發(fā)布時(shí)間：2018-04-11 01:09

  本文選題：紅外成像技術(shù) + 非均勻性校正�。� 參考：《南京理工大學(xué)》2017年碩士論文

【摘要】：近年來(lái),紅外成像技術(shù)不斷進(jìn)步,核心探測(cè)器不斷更新?lián)Q代,探測(cè)系統(tǒng)日益完善,尤其是反應(yīng)靈敏、集成度高、耗能小的紅外焦平面陣列的出現(xiàn),使得紅外成像技術(shù)在國(guó)家安防、環(huán)境監(jiān)測(cè)、國(guó)民經(jīng)濟(jì)發(fā)展等各大領(lǐng)域發(fā)揮著不可替代的作用。然而紅外圖像上的條紋、畸變,使得探測(cè)器的溫度靈敏度降低,探測(cè)距離縮短,嚴(yán)重影響了圖像的質(zhì)量,我們稱這些固定的噪聲為紅外圖像的非均勻性[Non-Uniformity,NU]。本論文以得到高分辨率紅外圖像為目標(biāo),首先對(duì)紅外成像技術(shù)、紅外探測(cè)器的發(fā)展及應(yīng)用進(jìn)行了闡述,緊接著對(duì)非均勻性在圖像上的存在形式、產(chǎn)生原因和學(xué)術(shù)界普遍認(rèn)同的定義進(jìn)行了說(shuō)明,指出非均勻性校正過(guò)程的機(jī)理。最后論文研究了定標(biāo)類算法與兩類基于場(chǎng)景的典型算法。一是統(tǒng)計(jì)類,典型算法有:時(shí)域高通濾波法、神經(jīng)網(wǎng)絡(luò)法、統(tǒng)計(jì)恒定法。另外是配準(zhǔn)類,典型算法有:運(yùn)動(dòng)補(bǔ)償、代數(shù)法和幀間配準(zhǔn)。通過(guò)對(duì)比說(shuō)明了各自的優(yōu)缺點(diǎn)。為了克服傳統(tǒng)的定標(biāo)類算法需要黑體參考源和嚴(yán)格的線性要求等的不足,本論文提出基于焦平面均值響應(yīng)的非均勻性校正算法。通過(guò)實(shí)驗(yàn)與對(duì)異常響應(yīng)像元的校正,驗(yàn)證了新算法有著更好的線性性能,并且對(duì)二階函數(shù)圖像的校正效果明顯優(yōu)于傳統(tǒng)定標(biāo)法中的二階擬合,非均勻性校正能力很強(qiáng);為了克服傳統(tǒng)的配準(zhǔn)類算法不易配準(zhǔn),計(jì)算量大,硬件難以實(shí)現(xiàn)等的不足,本論文提出基于遞歸的矩陣校正法。并且通過(guò)實(shí)驗(yàn)評(píng)估,驗(yàn)證了新算法計(jì)算量較小,對(duì)存儲(chǔ)空間的需求低,可以自適應(yīng)調(diào)整參數(shù),收斂性與穩(wěn)定性都很好,校正后的圖像可視性高的優(yōu)勢(shì)。
[Abstract]:In recent years, the infrared imaging technology has been improved, the core detectors have been updated and the detection system has become more and more perfect, especially the infrared focal plane arrays, which are sensitive in response, high in integration and low in energy consumption.Infrared imaging technology plays an irreplaceable role in national security, environmental monitoring, national economic development and other fields.However, the temperature sensitivity and detection range of the detector are reduced because of the fringe and distortion on the infrared image, which seriously affects the image quality. We call these fixed noises Non-UniformityNU in infrared image.This paper aims at obtaining high resolution infrared image. Firstly, the infrared imaging technology, the development and application of infrared detector are described, and then the existence of non-uniformity in the image is discussed.The causes and the generally agreed definitions are explained, and the mechanism of the nonuniformity correction process is pointed out.Finally, the scaling class algorithm and two typical scene-based algorithms are studied.One is statistical, typical algorithms are: time domain high pass filter, neural network, statistical constant method.There are also registration classes, such as motion compensation, algebraic method and frame registration.The merits and demerits of each are explained by comparison.In order to overcome the shortcomings of traditional calibration algorithms, such as blackbody reference sources and strict linear requirements, a nonuniformity correction algorithm based on focal plane mean response is proposed in this paper.Through experiments and correction of abnormal response pixels, it is proved that the new algorithm has better linear performance, and the correction effect of the second-order function image is obviously better than the second-order fitting in the traditional calibration method, and the ability of non-uniformity correction is very strong.In order to overcome the disadvantages of traditional registration algorithms, such as difficult registration, large computation and hard hardware implementation, this paper proposes a recursive matrix correction method.Through the experimental evaluation, it is proved that the new algorithm has the advantages of low computational complexity, low demand for storage space, adaptive adjustment of parameters, good convergence and stability, and high visibility of the corrected image.
【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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本文編號(hào)：1733748