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.
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.
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.
它是去除视频数据中时间冗余度的有效方法，它的性能好坏直接影响编码的效率和图像的质量。
It is an effective method to remove the video data time redundancy, which directly affects the performance of coding efficiency and image quality.
图像分形后，对相邻帧间对应的数据求差并进行压缩编码，减少时间与空间冗余度。
After image was decomposed, the corresponding data were compressed and coded. It could reduce the time and space redundancy.
通过合理分配数据层次，建立冗余度小、推导方便的数据存储结构，同时给出了实例。
Then a data storage structure, having low redundancy rate, being well assigned in data depth and easy in searching, was created. Also an example was given for illustration.
通过合理分配数据层次，建立冗余度小、推导方便的数据存储结构，同时给出了实例。
Then a data storage structure, having low redundancy rate, being well assigned in data depth and easy in searching, was created. Also an example was given for illustration.
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