發(fā)布時(shí)間：2018-08-01 08:16

【摘要】：合成孔徑雷達(dá)（SAR）因其特有的相干成像機(jī)理，成像結(jié)果存在諸多不同于光學(xué)圖像的質(zhì)量問(wèn)題，如旁瓣噪聲、相干斑等，使得圖像動(dòng)態(tài)范圍小、對(duì)比度低、模糊，嚴(yán)重影響SAR圖像解譯。質(zhì)量評(píng)估過(guò)程是用客觀參數(shù)對(duì)SAR圖像質(zhì)量?jī)?yōu)劣進(jìn)行評(píng)價(jià)的過(guò)程，是圖像解譯前的預(yù)處理步驟，具有重要的研究?jī)r(jià)值。本文針對(duì)SAR圖像質(zhì)量評(píng)估方法進(jìn)行深入研究，主要內(nèi)容如下： 1.研究了SAR圖像質(zhì)量評(píng)估的基本方法。RADARSAR、ENVISAT、J-ERS等著名的雷達(dá)系統(tǒng)都在地面上建有雷達(dá)數(shù)據(jù)質(zhì)量監(jiān)測(cè)站，從分辨率、旁瓣強(qiáng)度、幾何定位精度、輻射分辨率等方面對(duì)雷達(dá)回波數(shù)據(jù)質(zhì)量進(jìn)行初步評(píng)估。本文根據(jù)評(píng)估方法的不同將這些參數(shù)分為點(diǎn)目標(biāo)質(zhì)量參數(shù)和面目標(biāo)質(zhì)量參數(shù)，并具體闡述它們的定義及計(jì)算方法。針對(duì)點(diǎn)目標(biāo)難以獲取，點(diǎn)目標(biāo)質(zhì)量參數(shù)存在較大計(jì)算誤差的問(wèn)題，提出了用復(fù)數(shù)SAR圖像區(qū)域相干相關(guān)函數(shù)評(píng)估點(diǎn)目標(biāo)質(zhì)量參數(shù)的方法。仿真及實(shí)測(cè)SAR圖像數(shù)據(jù)都證明該方法用于計(jì)算SAR圖像的分辨率、峰值旁瓣比、積分旁瓣比等質(zhì)量指標(biāo)時(shí)是有效的。 2.研究了SAR圖像散焦模糊的原理及散焦模糊程度評(píng)估算法。散焦模糊是導(dǎo)致SAR圖像模糊的重要原因之一，主要由調(diào)頻率估計(jì)誤差導(dǎo)致。本文從SAR的成像原理出發(fā)，分析散焦模糊對(duì)成像結(jié)果的影響，得到散焦點(diǎn)目標(biāo)主瓣展寬、旁瓣升高，形成類似光學(xué)圖像運(yùn)動(dòng)模糊結(jié)果的結(jié)論。基于此，本文以運(yùn)動(dòng)模糊參數(shù)評(píng)估方法為基礎(chǔ)尋找有效的SAR圖像散焦模糊參數(shù)評(píng)估算法，，提出了用圖像截?cái)囝l譜的Radon變換評(píng)估模糊方向，大窗口中值濾波器快速去噪，用圖像顯著性區(qū)域平均邊緣寬度評(píng)估散焦模糊程度的算法。文中定義了一個(gè)散焦模糊度評(píng)估指標(biāo)UBD，實(shí)驗(yàn)證明該指標(biāo)能夠給出與主觀評(píng)估相一致的結(jié)論。 3.研究了SAR圖像對(duì)比度評(píng)估方法及增強(qiáng)算法。圖像對(duì)比度反映圖像的清晰程度，決定圖像的信息獲取能力。SAR圖像對(duì)比度評(píng)估不僅是圖像質(zhì)量評(píng)估的重要組成部分，還能客觀評(píng)價(jià)圖像增強(qiáng)算法的優(yōu)劣。文中闡述了兩種基于人眼視覺特性的對(duì)比度評(píng)估參數(shù)，EME和TEN，實(shí)驗(yàn)驗(yàn)證了用EME-TEN參數(shù)組合評(píng)估SAR圖像對(duì)比度的有效性。本文還深入研究了將模糊理論應(yīng)用于圖像增強(qiáng)的方法，基于此提出了最小模糊偏移度準(zhǔn)則下SAR圖像自動(dòng)對(duì)比度增強(qiáng)算法。利用
[Abstract]:Because of its unique coherent imaging mechanism, the imaging results of synthetic Aperture Radar (SAR) have many quality problems different from optical images, such as sidelobe noise, speckle and so on, which make the image dynamic range small, contrast low and blur. SAR image interpretation is seriously affected. The process of quality evaluation is to evaluate the quality of SAR images with objective parameters. It is a pre-processing step before image interpretation and has important research value. The main contents of this paper are as follows: 1. This paper studies the basic method of SAR image quality evaluation. The famous radar systems, such as RADARSARN ENVISATJERS and so on, have built radar data quality monitoring stations on the ground, including resolution, sidelobe intensity, geometric positioning accuracy, etc. The quality of radar echo data is preliminarily evaluated in terms of radiative resolution. In this paper, according to the different evaluation methods, these parameters are divided into point target quality parameters and surface target quality parameters, and their definitions and calculation methods are described in detail. In order to solve the problem that point target is difficult to obtain and point target quality parameter has large calculation error, a method of evaluating point target quality parameter by using coherent correlation function of complex SAR image region is presented in this paper. The simulated and measured SAR image data show that the proposed method is effective in calculating the resolution, peak sidelobe ratio and integral sidelobe ratio of SAR images. The principle of defocus blur in SAR image and the evaluation algorithm of defocus blur degree are studied. Defocus blur is one of the important causes of SAR image blur, which is mainly caused by the frequency estimation error. Based on the imaging principle of SAR, this paper analyzes the influence of defocus blur on imaging results, and obtains the conclusion that the main lobe is widened and the sidelobe is raised, which is similar to the result of motion blur of optical image. Based on the method of motion blur parameter evaluation, an effective defocus fuzzy parameter evaluation algorithm for SAR image is proposed in this paper. The Radon transform of image truncation spectrum is used to evaluate the fuzzy direction, and the median filter with large window is used for fast denoising. An algorithm for evaluating defocus ambiguity with the mean edge width of image salient region. In this paper, a defocusing ambiguity evaluation index, UBDD, is defined, and it is proved by experiments that the index can reach a conclusion consistent with the subjective evaluation. The contrast evaluation method and enhancement algorithm of SAR image are studied. Image contrast reflects the clarity of image, and determines the ability of image information acquisition. SAR image contrast evaluation is not only an important part of image quality assessment, but also can objectively evaluate the merits and demerits of image enhancement algorithm. In this paper, two contrast evaluation parameters based on human visual characteristics, EME and TEN, are described, and the effectiveness of using EME-TEN parameter combination to evaluate the contrast of SAR images is verified by experiments. The method of applying fuzzy theory to image enhancement is also studied in this paper. Based on this, an automatic contrast enhancement algorithm for SAR images based on minimum fuzzy offset criterion is proposed. Utilization
【學(xué)位授予單位】：國(guó)防科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：TN957.52

【參考文獻(xiàn)】

相關(guān)期刊論文 前7條

1 張榮;楊建朝;張倩;劉政凱;;SAR圖像運(yùn)動(dòng)模糊參數(shù)估計(jì)[J];電子學(xué)報(bào);2007年10期

2 吳成茂;;可調(diào)直方圖均衡化的正則解釋及其改進(jìn)[J];電子學(xué)報(bào);2011年06期

3 張銳;洪峻;明峰;;基于電磁散射的復(fù)雜目標(biāo)SAR回波與圖像仿真[J];電子與信息學(xué)報(bào);2010年12期

4 陶青川,鄧宏彬;基于小波變換的高斯點(diǎn)擴(kuò)展函數(shù)估計(jì)[J];光學(xué)技術(shù);2004年03期

5 武治國(guó);王延杰;;一種基于直方圖非線性變換的圖像對(duì)比度增強(qiáng)方法[J];光子學(xué)報(bào);2010年04期

6 張弓,張昆輝,朱兆達(dá),朱寧儀;一種基于逼近信噪比的SAR圖像質(zhì)量評(píng)估方法[J];南京航空航天大學(xué)學(xué)報(bào);2004年02期

7 王懷軍;粟毅;許紅波;朱宇濤;;微波成像譜變形旁瓣抑制方法[J];中國(guó)科學(xué):信息科學(xué);2010年12期

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