摘要
An effective image splicing algorithm based on phase correlation and speeded-UP robust features （SURF） operator is proposed which can sort the disordered sequence and stitch them into a super viewing field image without any human intervention. Phase correlation in frequency domain is used for images sorting and region of interest （ROI） estimation, and guiding features extracting and matching in spatial domain by SURF operator and bidirectional best bin first （BBF） strategy. The experimental results demonstrate that this algorithm not only can deal with the input images with translation, rotation and scale changes, but also outperforms the pre-existing methods on the aspect of repeatability, efficiency and accuracy.
An effective image splicing algorithm based on phase correlation and speeded-UP robust features （SURF） operator is proposed which can sort the disordered sequence and stitch them into a super viewing field image without any human intervention. Phase correlation in frequency domain is used for images sorting and region of interest （ROI） estimation, and guiding features extracting and matching in spatial domain by SURF operator and bidirectional best bin first （BBF） strategy. The experimental results demonstrate that this algorithm not only can deal with the input images with translation, rotation and scale changes, but also outperforms the pre-existing methods on the aspect of repeatability, efficiency and accuracy.
