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A new hyperspectral image compression paradigm based on fusion

机译:基于融合的新高光谱图像压缩范例

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The on-board compression of remote sensed hyperspectral images is an important task nowadays. One of the main difficulties is that the compression of these images must be performed in the satellite which carries the hyperspectral sensor. Hence, this process must be performed by space qualified hardware, having area, power and speed limitations. Moreover, it is important to achieve high compression ratios without compromising the quality of the decompress image. In this manuscript we proposed a new methodology for compressing hyperspectral images based on hyperspectral image fusion concepts. The proposed compression process has two independent steps. The first one is to spatially degrade the remote sensed hyperspectral image to obtain a low resolution hyperspectral image. The second step is to spectrally degrade the remote sensed hyperspectral image to obtain a high resolution multispectral image. These two degraded images are then send to the earth surface, where they must be fused using a fusion algorithm for hyperspectral and multispectral image, in order to recover the remote sensed hyperspectral image. The main advantage of the proposed methodology for compressing remote sensed hyperspectral images is that the compression process, which must be performed on-board, becomes very simple, being the fusion process used to reconstruct image the more complex one. An extra advantage is that the compression ratio can be fixed in advanced. Many simulations have been performed using different fusion algorithms and different methodologies for degrading the hyperspectral image. The results obtained in the simulations performed corroborate the benefits of the proposed methodology.
机译:遥感过高光谱图像的车载压缩是现在的重要任务。主要困难之一是必须在承载高光谱传感器的卫星中进行这些图像的压缩。因此,必须通过空间合格的硬件,具有区域,功率和​​速度限制来执行该过程。此外,重要的是在不影响解压缩图像的质量的情况下实现高压缩比。在本手稿中,我们提出了一种基于高光谱图像融合概念的压缩高光谱图像的新方法。所提出的压缩过程有两个独立的步骤。第一个是在空间地降解远程感测的高光谱图像以获得低分辨率高光谱图像。第二步骤是光谱降解远程感测的高光谱图像以获得高分辨率的多光谱图像。然后将这两个降级的图像发送到地球表面,在那里必须使用用于高光谱和多光谱图像的融合算法来融合它们,以便恢复遥感过高光谱图像。用于压缩远程感测的高光谱图像的提出方法的主要优点是必须在板上执行的压缩过程变得非常简单,是用于重建图像的融合过程更复杂。额外的优点是压缩比可以在先进中固定。已经使用不同的融合算法和不同方法进行了许多模拟,用于降低高光谱图像。在模拟中获得的结果进行了证实了所提出的方法的益处。

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