發(fā)布時(shí)間：2018-12-08 07:12

【摘要】：極化合成孔徑雷達(dá)(SAR)技術(shù)是一種先進(jìn)的遙感技術(shù),在現(xiàn)代國(guó)民經(jīng)濟(jì),尤其軍事領(lǐng)域的作用是越來(lái)越大。極化SAR技術(shù)不僅繼承了合成孔徑雷達(dá)技術(shù)的全天時(shí),全天候、高分辨率的優(yōu)勢(shì),并且相比較合成孔徑雷達(dá)技術(shù)極化SAR能夠獲得多種回波信號(hào),從而可以提供更加全面的散射信息。然而,極化SAR圖像中的斑點(diǎn)噪聲使極化SAR圖像信息的質(zhì)量大大降低,并且現(xiàn)有的極化SAR圖像質(zhì)量增強(qiáng)技術(shù)在濾除噪聲的同時(shí)不能很好地保持極化SAR圖像的散射特性,使其在極化SAR圖像的分類,分割,目標(biāo)檢測(cè)等的應(yīng)用中也受到影響。因此,極化SAR圖像的質(zhì)量增強(qiáng)技術(shù)在極化SAR圖像相關(guān)處理研究中比較重要,同時(shí),在長(zhǎng)期的研究過(guò)程中發(fā)現(xiàn),掌握極化SAR圖像像素點(diǎn)間散射特性相似性是比較重要的,對(duì)極化SAR圖像的質(zhì)量增強(qiáng),分類,目標(biāo)檢測(cè)等研究意義重大,然而,現(xiàn)有的散射特性相似性度量方法不能很好地度量極化SAR數(shù)據(jù)的散射特性。本文通過(guò)對(duì)合成以及真實(shí)極化SAR數(shù)據(jù)進(jìn)行統(tǒng)計(jì)分析,提出一種新的極化特性相似性度量方法,并將其應(yīng)用到極化SAR圖像的質(zhì)量增強(qiáng)技術(shù)的研究中,本文主要工作如下:(1)通過(guò)對(duì)大量合成的和真實(shí)的極化SAR數(shù)據(jù)的極化特性進(jìn)行研究,提出了一種新的極化SAR相似性度量方法。該相似性度量方法首先對(duì)極化SAR數(shù)據(jù)進(jìn)行基于散射模型的極化目標(biāo)分解得到極化特征向量,將極化特征向量建立三維極化特征空間,同時(shí)利用空間特征向量間的夾角以及它們模值的關(guān)系計(jì)算兩個(gè)像素點(diǎn)的極化相似性,通過(guò)與閾值的比較來(lái)決定兩個(gè)像素點(diǎn)是否相似。通過(guò)其驗(yàn)證實(shí)驗(yàn)發(fā)現(xiàn),該相似性度量方法能夠準(zhǔn)確并簡(jiǎn)便地度量出兩個(gè)像素點(diǎn)的極化相似性。(2)基于極化相似性的極化SAR圖像質(zhì)量增強(qiáng)算法。我們將極化相似性度量方法應(yīng)用到極化SAR圖像的質(zhì)量增強(qiáng)算法的研究中,提出了兩種基于極化相似性度量方法的極化SAR圖像質(zhì)量增強(qiáng)算法。第一種是基于散射特性的局部濾波算法,該算法首先對(duì)每一個(gè)待處理像素點(diǎn)進(jìn)行數(shù)據(jù)類型分類,判斷是否是低散射能量點(diǎn),是否為散射特性孤立點(diǎn),并根據(jù)其數(shù)據(jù)類型找到其相似像素點(diǎn)集合,進(jìn)一步利用Lee濾波模型進(jìn)行相干斑抑制。第二種是基于散射特性和NL-Lee濾波的極化SAR圖像質(zhì)量增強(qiáng)算法,該算法同樣首先對(duì)每一個(gè)待處理像素點(diǎn)進(jìn)行數(shù)據(jù)類型分類,判斷像素點(diǎn)是否為散射特性孤立點(diǎn),并根據(jù)其數(shù)據(jù)類型找到其相似像素點(diǎn)集合,進(jìn)一步利用NL-Lee濾波算法計(jì)算出參數(shù)k(i,j)以及利用數(shù)據(jù)類型來(lái)得到權(quán)值w(i,j),最終得到極化SAR圖像質(zhì)量增強(qiáng)的結(jié)果。
[Abstract]:Polarimetric synthetic Aperture Radar (SAR) is an advanced remote sensing technology, which plays a more and more important role in modern national economy, especially in military field. Polarization SAR technology not only inherits the advantage of all-day, all-weather and high resolution of synthetic Aperture Radar (SAR) technology, but also can obtain many kinds of echo signals compared with SAR technology. Thus more comprehensive scattering information can be provided. However, the speckle noise in polarimetric SAR images greatly reduces the quality of polarimetric SAR images, and the existing enhancement techniques of polarimetric SAR images can not preserve the scattering characteristics of polarimetric SAR images while filtering noise. It is also affected in the application of polarimetric SAR image classification, segmentation and target detection. Therefore, the quality enhancement of polarimetric SAR images is very important in the research of correlation processing of polarimetric SAR images. At the same time, it is found that it is important to grasp the similarity of scattering characteristics between pixels in polarimetric SAR images during a long period of research. It is of great significance to study the quality enhancement, classification and target detection of polarized SAR images. However, the existing methods for measuring the similarity of scattering characteristics can not well measure the scattering characteristics of polarimetric SAR data. Based on the statistical analysis of synthetic and real polarimetric SAR data, a new similarity measurement method of polarization characteristics is proposed in this paper, and applied to the study of quality enhancement of polarimetric SAR images. The main work of this paper is as follows: (1) by studying the polarization characteristics of a large number of synthetic and real polarimetric SAR data, a new polarimetric SAR similarity measurement method is proposed. Firstly, polarization eigenvector is obtained by polarization target decomposition based on scattering model for polarimetric SAR data, and the polarization feature space is established by polarization eigenvector. At the same time, the polarization similarity of the two pixels is calculated by using the angle between the spatial eigenvectors and the relationship between their modes, and the similarity between the two pixels is determined by comparing with the threshold. The experimental results show that the proposed method can accurately and easily measure the polarization similarity of two pixels. (2) the polarimetric SAR image quality enhancement algorithm based on polarization similarity. We apply the polarimetric similarity measure method to the study of the quality enhancement algorithm of polarimetric SAR images and propose two kinds of polarimetric SAR image quality enhancement algorithms based on the polarimetric similarity measurement method. The first is a local filtering algorithm based on scattering characteristics. Firstly, the algorithm classifies the data types of each pixel to determine whether it is a low scattering energy point or a scattering characteristic outlier. The similar pixel sets are found according to their data types, and speckle suppression is further carried out by using Lee filter model. The second is a polarimetric SAR image quality enhancement algorithm based on scattering characteristics and NL-Lee filtering. The algorithm also classifies the data types of each pixel to determine whether the pixel is a scattering characteristic outlier. The similar pixel set is found according to its data type, and then the parameter k (ij) is calculated by using NL-Lee filter algorithm and the weight value w (ij) is obtained by using data type. Finally, the quality enhancement results of polarimetric SAR images are obtained.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN957.52

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本文編號(hào)：2367932