【摘要】：圖像拼接與融合技術(shù)是圖像處理和計(jì)算機(jī)視覺領(lǐng)域中的熱門研究點(diǎn),近年來已經(jīng)被普遍地應(yīng)用于國防安全、機(jī)器人視覺、視頻監(jiān)控、全景圖像生成、醫(yī)學(xué)圖像處理、遙感、海底勘探、視頻壓縮與檢索、3D虛擬場(chǎng)景構(gòu)建等多個(gè)重要領(lǐng)域。其中圖像拼接的配準(zhǔn)率和拼接耗時(shí)以及圖像融合的質(zhì)量都是評(píng)價(jià)一個(gè)拼接方法好壞的指標(biāo)�；谔卣鞯膱D像拼接與融合方法因其配準(zhǔn)的質(zhì)量高并且不易受到尺度變化等因素的影響,受到廣大研究人員的推崇。本文在現(xiàn)有的基于特征的圖像配準(zhǔn)與拼接技術(shù)的基礎(chǔ)上,對(duì)圖像配準(zhǔn)和拼接融合的每一個(gè)步驟進(jìn)行了細(xì)化和改進(jìn),最終得到了良好的配準(zhǔn)與拼接結(jié)果。主要的工作如下:(1)分析比較了各種鏡頭畸變矯正算法的優(yōu)缺點(diǎn),根據(jù)實(shí)際需求采用張正友標(biāo)定法或基于Ilya Krylov模型對(duì)攝像機(jī)參數(shù)進(jìn)行了標(biāo)定和矯正。(2)研究了各種圖像增強(qiáng)的預(yù)處理方法,并提出了一種基于圖像金字塔的增強(qiáng)算法,使得圖像的配準(zhǔn)率得到提升,在光照不佳的條件下配準(zhǔn)率平均提高了14.3%。(3)研究了基于SIFT算法的圖像配準(zhǔn),并改進(jìn)了SIFT特征的描述符,使得圖像配準(zhǔn)的平均速度提高了2倍。(4)分析比較了各種圖像融合方法,在原有的加權(quán)平均法上進(jìn)行改進(jìn),使得融合結(jié)果的視覺效果有所改善。實(shí)驗(yàn)結(jié)果表明,文中提出的方法可有效用于各種領(lǐng)域的圖像拼接和視頻拼接。
[Abstract]:Image mosaic and fusion technology is a hot research point in the field of image processing and computer vision. In recent years, it has been widely used in national defense security, robot vision, video surveillance, panoramic image generation, medical image processing, remote sensing. Underwater exploration, video compression and retrieval, 3D virtual scene construction and other important areas. Among them, the registration rate, the time consuming and the quality of image fusion are all indicators to evaluate the quality of a stitching method. The feature-based image stitching and fusion method is highly praised by researchers because of its high registration quality and is not easy to be affected by the change of scale and other factors. In this paper, based on the existing feature-based image registration and stitching techniques, each step of image registration and stitching fusion is refined and improved, and good registration and stitching results are obtained. The main work is as follows: (1) the advantages and disadvantages of various lens distortion correction algorithms are analyzed and compared. According to the actual demand, the camera parameters are calibrated and corrected by using Zhang Zhengyou calibration method or Ilya Krylov model. (2) various image enhancement preprocessing methods are studied, and an image pyramid enhancement algorithm is proposed. The image registration rate is improved, and the average registration rate increases by 14.3% under the condition of poor illumination. (3) the image registration based on SIFT algorithm is studied, and the descriptor of SIFT feature is improved. The average speed of image registration is increased by 2 times. (4) the image fusion methods are analyzed and compared, and the original weighted average method is improved to improve the visual effect of the fusion results. Experimental results show that the proposed method can be effectively used in image mosaic and video mosaic in various fields.
【學(xué)位授予單位】：南京郵電大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 盧官明;陳浩;肖魯寧;蘇昊;鐘銳;;全景視圖泊車輔助系統(tǒng)中的多視點(diǎn)視頻拼接[J];南京郵電大學(xué)學(xué)報(bào)(自然科學(xué)版);2016年03期

2 徐燕麗;;一種魚眼鏡頭畸變圖像實(shí)時(shí)校正算法[J];信息通信;2016年06期

3 劉向南;馬純永;陳璐;陳戈;;基于三維場(chǎng)景出圖的拼接制作2.5維地圖算法[J];計(jì)算機(jī)應(yīng)用;2015年S1期

4 魏利勝;周圣文;張平改;孫駟洲;;基于雙經(jīng)度模型的魚眼圖像畸變矯正方法[J];儀器儀表學(xué)報(bào);2015年02期

5 陳曉;唐詩華;;基于Matlab的圖像融合方法及性能評(píng)價(jià)[J];地理空間信息;2014年06期

6 肖進(jìn)勝;饒?zhí)煊?賈茜;宋金鐘;易本順;;基于圖切割的拉普拉斯金字塔圖像融合算法[J];光電子.激光;2014年07期

7 姜柏軍;鐘明霞;;改進(jìn)的直方圖均衡化算法在圖像增強(qiáng)中的應(yīng)用[J];激光與紅外;2014年06期

8 戴霞;李輝;楊紅雨;張軍;;基于虛擬圖像金字塔序列融合的快速圖像增強(qiáng)算法[J];計(jì)算機(jī)學(xué)報(bào);2014年03期

9 趙娟;孫澎濤;吳粉俠;馮延琴;;基于像素級(jí)的圖像融合[J];長(zhǎng)春工程學(xué)院學(xué)報(bào)(自然科學(xué)版);2011年02期

10 張恒,雷志輝,丁曉華;一種改進(jìn)的中值濾波算法[J];中國圖象圖形學(xué)報(bào);2004年04期

相關(guān)碩士學(xué)位論文 前3條

1 桂輝;安防監(jiān)控中多相機(jī)圖像拼接相關(guān)問題的研究[D];浙江工業(yè)大學(xué);2015年

2 楊瑞陽;基于SURF算法的醫(yī)學(xué)顯微圖像拼接研究[D];蘭州大學(xué);2014年

3 趙彬;基于壓縮域的視頻配準(zhǔn)[D];山東大學(xué);2008年

，

本文編號(hào)：2392161