本文選題：超分辨率重建 + 超松弛迭代��； 參考：《中南林業(yè)科技大學(xué)》2014年碩士論文

【摘要】：圖像超分辨率重建是指利用同一場景的不同觀測角度、不同觀測時(shí)間或不同傳感器獲取的低分辨率圖像序列重建出一幅或多幅高空間分辨率圖像的技術(shù)。本論文對(duì)單幅圖像的超分辨率重建算法和遙感圖像的分類進(jìn)行了研究。 在單幅圖像超分辨率重建的研究過程中,提出了K均值結(jié)合局部線性嵌入的重建方法。由于圖像分塊后,很多圖像塊是類似的,對(duì)分塊圖像先進(jìn)行聚類,分成不同的類,重構(gòu)時(shí)根據(jù)相似性分別從不同類中抽取一個(gè)或幾個(gè)圖像塊,然后利用局部線性嵌入對(duì)分類后的圖像塊進(jìn)行重構(gòu),可提高重構(gòu)速度及效果。分別對(duì)普通數(shù)字圖像和遙感圖像運(yùn)用插值法、局部線性嵌入算法,以及K均值結(jié)合局部線性嵌入算法進(jìn)行多次實(shí)驗(yàn),證明K均值結(jié)合局部線性嵌入重建方法重建結(jié)果較理想。在遙感圖像的分類研究中,提出基于超松弛迭代的模糊K均值算法。在模糊K均值算法中引入超松弛迭代算法,在不犧牲分類精度的情況下,很大程度上提高了收斂速度。該算法適合于對(duì)大幅面遙感影像的分類。
[Abstract]:Image super-resolution reconstruction is a technique to reconstruct one or more high-spatial resolution images by using low-resolution image sequences obtained from different observation angles, different observation times or different sensors of the same scene. In this paper, the super-resolution reconstruction algorithm of single image and the classification of remote sensing image are studied. In the process of super-resolution reconstruction of single image, a reconstruction method based on K-means and local linear embedding is proposed. Because many image blocks are similar after the image is divided into blocks, the block images are first clustered into different classes, and one or more blocks are extracted from different classes according to the similarity of reconstruction. Then local linear embedding is used to reconstruct the classified image blocks, which can improve the reconstruction speed and effect. The interpolation method, local linear embedding algorithm and K-means combined with local linear embedding algorithm are used to reconstruct ordinary digital images and remote sensing images respectively. It is proved that the reconstruction results of K-means combined with local linear embedding are satisfactory. In the research of remote sensing image classification, a fuzzy K-means algorithm based on overrelaxation iteration is proposed. The overrelaxation iterative algorithm is introduced into the fuzzy K-means algorithm, which improves the convergence speed to a great extent without sacrificing the classification accuracy. This algorithm is suitable for classification of large format remote sensing images.
【學(xué)位授予單位】：中南林業(yè)科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP751

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本文編號(hào)：2008990