本文關(guān)鍵詞： 嵌入式 圖像配準(zhǔn) 圖像融合 FPGA DSP　出處：《中原工學(xué)院》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：當(dāng)代社會科技的迅猛發(fā)展迫切需要能夠?qū)崟r獲取圖像信息并進行綜合處理,來滿足現(xiàn)代人類高節(jié)奏的生活,嵌入式圖像處理系統(tǒng)應(yīng)運而生。圖像融合技術(shù)是將相關(guān)場景的多幅圖像合并成為一幅,彌補各傳感器成像不足之處獲得較大信息量。針對現(xiàn)有圖像融合算法僅僅將特征考慮在內(nèi)的現(xiàn)狀,本文提出了結(jié)合特征點相似性與空間結(jié)構(gòu)的優(yōu)化圖像融合算法,結(jié)合嵌入式發(fā)展情況,設(shè)計了基于現(xiàn)場可編程門陣列和數(shù)字信號處理器架構(gòu)的嵌入式圖像融合系統(tǒng),說明了系統(tǒng)硬件平臺設(shè)計和軟件算法實現(xiàn)過程。本文結(jié)合圖像配準(zhǔn)和圖像融合技術(shù)的發(fā)展和傳感器采集圖像的特點,對基于特征點的圖像融合算法進行深入研究,提出了以加速魯棒性特征(SURF)算法為理論依據(jù)的改進圖像融合算法�；谔卣鼽c的圖像融合算法首先獲取相關(guān)場景多幅圖像的SURF特征進行特征描述,提取出SURF特征描述子;其次利用SSD(Sum of Squared Differences)對提取的特征描述子進行特征匹配,并根據(jù)MSAC(M-estimator SAmple Consensus)去除匹配對中的“外點”求取轉(zhuǎn)換參數(shù);最后利用重疊區(qū)線性過渡用來進行圖像融合。而基于SURF特征點的改進圖像融合算法考慮了圖像的空間結(jié)構(gòu)特征,首先根據(jù)基于SURF特征點的圖像融合算法求取的轉(zhuǎn)換參數(shù),分析求解原數(shù)據(jù)空間結(jié)構(gòu),結(jié)合特征相似性與空間結(jié)構(gòu)求取復(fù)合特征;其次采用ICP(Iterative Closest Point)算法求取匹配矩陣;最后利用雙向匹配限制求取最終的匹配矩陣。仿真實驗表明,所提方法準(zhǔn)確度高,魯棒性強。針對圖像融合在嵌入式平臺的使用,考慮其硬件資源,搭建了以現(xiàn)場可編程門陣列和數(shù)字信號處理器為基礎(chǔ)的硬件平臺,設(shè)計了以前端視頻信號采集子系統(tǒng)、圖像融合子系統(tǒng)、圖像融合調(diào)試子系統(tǒng)為核心的嵌入式圖像處理平臺,對核心器件選型、PCB設(shè)計進行詳細描述,在嵌入式系統(tǒng)平臺上完成了圖像配準(zhǔn)和圖像融合。
[Abstract]:The rapid development of modern social science and technology urgently needs to be able to obtain real-time image information and comprehensive processing to meet the high pace of modern human life. The embedded image processing system emerges as the times require. Image fusion technology is to combine multiple images of related scenes into one image. Aiming at the fact that the existing image fusion algorithms only consider the features, this paper proposes an optimized image fusion algorithm which combines the similarity of feature points with the spatial structure. According to the development of embedded system, an embedded image fusion system based on field programmable gate array and digital signal processor is designed. The design of hardware platform and the realization of software algorithm are explained. Combining the development of image registration and image fusion technology and the characteristics of image acquisition by sensor, the image fusion algorithm based on feature points is studied deeply in this paper. An improved image fusion algorithm based on the accelerated robust feature surf algorithm is proposed. Firstly, the feature point based image fusion algorithm acquires the SURF features of multiple scene images for feature description and extracts the SURF feature descriptor. Secondly, the extracted feature descriptors are matched by SSD(Sum of Squared differences, and the "outer points" in the matching pairs are removed according to the MSAC(M-estimator SAmple Consensus. Finally, the linear transition of overlapping region is used for image fusion. The improved image fusion algorithm based on SURF feature points takes into account the spatial structure features of the image. Firstly, the conversion parameters are obtained according to the image fusion algorithm based on SURF feature points. The original data spatial structure is analyzed and solved, combining the feature similarity with the spatial structure to obtain the composite feature; secondly, the matching matrix is obtained by using ICP(Iterative Closest Point algorithm; finally, the final matching matrix is obtained by using the bidirectional matching restriction. The simulation results show that, The proposed method has high accuracy and robustness. Considering the hardware resources of image fusion in embedded platform, a hardware platform based on field programmable gate array and digital signal processor is built. The embedded image processing platform based on video signal acquisition subsystem, image fusion subsystem and image fusion debugging subsystem is designed. The PCB design of core device selection is described in detail. Image registration and image fusion are completed on the embedded system platform.
【學(xué)位授予單位】：中原工學(xué)院
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41

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