计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2013年
22期
173-179
,共7页
魏然然%戴芹%刘士彬%马彩虹
魏然然%戴芹%劉士彬%馬綵虹
위연연%대근%류사빈%마채홍
基于内容的图像检索%遥感图像%五叉2/3边长分解法%纹理特征提取
基于內容的圖像檢索%遙感圖像%五扠2/3邊長分解法%紋理特徵提取
기우내용적도상검색%요감도상%오차2/3변장분해법%문리특정제취
content-based image retrieval%remote sensing images%decomposition method of quintuple 2/3 side-length%texture feature extraction
由于一幅遥感图像是对一定范围内的地表状态的成像,并且遥感图像具有多样性、复杂性、海量等性质,致使遥感图像检索往往是查询图像和图像库图像的局部区域之间的相似性匹配。为了提高遥感图像的检索效率,必须首先对遥感图像进行分解。提出了一种将遥感图像分层分解的遥感图像检索方法,该方法利用改进五叉树分解法将图像库图像按层次分解成不同大小的子图,在提取子图的纹理特征后,以查询图像和图像库子图之间的欧式距离衡量图像相似度,实现了遥感图像检索。利用海地地震时的航空遥感图像作为实验数据,应用改进五叉树分解法将遥感图像分解后,进行查询检索实验,并与普通五叉树进行了对比。实验结果表明利用改进五叉树分解法进行遥感图像分解后得到的分块图像,可以更精准地查询出用户真正感兴趣的部分,能够获得较高的查全率和查准率,提高查询效率。
由于一幅遙感圖像是對一定範圍內的地錶狀態的成像,併且遙感圖像具有多樣性、複雜性、海量等性質,緻使遙感圖像檢索往往是查詢圖像和圖像庫圖像的跼部區域之間的相似性匹配。為瞭提高遙感圖像的檢索效率,必鬚首先對遙感圖像進行分解。提齣瞭一種將遙感圖像分層分解的遙感圖像檢索方法,該方法利用改進五扠樹分解法將圖像庫圖像按層次分解成不同大小的子圖,在提取子圖的紋理特徵後,以查詢圖像和圖像庫子圖之間的歐式距離衡量圖像相似度,實現瞭遙感圖像檢索。利用海地地震時的航空遙感圖像作為實驗數據,應用改進五扠樹分解法將遙感圖像分解後,進行查詢檢索實驗,併與普通五扠樹進行瞭對比。實驗結果錶明利用改進五扠樹分解法進行遙感圖像分解後得到的分塊圖像,可以更精準地查詢齣用戶真正感興趣的部分,能夠穫得較高的查全率和查準率,提高查詢效率。
유우일폭요감도상시대일정범위내적지표상태적성상,병차요감도상구유다양성、복잡성、해량등성질,치사요감도상검색왕왕시사순도상화도상고도상적국부구역지간적상사성필배。위료제고요감도상적검색효솔,필수수선대요감도상진행분해。제출료일충장요감도상분층분해적요감도상검색방법,해방법이용개진오차수분해법장도상고도상안층차분해성불동대소적자도,재제취자도적문리특정후,이사순도상화도상고자도지간적구식거리형량도상상사도,실현료요감도상검색。이용해지지진시적항공요감도상작위실험수거,응용개진오차수분해법장요감도상분해후,진행사순검색실험,병여보통오차수진행료대비。실험결과표명이용개진오차수분해법진행요감도상분해후득도적분괴도상,가이경정준지사순출용호진정감흥취적부분,능구획득교고적사전솔화사준솔,제고사순효솔。
Remote sensing image is an imagery of surface status within a certain range, which has the properties such as diversity, complexity and mass. That is why the remote sensing image retrieval is often a comparison between target image and sub images of the image database. So the remote sensing image should be decomposed before retrieval. This paper puts forward a new remote sensing image retrieval approach by using improved quintuple tree image decomposition method. First of all, the image is decom-posed by improved quintuple tree image decomposition method, which splits large scale remote sensing imagery into sub images. Then texture features of each image block are extracted. Finally, the euclidean distance is computed which is between target image and sub images of the remote sensing image in the image database. These images are returned according to their euclidean distance as the final retrieval results. Aerial remote sensing images during the earthquake of Haiti are used in the experiment, which make a comparison between improved quintuple tree image decomposition method and quintuple tree image decomposition method. The improved quintuple tree image decomposition method is validated using the result of the experiment. It can accurately catch the interested sub images of the user, so a higher recall and precision can be reached.