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The Application of Vector Quantization Algorithm in Hyperspectral Image Compression

机译:矢量量化算法在高光谱图像压缩中的应用

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With the development of Aerospace remote sensing technology, the hyperspectral remote sensing technology is widely applied in earth resources detection, environment investigation and military reconnaissance, etc. It is different from multispectral image, hyperspectral image spectrum period is as many as dozens to hundreds of band, with high resolution, large amount of data, corresponding to the data transmission problem, so the hyperspectral image compression is become necessary. In this paper the vector quantization algorithm is applied for hyperspectral image compression, first convert the three dimensional hyperspectral images into two dimensional pixel vectors, and then applied the vector quantization on the transformed pixel vectors. The experimental results show that the algorithm not only has better compression ratio, and can effectively save image spectrum section characteristics, which is a kind of efficient three-dimensional compression method.
机译:随着航空航天遥感技术的发展,高光谱遥感技术广泛应用于地球资源检测,环境调查和军事侦察等。它与多光谱图像不同,高光谱图像谱时期多达数百个频段,具有高分辨率,大量数据,对应于数据传输问题,因此高光谱图像压缩是必要的。在本文中,向上光谱图像压缩施加矢量量化算法,首先将三维高光谱图像转换为二维像素矢量,然后在变换的像素矢量上施加矢量量化。实验结果表明,该算法不仅具有更好的压缩比,并且可以有效地节省图像光谱部分特性,这是一种有效的三维压缩方法。

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