發(fā)布時(shí)間：2018-10-10 17:00

【摘要】：基于遙感圖像的目標(biāo)檢測(cè)與運(yùn)動(dòng)目標(biāo)跟蹤是空間對(duì)地觀測(cè)的重要研究方向，在軍事監(jiān)測(cè)、戰(zhàn)場(chǎng)分析、交通管理等領(lǐng)域具有廣闊的應(yīng)用。針對(duì)高分辨率星載遙感圖像的軍事目標(biāo)檢測(cè)以及無(wú)人機(jī)對(duì)運(yùn)動(dòng)目標(biāo)的穩(wěn)定跟蹤成為現(xiàn)今各國(guó)學(xué)者的研究熱點(diǎn)之一。 本文以高分辨率遙感圖像中的小型團(tuán)塊目標(biāo)和遙感圖像序列中的運(yùn)動(dòng)目標(biāo)為研究對(duì)象，圍繞目標(biāo)檢測(cè)和運(yùn)動(dòng)目標(biāo)跟蹤問(wèn)題開(kāi)展研究。文章首先總結(jié)了遙感探測(cè)基礎(chǔ)、圖像特征分析以及目標(biāo)檢測(cè)理論；針對(duì)高分辨率遙感圖像中的小型團(tuán)塊目標(biāo)，分析了視覺(jué)注意機(jī)制在目標(biāo)檢測(cè)中的作用，，基于一種新型的視覺(jué)顯著性模型，綜合運(yùn)用背景抑制、MeanShift圖像分割、目標(biāo)提取等算法，有效地實(shí)現(xiàn)了對(duì)遙感圖像中小型團(tuán)塊目標(biāo)的檢測(cè)與自動(dòng)提��；其次針對(duì)遙感圖像序列，分析了已有運(yùn)動(dòng)目標(biāo)跟蹤算法的原理與特點(diǎn)，利用卡爾曼濾波對(duì)目標(biāo)運(yùn)動(dòng)狀態(tài)的估計(jì)特性，改進(jìn)原有的CamShift跟蹤算法，更有效的實(shí)現(xiàn)了運(yùn)動(dòng)目標(biāo)的穩(wěn)定跟蹤。
[Abstract]:Target detection and moving target tracking based on remote sensing image is an important research direction of space earth observation, which has wide applications in military monitoring, battlefield analysis, traffic management and so on. Military target detection based on high resolution space-borne remote sensing images and the steady tracking of moving targets by UAVs have become one of the hot research topics in many countries. In this paper, the small block target in high resolution remote sensing image and the moving target in remote sensing image sequence are taken as the research objects, and the problem of target detection and moving target tracking is studied. Firstly, the paper summarizes the basis of remote sensing detection, image feature analysis and target detection theory, and analyzes the role of visual attention mechanism in target detection for small block targets in high-resolution remote sensing images. Based on a new visual salience model, the algorithm of background suppression, MeanShift image segmentation and object extraction is used to effectively detect and automatically extract the small and medium block target of remote sensing image. Secondly, aiming at remote sensing image sequence, The principle and characteristics of the existing moving target tracking algorithms are analyzed. The original CamShift tracking algorithm is improved by using the Kalman filter to estimate the moving state of the target, and the stable tracking of moving target is realized more effectively.
【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)】：TP751

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