Phase Splicing Method Based on Multi-Algorithm Fusion in Holography

Quantitative phase image stitching guided by reconstructed intensity images in one-shot double field of view multiplexed digital holographic microscopy

“…To test the stitching accuracy under different overlap rates, in addition to DPIS, two commonly used feature extraction algorithms were also compared. Following the phase image stitching strategy guided by the reconstructed intensity image, only in the intensity map feature extraction module, the combination of the Canny operator, cross-correlation algorithm and SIFT algorithm is replaced by: (1) phase correlation method (overlap areas location) and Harris corner detection (feature extraction) [ 11 ], referred to as PCHCD; (2) speed up robust feature algorithm [ 36 ] (for the entire image), referred to as SURF; other steps are the same as the proposed method.…”

“…Wen et al established a mathematical model of the DH phase error and corrected the relative rotation error between CCD coordinate system and two-dimensional (2D) motion stage [ 10 ], but could not fully compensate for the stitching error caused by axial misalignment between the overlap sub-apertures. Xie et al integrated multiple algorithms such as phase correlation, Harris corner detection, and full matching search into the DH phase stitching to improve the stitching efficiency [ 11 ]. This method requires at least 50% overlap areas between the phase images to be stitched, and cannot handle the phase images with complex textures.…”