针对高光谱遥感影像数据量大、数据冗余度高的特点，引入拉普拉斯特征映射方法对高光谱遥感数据进行非线性降维。

Feature extraction is an indispensable preprocessing step for large and high redundancy data of hyperspectral remote sensing image.

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该方法简单、实用，提高了数据的鲁棒性和准确性，同时降低了整个网络内的数据冗余度，节省了大量的网络能量和网络带宽。

The method is a simple, practical algorithm, and greatly reduces the redundancy of data within the network, saving a lot of storage resources and network bandwidth.

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数据压缩旨在利用图像的冗余度来减少表示图像所需的比特数，从而节省图像存贮容量，提高传输效率。

Data compression improves the efficiency of data transmission by utilizing the correlation of images and reducing the redundancy of bits representing them to save the memory capacity.

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