發(fā)布時間：2019-01-03 16:35

【摘要】：高光譜遙感是近些年來遙感領(lǐng)域發(fā)展的一個重要方向，高光譜遙感是通過航空航天飛行器上攜帶的光譜成像儀對地面進(jìn)行拍攝，得到一片地面區(qū)域的數(shù)百個甚至數(shù)千個極其狹窄的波段影像。這樣，對于成像范圍內(nèi)的任何一個像元，就可以繪制出一條近乎連續(xù)的光譜曲線，這可以用來和已有的光譜曲線數(shù)據(jù)庫進(jìn)行比對，得到地物的類型或成分。 然而，由于光譜成像儀的空間分辨率有限，實際成像中，一個像元對應(yīng)地面一個區(qū)域，而這一個區(qū)域有可能是由多種物質(zhì)混合而成，因此不能對像元進(jìn)行直接分析，需要進(jìn)行解混。解混的目的就是計算出組成該混合像元中不同純物質(zhì)的組成比例。 要進(jìn)行解混，就首先要進(jìn)行純物質(zhì)的提取，在高光譜遙感中，純物質(zhì)也被叫做端元。端元在不同的遙感圖像中一般是不同的，因此有必要通過一種合理的方法將端元從給定的遙感圖像中準(zhǔn)確的提取出來。 本文分析了當(dāng)前主流的幾種端元提取算法，例如純像元指數(shù)算法，N-FINDR算法，單形體體積法等，并重點研究了純像元指數(shù)算法。純像元指數(shù)算法的運算時間復(fù)雜度很高，這大大限制了在航空航天領(lǐng)域需要實時處理的應(yīng)用。因此本文在對純像元指數(shù)算法的研究中，提出了矩陣乘法的一種優(yōu)化結(jié)構(gòu)，，經(jīng)過優(yōu)化后的結(jié)構(gòu)，具有了并行性，適合在硬件電路上進(jìn)行實現(xiàn)。 在硬件系統(tǒng)的實現(xiàn)上，本文采用了Xilinx公司的ZYNQ片上系統(tǒng)平臺，在單芯片上進(jìn)行軟硬件協(xié)同開發(fā)，將純像元指數(shù)算法的核心步驟放在了數(shù)字邏輯電路上進(jìn)行，大大提高了運行速度。在設(shè)計的過程中，對存儲器結(jié)構(gòu)進(jìn)行了深入的優(yōu)化，添加了流水處理機制，并使用高級語言綜合工具進(jìn)行設(shè)計，使得處理速度得到了明顯的提高。經(jīng)過實際測試，本文實現(xiàn)的硬件結(jié)構(gòu)的運算速度比PC機上的軟件提高了400倍以上。與國際上對該算法在硬件電路上實現(xiàn)的最新結(jié)果相比，本文的結(jié)果也具有非常顯著的優(yōu)勢。
[Abstract]:Hyperspectral remote sensing is an important direction in the field of remote sensing in recent years. Hundreds or even thousands of extremely narrow band images of a ground area are obtained. In this way, for any pixel in the imaging range, a nearly continuous spectral curve can be drawn, which can be used to compare with the existing spectral curve database to obtain the type or composition of the ground object. However, because the spatial resolution of the spectral imager is limited, in actual imaging, a pixel corresponds to a ground area, and this area may be composed of a mixture of a variety of substances, so it is not possible to directly analyze the pixel. It needs to be unmixed. The purpose of unmixing is to calculate the composition ratio of different pure matter in the mixed pixel. In order to demix, the extraction of pure substance is the first step. In hyperspectral remote sensing, pure substance is also called endelement. The endelements are usually different in different remote sensing images, so it is necessary to extract the endelements accurately from the given remote sensing images by a reasonable method. In this paper, we analyze several current algorithms for extracting endelements, such as pure pixel exponent algorithm, N-FINDR algorithm, volume method of single body and so on, and focus on pure pixel exponent algorithm. The computational complexity of pure pixel exponent algorithm is very high, which greatly limits the application of real-time processing in the field of aeronautics and astronautics. Therefore, in the study of pure pixel exponent algorithm, an optimized structure of matrix multiplication is proposed. The optimized structure has parallelism and is suitable to be implemented in hardware circuit. In the realization of the hardware system, this paper adopts the ZYNQ system platform of Xilinx Company, and develops the hardware and software on a single chip. The core steps of the pure pixel exponent algorithm are put on the digital logic circuit. The running speed is greatly improved. In the design process, the memory structure is optimized deeply, the pipeline processing mechanism is added, and the advanced language synthesis tool is used to design the memory structure. The processing speed is improved obviously. After practical test, the calculation speed of the hardware structure is more than 400 times faster than that of the software on PC computer. Compared with the latest results in hardware circuits, the results of this paper also have a very significant advantage.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP751

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 耿修瑞;趙永超;周冠華;;一種利用單形體體積自動提取高光譜圖像端元的算法[J];自然科學(xué)進(jìn)展;2006年09期

本文編號：2399625