CAJ | 학술논문

针对基于局部特征匹配的图像配准和识别算法对于多谱段图像配准性能较差的缺点,提出一种基于局部特征聚类匹配的图像配准方法,该方法针对多谱图像的特点构建优化的局部特征提取算子,根据特征点对的相对主方向统计信息对初始匹配点集重新聚类,求出正确匹配的点对子集以实现配准.实验结果表明,该算法较大地提高了多谱图像配准的正确率和精度.
침대기우국부특정필배적도상배준화식별산법대우다보단도상배준성능교차적결점,제출일충기우국부특정취류필배적도상배준방법,해방법침대다보도상적특점구건우화적국부특정제취산자,근거특정점대적상대주방향통계신식대초시필배점집중신취류,구출정학필배적점대자집이실현배준.실험결과표명,해산법교대지제고료다보도상배준적정학솔화정도.
Image registration and object recognition algorithm based on local feature match often falls when aligning multispectral images. Aiming at such shortcoming, this paper presents a registration algorithm based on local feature match by using clustering. It builds optimized local feature descriptors according to the characteristic of multispoctral images and obtains the correct set of corresponding points by using the statistical information of the relative main orientation. Experimental results confirm that the correct rate and registration accuracy are substantially improved by the algorithm.