本文關(guān)鍵詞：SAR圖像非局部均值去噪和分割應(yīng)用研究　出處：《西安電子科技大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 極化SAR 貝葉斯 非局部均值 降噪 機場分割

【摘要】：合成孔徑雷達(dá)(Synthetic Aperture Radar,SAR)相比于光學(xué)傳感器具有多波段、視角可變、穿透力強,能全天時、全天候?qū)Φ貟呙璧葍?yōu)點,在國民經(jīng)濟和軍事領(lǐng)域都有著廣泛的應(yīng)用。然而由SAR系統(tǒng)成像機制所致,相干斑噪聲一直是嚴(yán)重影響SAR圖像成像質(zhì)量的重要因素,給SAR圖像后續(xù)的分類、分割、目標(biāo)檢測和識別等應(yīng)用帶來極大的困難。極化SAR圖像屬于SAR圖像的一種,也飽受相干斑噪聲的影響,其相干斑抑制工作一直是國際學(xué)者們研究的熱點之一。圖像分割也是圖像處理的主要研究方向之一,機場作為重要的軍事目標(biāo),SAR圖像中的機場檢測分割也有重要的研究價值。現(xiàn)有的分割方法都是依據(jù)一定的圖像特征、利用特定的分割準(zhǔn)則來完成圖像的分割,然而由于待分割樣本差異較大,不存在一種“最好”的算法適用于所有的分割問題,各種方法都存在各自的局限性,因此對各類分割方法的研究也一直沒有間斷過。對這兩個方面,本文的主要工作如下:(1)提出了一種基于貝葉斯非局部均值的極化SAR圖像質(zhì)量增強算法。結(jié)合非局部均值模型,在貝葉斯理論框架下給出了的權(quán)值計算方法及理論證明,通過驗證實驗本文方法得到的權(quán)值貼近數(shù)據(jù)的真實情況,本文方法的濾波結(jié)果在相干斑抑制和細(xì)節(jié)保持方面有較好的平衡。(2)提出了一種基于局部閾值分割的機場SAR圖像分割算法。機場都有明顯的幾何特征,本文從局部閾值分割的思想出發(fā),在圖像分塊的過程中利用機場結(jié)構(gòu)信息,使圖像的分塊更加合理,同時考慮到照度不均等因素造成的圖像強度不一致問題,引入了照度補償函數(shù)。通過對真實的機場SAR圖像分割測驗,本文提出的方法獲得了較為理想的分割結(jié)果,達(dá)到了預(yù)期的要求。
[Abstract]:Compared with optical sensors, synthetic Aperture radar (SAR) has multi-band, variable angle of view, strong penetration, and can be used all day. All-weather ground scanning has been widely used in national economy and military field. However, it is caused by the imaging mechanism of SAR system. Speckle noise has always been an important factor affecting the imaging quality of SAR images. It classifies and segments SAR images. The application of target detection and recognition brings great difficulties. Polarimetric SAR image is a kind of SAR image, which is also affected by speckle noise. Image segmentation is one of the main research directions of image processing, and the airport is an important military target. Airport detection and segmentation in SAR images also have important research value. Existing segmentation methods are based on certain image features, using specific segmentation criteria to complete image segmentation. However, due to the large differences of samples to be segmented, there is no "best" algorithm suitable for all segmentation problems, and each method has its own limitations. Therefore, the research on all kinds of segmentation methods has not been interrupted. The main work of this paper is as follows: (1) A new image quality enhancement algorithm based on Bayesian non-local mean is proposed, which combines the non-local mean model. Under the framework of Bayesian theory, the weight calculation method and the theoretical proof are given, and the experimental results show that the weights obtained by this method are close to the real situation of the data. The filtering results of this method have a good balance in speckle suppression and detail preservation.) A segmentation algorithm for airport SAR image based on local threshold segmentation is proposed. In this paper, based on the idea of local threshold segmentation, the field structure information is used in the process of image segmentation, which makes the image segmentation more reasonable, and takes into account the inconsistency of image intensity caused by the inhomogeneity of illumination. The illumination compensation function is introduced. By testing the real airport SAR image segmentation, the method proposed in this paper obtains more ideal segmentation results and meets the expected requirements.
【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】：2015
【分類號】：TN957.52

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本文編號：1366195