本文關(guān)鍵詞： 圖像融合 遙感 方向性信息測(cè)度 IHS變換 YIQ變換 PCA變換 金字塔結(jié)構(gòu) 多分辨率分析 小波變換 區(qū)域特征 區(qū)域邊界強(qiáng)度 自適應(yīng)融合 容錯(cuò) 評(píng)價(jià)準(zhǔn)則　出處：《西北工業(yè)大學(xué)》2004年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】： 作為圖像融合領(lǐng)域的一個(gè)重要分支，，多源遙感圖像融合研究的是如何綜合利用不同航空遙感傳感器所獲取的圖像信息，來(lái)產(chǎn)生新的數(shù)據(jù)，以獲取對(duì)同一事物或目標(biāo)的更為全面、客觀及本質(zhì)上的認(rèn)識(shí)。在高度信息化的今天，遙感圖像融合已經(jīng)成為圖像處理和圖像信息理解領(lǐng)域中不可或缺的技術(shù)，并在很多軍事和民用方面有著重要應(yīng)用。 本文應(yīng)用圖像處理和現(xiàn)代信號(hào)處理技術(shù)中的多種手段，研究了不同層次上多源遙感圖像的融合方法。通過(guò)對(duì)不同航空遙感傳感器所獲取的圖像數(shù)據(jù)進(jìn)行融合，從而提高圖像的分辨率、圖像分析結(jié)果的準(zhǔn)確性和置信度，并最終提高對(duì)特定航空目標(biāo)進(jìn)行自動(dòng)檢測(cè)、識(shí)別的有效性。 本文的主要研究?jī)?nèi)容和工作可總結(jié)如下： 1．介紹了圖像融合的基本概念和原理，進(jìn)而系統(tǒng)分析了多種傳統(tǒng)的圖像融合方法，并通過(guò)實(shí)驗(yàn)對(duì)其特點(diǎn)和性能做了細(xì)致的對(duì)比，總結(jié)出了一系列有用的結(jié)論； 2．在特征級(jí)融合方面，提出了一種基于方向性信息測(cè)度和IHS變換的圖像融合算法。實(shí)驗(yàn)表明該算法產(chǎn)生的光譜畸變很小，并且有良好的抗噪性，非常適合處理多光譜圖像的融合； 3．在多分辨率圖像融合算法中，提出了基于小波變換的自適應(yīng)圖像融合算法(DWT_EI)。與傳統(tǒng)算法比較，該算法在提高圖像信息含量方面表現(xiàn)得最好。同時(shí)它的運(yùn)算也相對(duì)簡(jiǎn)單，并且和原始圖像的相關(guān)性也很好(即光譜畸變小)，是一種非常好的融合算法； 4．歸納并給出了基于信息量的評(píng)價(jià)、基于統(tǒng)計(jì)特性的評(píng)價(jià)、基于相關(guān)性的評(píng)價(jià)和基于梯度值的評(píng)價(jià)四類(lèi)十項(xiàng)融合結(jié)果評(píng)價(jià)指標(biāo)。這些指標(biāo)被用于對(duì)融合實(shí)驗(yàn)結(jié)果的實(shí)際評(píng)價(jià)中，使得對(duì)算法的評(píng)價(jià)從定性到定量?jī)煞矫娑加辛艘欢ǖ脑u(píng)價(jià)標(biāo)準(zhǔn)； 5．不僅從實(shí)際應(yīng)用角度驗(yàn)證了圖像融合技術(shù)能夠增加圖像信息含量、提高圖像分割、分類(lèi)和識(shí)別的有效性這一結(jié)論，而且從理論角度出發(fā)，進(jìn)一步探討了圖像融合中的識(shí)別與決策問(wèn)題。同時(shí)對(duì)圖像融合中的可靠性與容錯(cuò)性問(wèn)題也進(jìn)行了簡(jiǎn)要分析； 6．除多源遙感影像作為實(shí)驗(yàn)數(shù)據(jù)以外，本文還選用了一組多聚焦可見(jiàn)光圖片來(lái)驗(yàn)證和評(píng)價(jià)各種算法的融合效果，從而使得各種算法的有效性及優(yōu)劣性更加直觀。
[Abstract]:As an important branch in the field of image fusion, multi-source remote sensing image fusion studies how to synthetically utilize the image information obtained by different aerial remote sensing sensors to generate new data. In order to obtain a more comprehensive, objective and essential understanding of the same thing or object, remote sensing image fusion has become an indispensable technology in the field of image processing and image information understanding. And in many military and civilian areas have important applications. In this paper, image processing and modern signal processing technology are used in a variety of means. The fusion methods of multi-source remote sensing images at different levels are studied. The image resolution is improved by fusion of image data obtained by different aerial remote sensing sensors. The accuracy and confidence of image analysis results, and finally improve the effectiveness of automatic detection and recognition of specific aeronautical targets. The main contents and work of this paper can be summarized as follows: 1. The basic concepts and principles of image fusion are introduced, and then various traditional image fusion methods are systematically analyzed, and the characteristics and performance of these methods are compared in detail through experiments. A series of useful conclusions are summarized. 2. In the aspect of feature level fusion, an image fusion algorithm based on directional information measure and IHS transform is proposed. The experimental results show that the spectral distortion is very small and the algorithm has good noise resistance. It is very suitable for multispectral image fusion. 3. In the multi-resolution image fusion algorithm, an adaptive image fusion algorithm based on wavelet transform is proposed, which is compared with the traditional algorithm. The algorithm has the best performance in improving the information content of the image. At the same time, its operation is relatively simple, and the correlation with the original image is very good (that is, the spectral distortion is small, it is a very good fusion algorithm; 4. The evaluation based on information quantity and statistical characteristic is summarized and given. Evaluation based on correlation and evaluation based on gradient value. These indicators are used in the actual evaluation of fusion experiment results. Make the evaluation of the algorithm from qualitative and quantitative aspects have a certain evaluation criteria; 5. The conclusion that image fusion technology can increase the content of image information, improve the validity of image segmentation, classification and recognition is verified from the practical application. The problem of recognition and decision in image fusion is discussed, and the problems of reliability and fault tolerance in image fusion are also analyzed briefly. 6. In addition to multi-source remote sensing images as experimental data, this paper also selected a group of multi-focused visible light images to verify and evaluate the fusion effect of various algorithms. In order to make the effectiveness of various algorithms and advantages and disadvantages more intuitive.
【學(xué)位授予單位】：西北工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2004
【分類(lèi)號(hào)】：TP751

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本文編號(hào)：1453555