本文選題：全景圖像 + 全景設(shè)備區(qū)提取�。� 參考：《哈爾濱工程大學(xué)》2016年碩士論文

【摘要】：我國(guó)具有綿長(zhǎng)的海岸線和廣闊的海洋領(lǐng)土,海洋維權(quán)執(zhí)法及海上搜救任務(wù)繁重,大力開(kāi)發(fā)先進(jìn)的海域監(jiān)控設(shè)備,研究海上目標(biāo)檢測(cè)方法具有重要的意義。在海域監(jiān)控領(lǐng)域采用全景視覺(jué)系統(tǒng),可以滿足海洋環(huán)境下大視場(chǎng)、全范圍、遠(yuǎn)距離監(jiān)控的需求,有效減少監(jiān)控設(shè)備數(shù)量、降低硬件成本,但該系統(tǒng)目前缺乏成熟的目標(biāo)檢測(cè)技術(shù)支持。由遠(yuǎn)及近駛來(lái)的遠(yuǎn)景目標(biāo)會(huì)最先出現(xiàn)在海天線上,在海天線區(qū)域檢測(cè)小目標(biāo)可為拍攝取證等工作提供更多的反應(yīng)時(shí)間,因此本論文開(kāi)展基于全景海天線提取的小目標(biāo)檢測(cè)算法研究。折反射全景視覺(jué)系統(tǒng)成像原理的特殊性,不僅使得常規(guī)視覺(jué)中的直線海天線在全景圖像中呈橢圓形,而且使得全景圖像中包含有大量全景設(shè)備區(qū)成像。鑒于全景海域圖像的特殊性和背景的復(fù)雜性,本文的基本研究思路為:首先在全景圖像中對(duì)海天線提取和目標(biāo)檢測(cè)有不良影響的全景設(shè)備區(qū)干擾進(jìn)行提取和剔除,然后進(jìn)行全景海天線提取,最后在海天線區(qū)域檢測(cè)小目標(biāo)。因此論文研究的三大核心內(nèi)容為:全景設(shè)備區(qū)提取、全景海天線提取以及海天線區(qū)域的小目標(biāo)檢測(cè)。首先,進(jìn)行了全景設(shè)備區(qū)提取方法研究。根據(jù)全景設(shè)備區(qū)屬于人造物體,其紋理特征與海面、天空等自然景物有明顯區(qū)別的特點(diǎn),設(shè)計(jì)了基于分形維數(shù)的全景設(shè)備區(qū)提取算法;根據(jù)全景圖像中的全景設(shè)備區(qū)干擾比較明顯,更易引起視覺(jué)注意的特點(diǎn),設(shè)計(jì)了基于視覺(jué)顯著圖的全景設(shè)備區(qū)提取算法;并通過(guò)實(shí)驗(yàn)驗(yàn)證了上述算法的有效性。其次,進(jìn)行了基于全景視覺(jué)的海天線提取算法研究。在抑制了全景設(shè)備區(qū)干擾的基礎(chǔ)上,針對(duì)全景海天線呈近似圓形的特點(diǎn),設(shè)計(jì)了基于改進(jìn)梯度Hough圓變換的海天線提取算法;針對(duì)全景海天線具有明顯邊緣輪廓特征的特點(diǎn),提出了基于改進(jìn)主動(dòng)輪廓模型的海天線提取算法;針對(duì)全景海天線在全景圖像中的梯度能量相對(duì)較大的特點(diǎn),提出了一種基于改進(jìn)Seam Carving的海天線提取算法;最后通過(guò)實(shí)驗(yàn)驗(yàn)證了這三種算法的有效性,并與現(xiàn)有文獻(xiàn)中的算法進(jìn)行了實(shí)驗(yàn)對(duì)比分析。最后,進(jìn)行海天線區(qū)域的小目標(biāo)檢測(cè)算法研究。在海天線提取的基礎(chǔ)上,將小目標(biāo)視為圖像信號(hào)的奇異點(diǎn),設(shè)計(jì)了一種基于提升小波互能量的海天線區(qū)域小目標(biāo)檢測(cè)算法;利用暗通道理論對(duì)目標(biāo)的放大作用,提出了一種基于暗通道先驗(yàn)理論的海天線區(qū)域小目標(biāo)檢測(cè)算法。最后通過(guò)大量實(shí)驗(yàn)驗(yàn)證了算法的有效性,并與現(xiàn)有文獻(xiàn)中的算法進(jìn)行了實(shí)驗(yàn)對(duì)比與統(tǒng)計(jì)分析,驗(yàn)證了算法的優(yōu)越性。
[Abstract]:China has a long coastline and vast maritime territory, the task of maritime rights enforcement and maritime search and rescue is heavy. It is of great significance to develop advanced marine monitoring equipment and to study the detection methods of marine targets. The use of panoramic vision system in the area of sea area monitoring can meet the needs of large field of view, wide range and long distance monitoring in marine environment, effectively reduce the number of monitoring equipment and reduce the cost of hardware. But this system lacks the mature target detection technology support at present. Distant and near-term targets will first appear on the sea and sky lines. Detection of small targets in the sea antenna area can provide more reaction time for such work as taking evidence. In this paper, the small target detection algorithm based on panoramic sea antenna extraction is studied. Because of the particularity of the imaging principle of the reflected panoramic vision system, the linear sea antenna in the conventional vision is not only elliptical in the panoramic image, but also contains a large number of panoramic imaging equipment in the panoramic image. In view of the particularity of panoramic sea area image and the complexity of background, the basic research ideas of this paper are as follows: firstly, in panoramic image, the interference of panoramic equipment which has adverse effects on antenna extraction and target detection is extracted and eliminated. Then the panoramic sea antenna is extracted and the small target is detected in the sea antenna area. Therefore, the three core contents of this paper are: panoramic equipment region extraction, panoramic sea antenna extraction and small target detection in sea antenna region. Firstly, the extraction method of panoramic equipment area is studied. According to the fact that panoramic equipment area belongs to artificial object and its texture features are obviously different from those of sea surface and sky, an algorithm of extracting panoramic equipment area based on fractal dimension is designed. According to the obvious interference of panoramic equipment area in panoramic image, which is more easy to attract visual attention, a panoramic equipment area extraction algorithm based on visual salient image is designed, and the validity of the algorithm is verified by experiments. Secondly, the algorithm of sea antenna extraction based on panoramic vision is studied. On the basis of suppressing the interference of panoramic equipment, aiming at the characteristic that the panoramic sea antenna is approximately circular, the algorithm of extracting sea antenna based on improved gradient Hough circle transform is designed, and aiming at the characteristic of obvious edge contour of panoramic sea antenna, A sea antenna extraction algorithm based on improved active contour model is proposed, and a sea antenna extraction algorithm based on improved seam carrying is proposed, which is based on the relatively large gradient energy of panoramic sea antenna in panoramic images. Finally, the validity of the three algorithms is verified by experiments, and compared with the existing algorithms. Finally, the small target detection algorithm in the sea antenna region is studied. On the basis of the sea antenna extraction, the small target is regarded as the singularity of the image signal, and a small target detection algorithm based on lifting wavelet mutual energy is designed, which uses dark channel theory to amplify the target. A small target detection algorithm based on dark channel priori theory is proposed in this paper. Finally, the validity of the algorithm is verified by a large number of experiments, and the superiority of the algorithm is verified by comparison and statistical analysis with the existing algorithms in the literature.
【學(xué)位授予單位】：哈爾濱工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類(lèi)號(hào)】：U675.79;TP391.41

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