光学学报
光學學報
광학학보
ACTA OPTICA SINICA
2009年
10期
2744-2750
,共7页
图像处理%图像配准%非采样Contourlet变换%归一化互相关%概率支撑匹配
圖像處理%圖像配準%非採樣Contourlet變換%歸一化互相關%概率支撐匹配
도상처리%도상배준%비채양Contourlet변환%귀일화호상관%개솔지탱필배
image processing%image registration%nonsubsampled contourlet transform%normalized crosscorrelation%probability support matching
为了提高高分辨率遥感图像配准的精确度,将非采样Contourlet变换应用于高分辨率遥感图像配准算法中.首先对高分辨率遥感图像进行非采样Contourlet变换.利用非采样Contourlet变换的平移不变性在变换域提取图像的边缘并选择合适的阈值准确地得到图像的边缘特征点.然后利用归一化互相关匹配法和概率支撑法对特征点进行匹配.最后通过三角形局部变换映射甬数实现图像配准.实验结果表明,该方法更能准确地提取高分辨率遥感图像的特征点,大大提高了正确匹配的概率,与基于小波方法的图像配准效果相比有更高的准确性和稳健性.
為瞭提高高分辨率遙感圖像配準的精確度,將非採樣Contourlet變換應用于高分辨率遙感圖像配準算法中.首先對高分辨率遙感圖像進行非採樣Contourlet變換.利用非採樣Contourlet變換的平移不變性在變換域提取圖像的邊緣併選擇閤適的閾值準確地得到圖像的邊緣特徵點.然後利用歸一化互相關匹配法和概率支撐法對特徵點進行匹配.最後通過三角形跼部變換映射甬數實現圖像配準.實驗結果錶明,該方法更能準確地提取高分辨率遙感圖像的特徵點,大大提高瞭正確匹配的概率,與基于小波方法的圖像配準效果相比有更高的準確性和穩健性.
위료제고고분변솔요감도상배준적정학도,장비채양Contourlet변환응용우고분변솔요감도상배준산법중.수선대고분변솔요감도상진행비채양Contourlet변환.이용비채양Contourlet변환적평이불변성재변환역제취도상적변연병선택합괄적역치준학지득도도상적변연특정점.연후이용귀일화호상관필배법화개솔지탱법대특정점진행필배.최후통과삼각형국부변환영사용수실현도상배준.실험결과표명,해방법경능준학지제취고분변솔요감도상적특정점,대대제고료정학필배적개솔,여기우소파방법적도상배준효과상비유경고적준학성화은건성.
For the purpose of improving high-resolution remote sensing images registration precision,nonsubsampled contourlet transform is applied to high-resolution remote sensing images registration. Firstly, for nonsubsampled contourlet transform shift invariance, nonsubsampled contourlet transform is used to extract the images edge in contourlet transform domain and the feature points are extracted from images edge by selecting an appropriate threshold. Then, normalized cross-correlation matching and probability support matching method are used to match the images feature points. Finally, triangle-based local transformation function is employed to register the images. The experimental results show that this method can more accurately extract the corresponding feature points of high-resolution remote sensing images and increase correct matching probability and have more precise and more robust registration effect than the method based on wavelet.