發(fā)布時(shí)間：2018-11-15 12:24

【摘要】：在視頻圖像探測(cè)領(lǐng)域,普通CMOS相機(jī)體積小、質(zhì)量輕,適合白天工作;ICCD內(nèi)部存在微通道板結(jié)構(gòu),較適合在夜間工作;低照度CMOS能在晝夜工作且便于攜帶,在實(shí)際應(yīng)用中具有獨(dú)特的優(yōu)勢(shì)。本文針對(duì)CIS0431低照度CMOS相機(jī)與PIC0384型非制冷紅外焦平面研制了圖像融合系統(tǒng)電子組件部分,并對(duì)基于FPGA的低照度CMOS與非制冷紅外實(shí)時(shí)圖像融合算法進(jìn)行研究。本文首先在課題組已有的紅外圖像處理系統(tǒng)的基礎(chǔ)上,以FPGA作為為核心處理芯片,改進(jìn)并設(shè)計(jì)低照度CMOS與非制冷紅外圖像融合硬件平臺(tái),并對(duì)硬件系統(tǒng)進(jìn)行調(diào)試;其次,研究并實(shí)現(xiàn)低照度CMOS與非制冷紅外圖像預(yù)處理及雙源圖像配準(zhǔn),低照度CMOS圖像預(yù)處理主要是在10~(-3)lux照度下消除高斯噪聲,而紅外圖像預(yù)處理過(guò)程包括非均勻校正與灰度直方圖增強(qiáng)圖像對(duì)比度;再次,研究拉普拉斯金字塔圖像融合算法,并在系統(tǒng)中實(shí)現(xiàn)改進(jìn)的拉普拉斯金字塔分解圖像融合算法;最后,進(jìn)行成像實(shí)驗(yàn),對(duì)系統(tǒng)的成像效果進(jìn)行評(píng)估,在白天系統(tǒng)以低照度CMOS圖像為主,當(dāng)照度在10~(-3)lux至1lux時(shí)對(duì)低照度CMOS與紅外圖像進(jìn)行融合,當(dāng)照度低于10~(-3)lux時(shí)低照度CMOS相機(jī)已無(wú)法清晰成像,此時(shí)以非制冷紅外作為系統(tǒng)的圖像輸入源,同時(shí)對(duì)本文提出的算法與加權(quán)平均融合算法進(jìn)行比較并進(jìn)行客觀評(píng)價(jià),實(shí)驗(yàn)結(jié)果表明,本文設(shè)計(jì)的低照度CMOS與非制冷紅外圖像融合系統(tǒng)能對(duì)圖像進(jìn)行實(shí)時(shí)融合且效果比較理想。
[Abstract]:In the field of video image detection, the ordinary CMOS camera is small in size, light in mass, suitable for daytime operation, and has a microchannel board structure in ICCD, which is more suitable for working at night. Low illuminance CMOS can work day and night and is easy to carry, so it has unique advantages in practical application. In this paper, the electronic component of image fusion system is developed for CIS0431 low illuminance CMOS camera and PIC0384 uncooled infrared focal plane, and the algorithm of low illuminance CMOS and uncooled infrared real-time image fusion based on FPGA is studied. Firstly, on the basis of the infrared image processing system of our research group, the hardware platform of low illuminance CMOS and uncooled infrared image fusion is improved and designed with FPGA as the core processing chip, and the hardware system is debugged. Secondly, we study and realize low illuminance CMOS and uncooled infrared image preprocessing and dual source image registration. Low illuminance CMOS image preprocessing is mainly to eliminate Gao Si noise under 10 ~ (-3) lux illumination. The infrared image preprocessing process includes non-uniform correction and gray histogram enhancement image contrast; Thirdly, the image fusion algorithm of Laplacian pyramid is studied, and the improved image fusion algorithm of Laplacian pyramid decomposition is implemented in the system. Finally, the imaging experiment was carried out to evaluate the imaging effect of the system. In the daytime, the low illuminance CMOS image was the main one. When the illumination was from 10 ~ (-3) lux to 1lux, the low illuminance CMOS was fused with the infrared image. When the illumination is below 10 ~ (-3) lux, the low illuminance CMOS camera can no longer be clearly imaged, and the uncooled infrared is used as the input source of the system. At the same time, the algorithm proposed in this paper is compared with the weighted average fusion algorithm and evaluated objectively. The experimental results show that the low illuminance CMOS and uncooled infrared image fusion system designed in this paper can fuse the images in real time and the effect is satisfactory.
【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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