The article invoves in the preprocessing of hyperion data, and denoising of hyperspectral reference spectral library, which is generated from the spectro-radiometer. The atmospheric correction module like Fast Line-of-sight of Atmospheric Analysis of Spectral Hypercubes provided the smooth absolute spectral profile. In connection to that, the Hybrid Adaptive Bilateral Filter (HABF) is proposed for denoising of field based spectral library, and laboratory based spectral library. To implement the proposed algorithm, spectral library of mangrove has been exploited, which is collected from Muthupet mangrove forest, and spectra of particular species is generated from Field-spectro-radiometer with wavelength ranges from 350 nm to 2500 nm, and 10 nm band width. This spectral library has been used as an input signal since it contains noise across wavelength ranges from 350 – 450 nm, 1000 – 1200 nm, and 2000 – 2500 nm due to atmospheric conditions. These noises can be removed effectively by the proposed wavelet based HABF techniques and conventional method of denoising. The performance of each method was compared with performance evaluation parameter such as PSNR and MSE

中文翻译：

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使用高光谱卫星数据（Hyperion）校准模块对反射率进行高效的预处理和检索，并使用基于小波的自适应双边滤波（HABF）对高光谱参考光谱进行去噪-以泰米尔纳德邦Muthupet泻湖的红树林为例

本文介绍了高离子数据的预处理和从光谱辐射仪生成的高光谱参考光谱库的去噪。大气校正模块（例如光谱超立方体的大气分析快速视线）提供了平滑的绝对光谱轮廓。与此相关，提出了混合自适应双向滤波器（HABF），用于对基于现场的光谱库和基于实验室的光谱库进行降噪。为了实现该算法，本文利用了从Muthupet红树林中采集到的红树林光谱库，并通过波长范围为350 nm至2500 nm，带宽为10 nm的光谱仪测量了特定物种的光谱。 。该光谱库已被用作输入信号，因为它由于大气条件而包含了从350 – 450 nm，1000 – 1200 nm和2000 – 2500 nm波长范围内的噪声。可以通过提出的基于小波的HABF技术和常规的降噪方法有效地消除这些噪声。将每种方法的性能与性能评估参数（例如PSNR和MSE）进行比较