CAJ | 학술논문

针对尺度不变特征变换（Scale Invariant Feature Transform，SIFT）算法图像配准时间长、匹配率低等问题，提出了重合区域图像极值特征提取法以及图像降采样特征配准法。在特征匹配的过程中，重点考虑重叠区域的特征匹配点对极值一致性约束条件，并利用差分尺度空间的局部单极值，以减小冗余特征点，节约特征提取与匹配时间；在此基础上，以图像尺度大小（选择180×180）作为缩放约束，对图像进行同比例插值缩小，并根据缩放后图像与原始图像变换矩阵之间的关系，计算出原始图像变换矩阵，实现图像的快速、精确配准。利用实例验证了所提方法的有效性和可行性。
침대척도불변특정변환（Scale Invariant Feature Transform，SIFT）산법도상배준시간장、필배솔저등문제，제출료중합구역도상겁치특정제취법이급도상강채양특정배준법。재특정필배적과정중，중점고필중첩구역적특정필배점대겁치일치성약속조건，병이용차분척도공간적국부단겁치，이감소용여특정점，절약특정제취여필배시간；재차기출상，이도상척도대소（선택180×180）작위축방약속，대도상진행동비례삽치축소，병근거축방후도상여원시도상변환구진지간적관계，계산출원시도상변환구진，실현도상적쾌속、정학배준。이용실례험증료소제방법적유효성화가행성。
The Scale Invariant Feature Transform(SIFT)algorithm with low matching rate and long time is widely used in image registration. In order to improve the matching rate and the real-time performance, an improved SIFT algorithm is proposed, which extracts the extreme feature of image in the overlapping areas and down-sample the image registration. In feature matching process, the extreme consistency constraints of matching points in overlap region are considered. In order to reduce the description of operator dimension and false matching, and improve the matching accuracy, the local unipolar value in differential scale space is used. On the basis, the image scaling constraints with 180×180 are presented. According to the resized image and original image, the relationship between two transformation matrixes is derived to realize the rapid and accurate image registration. At last, experimental results show the effectiveness and feasibility of the proposed method.