基于CSIFT的彩色图像配准技术研究

图像配准在计算机视觉、遥感、医学诊断与治疗、环境监测等领域有广泛的研究应用.目前,多数算法是将彩色图像转化为灰度图后再配准,色彩信息的丢失可能会引起误配准.为此,提出一种基于CSIFT(Colored scale invariant feature transform)的彩色图像配准方法,求出彩色图像各个位置处的颜色不变最,以颜色不变量作为输入图像,再提取特征点并描述特征点周围的信息,通过最近邻匹配法求出图像问的匹配对,最后利用匹配的特征求取图像间的变换参数及配准后图像.实验结果表明,对彩色图像进行已知参数值变换时,该算法能得到精度高、误差小的计算结果;对变换关系末知的彩色图像,也能准确地求出图像间的映射关系;且多数情况下运行速度较SIFT(Scale invariant feature transform)快.

Study on Color Image Registration Technique Based on CSIFT

Image registration technique has been widely studied and used in many fields, such as computer vision, remote sensing, medical diagnosis and treatment, environmental monitoring. Presently, registration happens after the color image is transformed into gray one in most algorithms, which causes color information loss and may lead to wrong registration. For this reason, a color image registration algorithm based on color scale invariant feature transform (CSIFT) is proposed. Firstly, color invariant value is calculated at each location in color images. Secondly feature points are extracted and neighbor information around these points is described using color invariant value as input information. Thirdly the points between two images are matched using the nearest neighbor method. Finally transformation parameters between images and the registered image can be determined using matched features. Experimental results indicate that high accuracy and small errors can be achieved when parameter values are transformed in color images, and mapping relationship can also be acquired correctly in the condition of unknown transformed relationship. This method is fast in operation in most conditions.