發(fā)布時(shí)間：2018-03-14 15:21

  本文選題：紅外熱像儀　切入點(diǎn)：特征提取　出處：《南京理工大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：紅外圖像反映了物體之間的溫度差異分布,所以紅外監(jiān)測(cè)技術(shù)具有遠(yuǎn)距離不接觸和不受惡劣環(huán)境影響的特點(diǎn),在軍事目標(biāo)探測(cè)與預(yù)警、電力設(shè)備在線監(jiān)測(cè)和工業(yè)檢測(cè)等范圍都得到了較為廣泛的應(yīng)用。但紅外熱像儀大多數(shù)成像范圍窄且分辨率不高,一張圖像往往很難顯示較大目標(biāo)物體的全部樣貌,給后續(xù)的圖像分析和被測(cè)目標(biāo)的溫度趨勢(shì)判斷帶來(lái)了不便,而圖像拼接技術(shù)為其提供了一個(gè)較為合適的解決方案。論文首先對(duì)紅外熱像的拼接技術(shù)進(jìn)行了研究,著重研究了紅外熱像的特征點(diǎn)提取與圖像配準(zhǔn),在此基礎(chǔ)上提出了相應(yīng)的改進(jìn)算法。并設(shè)計(jì)了與之配套的紅外熱像采集與拼接系統(tǒng),通過(guò)實(shí)驗(yàn)驗(yàn)證了其實(shí)用性與可靠性。在圖像預(yù)處理的研究中,論文首先分析了紅外成像原理,對(duì)紅外圖像的去噪和增強(qiáng)技術(shù)進(jìn)行了研究,并在此基礎(chǔ)上對(duì)紅外圖像進(jìn)行仿真實(shí)驗(yàn)與結(jié)果分析。在圖像配準(zhǔn)的研究中,論文首先對(duì)三大配準(zhǔn)方式進(jìn)行了介紹與仿真說(shuō)明,研究確定了在論文中使用基于特征的圖像配準(zhǔn)方案;在特征點(diǎn)的提取中,對(duì)經(jīng)典的角點(diǎn)提取算法和局部不變特征提取算法進(jìn)行了深入的研究,進(jìn)行了編程實(shí)驗(yàn)仿真與結(jié)果分析,并提出了一種改進(jìn)的多尺度空間的特征點(diǎn)提取方式,通過(guò)編程實(shí)驗(yàn)驗(yàn)證了其可行性;在圖像的特征匹配中,對(duì)待匹配圖像之間的粗匹配和結(jié)合改進(jìn)的RANSAC算法的特征點(diǎn)的提純方法進(jìn)行研究,并用編程實(shí)驗(yàn)驗(yàn)證了其可行性。在圖像融合的研究中,論文對(duì)基本的融合方式進(jìn)行了介紹,來(lái)完成圖像拼接的最后一步,并進(jìn)行編程實(shí)驗(yàn)生成兩幅圖的拼接圖。在軟件系統(tǒng)的設(shè)計(jì)中,論文根據(jù)之前對(duì)算法的研究成果,設(shè)計(jì)了一套基于紅外熱像儀的熱像采集與拼接系統(tǒng)。該系統(tǒng)不僅能完成熱像儀的控制、實(shí)時(shí)視頻的點(diǎn)溫度檢測(cè)和熱像的采集,還能夠選擇相應(yīng)的算法對(duì)熱像儀采集的圖像進(jìn)行處理與拼接,給后續(xù)圖像的分析工作帶來(lái)了方便,具有一定的價(jià)值和意義。
[Abstract]:Infrared images reflect the distribution of temperature differences between objects, so infrared monitoring technology has the characteristics of remote non-contact and unaffected by adverse environment, in the detection and early warning of military targets, Power equipment on-line monitoring and industrial detection have been widely used. However, most infrared thermal imagers have narrow imaging range and low resolution, so it is difficult for an image to display the full appearance of a large target object. It brings inconvenience to the subsequent image analysis and the temperature trend judgment of the target under test, and the image stitching technology provides a more suitable solution for it. Firstly, the paper studies the technology of infrared thermal image stitching. In this paper, the feature point extraction and image registration of infrared thermal image are emphatically studied, and the corresponding improved algorithm is put forward, and a matching infrared thermal image acquisition and splicing system is designed. The practicability and reliability are verified by experiments. In the research of image preprocessing, firstly, the principle of infrared imaging is analyzed, and the denoising and enhancement techniques of infrared image are studied. On this basis, the infrared image simulation experiments and results analysis. In the image registration research, the paper first introduces the three major registration methods and simulation. In the feature point extraction, the classical corner extraction algorithm and the local invariant feature extraction algorithm are deeply studied, and the programming experiments and results analysis are carried out. An improved feature point extraction method in multi-scale space is proposed, and its feasibility is verified by programming experiments. The methods of coarse matching between matching images and feature points of improved RANSAC algorithm are studied, and the feasibility of this method is verified by programming experiments. In the research of image fusion, the basic fusion methods are introduced in this paper. In the software system design, according to the previous research results of the algorithm, A thermal image acquisition and splicing system based on infrared thermal imager is designed. The system can not only control the thermal imager, detect the point temperature of the real-time video, but also collect the thermal image. It can also select the corresponding algorithm to process and join the images collected by the thermal imager, which brings convenience to the analysis of the subsequent images, and has certain value and significance.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41

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