise in color visualization of real multispectral images. The low-noise visualizations are demonstrated to be more comprehensive to a human on examples from a publicly available dataset of Earth surface images. Noise variance estimation needed for weighting uses the method proposed earlier by the authors. The validation dataset consists of publicly available images of Earth surface.
机译:我们研究了提高嘈杂多光谱图像的可视化质量的技术。考虑对比度形式可视化方法,其在输出图像中保证在输入图像中的对象的光谱和背景之间存在差异时,保证了输出图像中的非零对比度。改进基于噪声水平的估计基于频道加权。我们展示了这种方法,以降低真实多光谱图像的颜色可视化噪声。低噪声可视化被证明在来自地面图像的公共数据集中的示例中更全面地对人类更全面。加权所需的噪声方差估计使用作者提前提出的方法。验证数据集由地球表面的公开可用图像组成。

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