Extracting overlapping 2D-images by central-derivatives-based algorithm

Abstract

Abstract Usual algorithms, such as, 5-steps and a backward-derivatives-based (BDB) method, could extract an image of a top layer from a one of a base layer in a 2D full-field optical coherent tomography (FFOCT). Those both algorithms still give the robust images. For improving the quality of the image in 2D-FFOCT, in this research a central-derivatives-based (CDB) algorithm is introduced to apply for investigating two overlapping 2D images. According to our simulation, it shows that the performance of CDB-algorithm is as good as the one of 5-step algorithm in case a phase difference between each fringe images is not more than 40 degree. It is also less robust by comparing with the one of BDB-algorithm. By our experimental results, it can also be concluded that the CDB-algorithm can separate two overlapping 2D images with more brightness than the ones applied by BDB-algorithm.