空军工程大学学报(自然科学版)
空軍工程大學學報(自然科學版)
공군공정대학학보(자연과학판)
JOURNAL OF AIR FORCE ENGINEERING UNIVERSITY (NATURAL SCIENCE EDITION)
2014年
1期
72-76
,共5页
SIFT%图像配准%特征匹配%图像处理
SIFT%圖像配準%特徵匹配%圖像處理
SIFT%도상배준%특정필배%도상처리
SIFT%image matching%feature matching%image processing
针对SIFT特征匹配算法在特征空间中进行历遍搜索,匹配速度慢的问题,提出一种金字塔层间匹配算法。首先,根据特征点所处金字塔层不同将特征点划分为不同的集合,其次,选择待配准图像金字塔中某一层集合,在基准图像金字塔中寻找相似层,并确定待配准图像金字塔与基准图像金字塔层之间的相似关系,最后,在相似层之间寻找匹配点。待配准图像中的选择层集合由金字塔底层到顶层,寻找相似层所用时间依次缩短。与原算法相比,该算法具有相同的旋转稳定性。将该算法与原算法分别应用实际图像配准中,结果表明:可见光图像配准中,匹配速度提高了3.2倍,正确匹配率提高了10.3%,红外图像配准中,匹配速度提高1.4倍,正确匹配率达到100%。
針對SIFT特徵匹配算法在特徵空間中進行歷遍搜索,匹配速度慢的問題,提齣一種金字塔層間匹配算法。首先,根據特徵點所處金字塔層不同將特徵點劃分為不同的集閤,其次,選擇待配準圖像金字塔中某一層集閤,在基準圖像金字塔中尋找相似層,併確定待配準圖像金字塔與基準圖像金字塔層之間的相似關繫,最後,在相似層之間尋找匹配點。待配準圖像中的選擇層集閤由金字塔底層到頂層,尋找相似層所用時間依次縮短。與原算法相比,該算法具有相同的鏇轉穩定性。將該算法與原算法分彆應用實際圖像配準中,結果錶明:可見光圖像配準中,匹配速度提高瞭3.2倍,正確匹配率提高瞭10.3%,紅外圖像配準中,匹配速度提高1.4倍,正確匹配率達到100%。
침대SIFT특정필배산법재특정공간중진행력편수색,필배속도만적문제,제출일충금자탑층간필배산법。수선,근거특정점소처금자탑층불동장특정점화분위불동적집합,기차,선택대배준도상금자탑중모일층집합,재기준도상금자탑중심조상사층,병학정대배준도상금자탑여기준도상금자탑층지간적상사관계,최후,재상사층지간심조필배점。대배준도상중적선택층집합유금자탑저층도정층,심조상사층소용시간의차축단。여원산법상비,해산법구유상동적선전은정성。장해산법여원산법분별응용실제도상배준중,결과표명:가견광도상배준중,필배속도제고료3.2배,정학필배솔제고료10.3%,홍외도상배준중,필배속도제고1.4배,정학필배솔체도100%。
Aimed at the slow matching speed of SIFT feature matching method in searching the whole data-base of feature points for matching points,an improved matching method of searching between the layers of the pyramid is proposed for improving the speed of SIFT matching.First,according to the feature points in different layers of the pyramid,the feature points are divided into different sets.Then a layer set in the input image pyramid is chosen to search for the similar layer in the template image pyramids,and then the similarity between input image pyramid and the template pyramid is determined.Finally,the mat-ches are found between the similar layers.The chosen layer in the input image pyramid is from the bottom of the pyramid to the top of the pyramid.By so doing,the time of searching for similar layer is shorten. Compared with the original algorithm,this algorithm has the same rotational stability.This algorithm and the original algorithm are applied to the actual image registration respectively,the results show that the matching speed is 3.2 times as fast as the original matching speed and the correct matching rate is increased by 10.3% in visual image registration.In infrared image registration the matching speed is 1.4 times as fast as the original matching speed and the correct matching rate reaches 100%.