發(fā)布時間：2019-06-22 14:44

【摘要】：最近這些年來,隨著遙感技術(shù)的發(fā)展,合成孔徑雷達因其成像不受光照的影響,越來越受到人們的關(guān)注,特別是在變化檢測領(lǐng)域。變化檢測是指讓計算機檢測出同一個地方不同時間的兩幅圖像之間的差異。本文對合成孔徑雷達圖像變化檢測問題進行了研究,提出了基于多目標(biāo)聚類與非局部均值的合成孔徑雷達圖像變化檢測的方法,所取得的主要研究成果有以下兩個方面:1.提出了一種基于多目標(biāo)聚類的差異圖分析方法。眾所周知,圖像中同時存在圖像細(xì)節(jié)和圖像噪聲,所以在變化檢測任務(wù)中權(quán)衡細(xì)節(jié)的保留和噪聲的不敏感扮演了一個關(guān)鍵的角色。本文定義了兩個目標(biāo)函數(shù),一個目標(biāo)函數(shù)表示保持圖像細(xì)節(jié),另一個目標(biāo)函數(shù)表示濾除圖像噪聲。這樣就把變化檢測問題轉(zhuǎn)變?yōu)槎嗄繕?biāo)優(yōu)化的問題,然后再采用多目標(biāo)進化算法對目標(biāo)函數(shù)進行優(yōu)化。作為結(jié)果,我們可以獲得一組有著不同程度的最優(yōu)解,用戶可以選擇針對特定問題的合適的解。2.提出了一種基于非局部均值的多目標(biāo)聚類的變化檢測方法。在圖像去噪中,相較于局部濾波器,非局部濾波器表現(xiàn)出更好的性能。本文使用非局部均值對差異圖去噪表示濾出噪聲的目標(biāo)函數(shù)中的圖像。非局部均值中塊與塊之間的相似度度量是一個關(guān)鍵的問題。為了更適應(yīng)合成孔徑雷達圖像,比值相似度度量被應(yīng)用于非局部均值算法中。
[Abstract]:In recent years, with the development of remote sensing technology, synthetic aperture radar (SAR) has attracted more and more attention because its imaging is not affected by light, especially in the field of change detection. Change detection refers to the computer to detect the difference between two images at different times in the same place. In this paper, the problem of SAR image change detection is studied, and a method of SAR image change detection based on multi-target clustering and non-local mean is proposed. The main research results are as follows: 1. A difference graph analysis method based on multi-objective clustering is proposed. As we all know, there are both image details and image noise in the image, so it plays a key role in weighing the retention of details and the insensitivity of noise in the task of change detection. In this paper, two objective functions are defined, one to maintain image details and the other to filter out image noise. In this way, the change detection problem is transformed into the multi-objective optimization problem, and then the multi-objective evolutionary algorithm is used to optimize the objective function. As a result, we can obtain a set of optimal solutions with different degrees, and the user can choose the appropriate solution for a particular problem. 2. A change detection method based on non-local mean value for multi-objective clustering is proposed. Compared with the local filter, the nonlocal filter shows better performance in image denoising. In this paper, the nonlocal mean is used to Denoise the difference graph to represent the image in the objective function of filtering noise. The measure of similarity between blocks in nonlocal mean is a key problem. In order to be more suitable for synthetic aperture radar (SAR) images, the ratio similarity measure is applied to the nonlocal mean algorithm.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN957.52

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