基于GPU的变型SIFT算子实时图像配准

GPU-based Real Time Image Registration with Variant SIFT

针对SIFT变型算法描述向量维数过高实、时性差的问题,分别在建立高斯尺度金字塔、关键点的亚像素定位等方面进行改进与并行化。利用CUDA设备构架在GPU硬件上实现多线程,一方面避免了PCA方法造成的关键点信息流失,另一方面使得配准速度达到了工程中的实时性要求。在VS2005平台上通过C语言实现混合CUDA编程,结果表明该方法使得配准速度和点对匹配正确率都有较大提升。

Improvements and parallelization in the aspects of creating differences of gaussian and locating sub-pixel keypoints were made against the problem that the dimension of descriptors from variant SIFT-GLOH（Gradient Location Orientation Histogram） is too high to meet the need of real time.The algorithm was implemented in multi-threads on the GPU hardware with CUDA（Compute Unified Device Architecture）.On one hand,the information loss of keypoints caused by PCA was avoided.On the other hand,the speed of registration sacrificed the need of real time in engineering.The programs were compiled by C language CUDA on VS2005 platform.The result shows that the ratio of correct matching point pairs and registration speed are both promoted greatly.