本文選題：相機標定 + 成像模型��； 參考：《哈爾濱工業(yè)大學》2017年碩士論文

【摘要】：隨著人類經(jīng)濟社會發(fā)展,石油、天然氣等資源的消耗與日俱增,陸地上這些資源正被開發(fā)殆盡。而占地球表面積三分之二的海洋中仍然有大量資源尚未被開發(fā)。由于深海環(huán)境對人類相當危險,因此對海洋的探索主要依靠水下機器人。利用視覺信息對周圍環(huán)境進行三維重建,對水下機器人的導航及探索活動具有重要應用價值,也是目前計算機視覺領(lǐng)域的重要研究方向。但由于水下環(huán)境較為復雜,水下照片質(zhì)量下降,并且會發(fā)生畸變,使得傳統(tǒng)空氣中相機標定及三維重建算法不能直接應用于水下。本文針對課題內(nèi)容及算法要求,對空氣中三維重建算法進行了深入研究并改進,以適應水下重建的需要。采用多分辨率立體匹配結(jié)合多種約束條件,得到視差圖。并且針對目前常用方法中存在的模型階梯陰影誤差問題,提出了一種新的視差圖優(yōu)化方法,利用各向異性濾波處理視差圖,使算法的精度及魯棒性得到了提升,同時運行時間也有所減少,提高了算法效率。針對水下成像模型與空氣中模型的區(qū)別,對水下相機進行標定并且對存在的像素偏移誤差進行補償。為了研究水下成像過程,本文對理想情況下水下成像過程進行建模,同時改進一種基于平面標定板的水下相機標定方法,將折射參數(shù)加入到標定模型中,完成水下相機標定。根據(jù)實際實驗條件與理想條件不同,建立非理想條件下水下圖象復原模型,引入像素偏移誤差參數(shù),設(shè)計算法對其進行補償,并進行實驗驗證補償效果。補償后的水下圖像即可復原為空氣中圖像,并且應用空氣中的雙目重建算法,得到水下物體的三維模型。本文設(shè)計了多組實驗,分別對多個水下物體進行建模,并且把水下重建結(jié)果與空氣中的結(jié)果進行對比。相對于空氣中的重建模型,本課題所提出的算法,有重建精度高、運行效率高、模型完整度好的優(yōu)點,可以應用在實際水下研究工作中。
[Abstract]:With the development of human economy and society, the consumption of oil, natural gas and other resources is increasing day by day.The oceans, which account for 2/3 of the earth's surface area, still have vast untapped resources.Because the deep sea environment is very dangerous to human beings, the exploration of the ocean mainly depends on underwater vehicles.Using visual information to reconstruct the surrounding environment has important application value for underwater vehicle navigation and exploration activities. It is also an important research direction in the field of computer vision.However, due to the complexity of underwater environment, the quality of underwater photos is decreased and distortion occurs, the traditional camera calibration and 3D reconstruction algorithms in the air can not be directly applied to underwater.In order to meet the need of underwater reconstruction, the 3D reconstruction algorithm in air is studied and improved in this paper.The parallax map is obtained by multi-resolution stereo matching combined with many constraints.In order to solve the problem of model step shadow error, a new parallax map optimization method is proposed, which can improve the accuracy and robustness of the algorithm by using anisotropic filter to process the parallax map.At the same time, the running time is also reduced, and the efficiency of the algorithm is improved.Aiming at the difference between underwater imaging model and airborne model, the underwater camera is calibrated and the pixel offset error is compensated.In order to study the underwater imaging process, the underwater imaging process is modeled in this paper, and an underwater camera calibration method based on the plane calibration plate is improved. The refraction parameters are added to the calibration model to complete the underwater camera calibration.According to the difference between the actual experimental conditions and the ideal conditions, the underwater image restoration model under the non-ideal condition is established. The pixel offset error parameter is introduced, the algorithm is designed to compensate it, and the compensation effect is verified by experiments.The compensated underwater image can be restored to the image in the air, and the 3D model of underwater object can be obtained by using the binocular reconstruction algorithm in the air.In this paper, several experiments are designed to model several underwater objects, and the results of underwater reconstruction are compared with those in air.Compared with the reconstruction model in air, the algorithm proposed in this paper has the advantages of high reconstruction accuracy, high running efficiency and good model integrity, so it can be used in practical underwater research.
【學位授予單位】：哈爾濱工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41

【參考文獻】

相關(guān)碩士學位論文 前4條

1 湯興粲;水下攝像機標定與測量算法研究[D];哈爾濱工業(yè)大學;2015年

2 李洪生;水下攝像機標定技術(shù)的研究[D];哈爾濱工業(yè)大學;2013年

3 王玲玲;基于雙目立體視覺的水下三維重建[D];浙江大學;2011年

4 吳云峰;水下機器人雙目立體視覺技術(shù)研究[D];哈爾濱工程大學;2006年

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本文編號：1745220