本文關(guān)鍵詞： 紅外焦平面陣列 非均勻性校正 FPGA 鬼影 盲元處理 圖像增強(qiáng)　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】：近些年,紅外熱成像技術(shù)發(fā)展速度迅猛,紅外焦平面陣列作為現(xiàn)今主流紅外成像系統(tǒng)的核心器件,其品質(zhì)的優(yōu)劣直接影響紅外圖像成像質(zhì)量。因生產(chǎn)原料、加工工藝等問題紅外焦平面陣列存在著固有的非均勻性,需通過信號處理算法來解決。國內(nèi)外對焦平面非均勻性校正算法做了大量的研究工作,基于場景的非均勻性校正算法因其自身優(yōu)勢已然成為近年來的研究熱點(diǎn)。當(dāng)前基于場景的校正算法硬件實(shí)現(xiàn)主要面臨兩個(gè)難題:算法復(fù)雜性大,硬件實(shí)現(xiàn)受制約;易產(chǎn)生鬼影。本文主要針對以上兩點(diǎn)對基于場景的非均勻性校正算法進(jìn)行了研究,并實(shí)現(xiàn)了一種基于FPGA硬件平臺的紅外焦平面非均勻性校正系統(tǒng)。本論文設(shè)計(jì)了基于場景的紅外焦平面非均勻性校正算法的紅外成像硬件系統(tǒng),包括主處理芯片F(xiàn)PGA的選型、紅外焦平面陣列的硬件和軟件驅(qū)動(dòng)、AD和DA轉(zhuǎn)換模塊的設(shè)計(jì)。研究并實(shí)現(xiàn)了紅外成像系統(tǒng)必備的盲元處理和圖像增強(qiáng)模塊,盲元處理模塊采用雙參考輻射源檢測算法和鄰域替代算法,去除了大部分的盲元點(diǎn)噪聲,有效提高圖像成像質(zhì)量。圖像增強(qiáng)模塊選用平臺直方圖均衡化算法,大幅度提高圖像對比度,增強(qiáng)圖像可視性。分析了基于場景的經(jīng)典神經(jīng)網(wǎng)絡(luò)算法及不足,提出改進(jìn)型基于場景的非均勻性校正算法。并從圖像清晰度、非均勻性以及鬼影的抑制等多個(gè)角度,對比分析了經(jīng)典神經(jīng)網(wǎng)絡(luò)校正算法和本文改進(jìn)型校正算法的優(yōu)劣。在FPGA平臺上實(shí)現(xiàn)了改進(jìn)型基于場景的非均勻性校正算法移植,校正算法模塊包括采樣矩陣窗口模塊、校正參數(shù)實(shí)時(shí)讀寫模塊和校正算法模塊等部分。經(jīng)測試,該算法在文中搭建的紅外焦平面陣列成像系統(tǒng)的硬件平臺上實(shí)現(xiàn)了對實(shí)時(shí)紅外視頻的校正,能夠快速去除紅外圖像中的非均勻性噪聲,大幅改善紅外圖像成像效果,同時(shí)有效抑制鬼影的產(chǎn)生。
[Abstract]:In recent years, infrared thermal imaging technology is developing rapidly. Infrared focal plane array (IRFPA), as the core device of mainstream infrared imaging system, its quality directly affects the imaging quality of infrared image. There is inherent inhomogeneity in infrared focal plane array (IRFPA), which needs to be solved by signal processing algorithm. A lot of research work has been done on focal plane nonuniformity correction algorithm at home and abroad. The scene based nonuniformity correction algorithm has become a research hotspot in recent years because of its own advantages. At present, the hardware implementation of scene based correction algorithm mainly faces two problems: the complexity of the algorithm. Hardware implementation is restricted; It is easy to produce ghost image. In this paper, the scene based nonuniformity correction algorithm is mainly studied for the above two points. An infrared focal plane nonuniformity correction system based on FPGA hardware platform is implemented. This paper designs an infrared imaging hardware system based on scene based infrared focal plane nonuniformity correction algorithm. Including the main processing chip FPGA selection, infrared focal plane array hardware and software driver. The design of AD and DA conversion module. The blind element processing and image enhancement module of infrared imaging system are studied and implemented. The blind element processing module adopts dual-reference emitter detection algorithm and neighborhood substitution algorithm. Most of the blind point noise is removed and the image quality is improved effectively. The image enhancement module uses the platform histogram equalization algorithm to greatly improve the image contrast. Enhance the visibility of images. Analyze the classical neural network algorithm based on scene and its shortcomings, and propose an improved non-uniformity correction algorithm based on scene. Inhomogeneity and the suppression of ghosts and other angles. The advantages and disadvantages of the classical neural network correction algorithm and the improved correction algorithm in this paper are compared and analyzed. The improved scene based nonuniformity correction algorithm is transplanted on the FPGA platform. The correction algorithm module includes sampling matrix window module, correction parameter real-time reading and writing module, correction algorithm module and so on. The algorithm realizes the correction of real-time infrared video on the hardware platform of the infrared focal plane array imaging system in this paper, and it can quickly remove the non-uniform noise in the infrared image. Greatly improve the imaging effect of infrared images, and effectively suppress the generation of ghost images.
【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】：TP391.41

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