Ultra-spectrum image real-time compression system based on noise decomposing compression algorithm

Abstract

The invention relates to a hyperspectrum image real-time compression system based on the noise decomposition and compression algorithm, which is composed of the host computer, the high-speed image processor and the image collection apparatus. The image collection apparatus is connected to the slave processor via the CAB bus port and to the host computer via the PCI bus. The host computer is bi-directionally connected to the slave processor via the PCI bus. In addition, it is connected to the image display and the image data compression result memory respectively. Its characteristic lies in the following. First, the bi-directionally connected image noise decomposition and compression block and the host connector is equipped on the slave processor to receive the command data from the host computer and to transmit the image real time compression result data to the host computer. Second, the host computer control block, the slave processor interface, the display block and the storage block are equipped on the host computer. The control block receives the original image data and the user command to generate the system data resource, and transmits the command to the slave processor and receives the image real time compression result data via the slave processor. The host computer control block transmits the original image data to the display block and the image real time compression result to the storage block to generate the compression file.

Description

technical field [0001] The present invention relates to a hyperspectral image real-time compression system, in particular to an image compression system based on a noise decomposition compression algorithm, which reduces the influence of noise introduced by the compression algorithm on image information by estimating the signal-to-noise ratio of the real-time hyperspectral image To the minimum, it realizes the high-fidelity compression of the hyperspectral image, and also guarantees the image compression rate of the image compression system. Background technique [0002] There have been many reports on the research results of hyperspectral image compression, but most of them stay in the stage of theoretical research and software processing, and there are not many real-time hardware applications. The reasons are as follows: firstly, the data volume of hyperspectral images is huge, which requires high processing power of hardware, and it was difficult to complete it in real ti...

AI Technical Summary

Problems solved by technology

[0004] However, the actual remote sensing images inevitably have the interference of random noise. The shortcoming of analyzing these imaging spectral image compression systems is that they do not consider the noise characteristics of the image. When the image is compressed by a certain multiple, the image edge The original noise of the transition zone is amplified by the system, and spreads and pollutes the high-bit data of the image, resulting in the loss of image information

In short, when using these compression systems to compress images, the image information cannot be reasonably preserved

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