發(fā)布時間：2018-09-07 12:58

【摘要】：紅外成像無論在軍事領(lǐng)域還是民用領(lǐng)域都有著極為廣泛的應(yīng)用�，F(xiàn)有的紅外成像系統(tǒng)中非制冷紅外探測器由于其體積小,功耗低等優(yōu)勢占據(jù)著主要地位,但非制冷型的紅外探測器有非均勻性差,易受環(huán)境因素干擾等問題。傳統(tǒng)的紅外成像系統(tǒng)難以實現(xiàn)較為復(fù)雜的圖像處理算法,導(dǎo)致畫面質(zhì)量和應(yīng)用范圍不盡如人意,開發(fā)的難度也較大。本文提出了新的紅外成像系統(tǒng)架構(gòu),以此架構(gòu)為基礎(chǔ)可以方便快捷的搭建起紅外成像系統(tǒng),既加快了紅外系統(tǒng)開發(fā)的速度,又能在此基礎(chǔ)上實現(xiàn)更復(fù)雜的算法。本文第一章主要介紹了紅外成像技術(shù)發(fā)展概況和紅外成像系統(tǒng)的幾種不同架構(gòu)。第二章簡要說明了新架構(gòu)的三個重要組成部分:Qsys平臺,Avalon總線和Nios處理器。第三章詳細介紹了 Avalon-MM和Avalon-ST總線的規(guī)范和使用。在以上內(nèi)容的基礎(chǔ)上,第四章詳細介紹了如何在新架構(gòu)下實現(xiàn)紅外成像系統(tǒng)的各個算法模塊。除了通用的格式轉(zhuǎn)換和PAL顯示之外,本文還著重研究了提高紅外成像質(zhì)量的圖像處理算法,并提出了改進的直方圖算法和改進的圖像背景補償算法。對這些算法進行理論推導(dǎo)之后,實現(xiàn)了這些算法并以IP核的形式應(yīng)用到紅外成像系統(tǒng)新架構(gòu)中。第五章描述了在一個紅外系統(tǒng)硬件平臺上實現(xiàn)該架構(gòu),以較小的體積和功耗,實現(xiàn)了非常良好的成像質(zhì)量,并且整個項目的開發(fā)周期得以大大縮短。
[Abstract]:Infrared imaging has been widely used in both military and civil fields. The existing uncooled infrared detectors occupy the main position because of their small size and low power consumption. However, the uncooled infrared detectors have some problems such as poor heterogeneity and easy to be interfered by environmental factors. The traditional infrared imaging system is difficult to realize more complicated image processing algorithm, which leads to the unsatisfactory picture quality and application range, and it is also difficult to develop. In this paper, a new infrared imaging system architecture is proposed. Based on this architecture, the infrared imaging system can be constructed conveniently and quickly, which not only speeds up the development of infrared system, but also realizes more complex algorithms on this basis. The first chapter introduces the development of infrared imaging technology and several different structures of infrared imaging system. Chapter 2 briefly describes three important components of the new architecture: the Avalon bus and the Nios processor. The third chapter introduces the specification and use of Avalon-MM and Avalon-ST bus in detail. On the basis of the above, chapter 4 introduces in detail how to implement each algorithm module of infrared imaging system under the new framework. In addition to the general format conversion and PAL display, this paper also focuses on the image processing algorithm to improve the infrared imaging quality, and proposes an improved histogram algorithm and an improved image background compensation algorithm. After theoretical derivation of these algorithms, these algorithms are implemented and applied to the new architecture of infrared imaging system in the form of IP kernel. The fifth chapter describes the implementation of the architecture on an infrared system hardware platform, with a small volume and power consumption, achieved a very good imaging quality, and the entire project development cycle can be greatly shortened.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN216

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