Search

In recent times, both the windowed Fourier ridges (WFR) and sampling moiré (SM) algorithms have been extensively used due to their high effectiveness in the demodulation of carrier fringe patterns. As they are developed independently, they are mostly recognized as completely different techniques, but we theoretically prove that SM is a special WFR with a specific window shape and a preset local frequency. This unifies the two different algorithms and enhances the understanding of their theoretical aspects, which helps to simplify the selection of these algorithms in real applications. [ABSTRACT FROM AUTHOR]

The windowed Fourier ridges (WFR) algorithm is shown to be a phase-shifting algorithm for phase extraction from a carrier fringe pattern. However, the former only provides a phase estimation with a controllable phase error, whereas the latter pursues exact phase extraction. This link not only is interesting but also enhances the understanding of different phase extraction techniques. Advantages and disadvantages of the WFRs algorithm are discussed. [ABSTRACT FROM AUTHOR]

Abstract: Phase unwrapping is an interesting yet challenging problem in optical interferometry. In this paper, we limit our interest to unwrapping noisy phase maps as it is a common but difficult task. Our aim is to propose a simple solution to phase unwrapping. We first remove the noise by a novel windowed Fourier transform approach and then use sequential line scanning method for phase unwrapping. This simple approach is verified to be very effective. [Copyright &y& Elsevier]

Abstract In this paper, deep learning as a novel algorithm is proposed to reduce the noise of the fringe patterns. Usually, the training samples are acquired through experimental acquisition, but these data can be easily obtained by simulations in the proposed algorithm. Thus, the time cost used for the whole training process is greatly reduced. The performance of the proposed algorithm has been demonstrated through the analysis on the simulated and real fringe patterns. It is obvious that the proposed algorithm has a faster calculation speed compared with existing denoising algorithm, and recovers the fringe patterns with high quality. Most importantly, the proposed algorithm may provide a solution to other denoising problems in the field of optics, such as hologram and speckle denoising. [ABSTRACT FROM AUTHOR]

Simulation of physically based deformable models is a hot topic in computer graphics. Most of the existing models focus on isotropic materials and some on transversely isotropic materials. We propose a modeling method for orthotropic materials, which exhibits different mechanical behaviors along three orthogonal directions. First, constraints for the strain energy density in linear elastic models are analyzed, and a positive-definite elasticity tensor is derived for an orthotropic material. Second, an orthotropic deformation controlling frame-field is conceptualized and a frame construction tool is developed for users to define the desired material properties. A quaternion Laplacian smoothing algorithm is proposed, and several user-defined rotation minimizing frames are propagated into the entire body of the deformable object, which forms a smooth frame-field. Third, the corotational linear FEM model coupled with the orthonormal frame-field is formulated to realize a dynamics system, which can deal with large deformations. All the algorithms have been implemented in a comprehensive modeling and simulation system, and a GUI is provided to design the orthotropic model. Experiments on real-time deformation simulation and analytical comparisons are presented. [ABSTRACT FROM AUTHOR]

• A computational ghost imaging method is proposed based on sparse reconstruction. • The burden of key management such as storage and transmission is considerably reduced. • Information can be authenticated when a significantly small part of speckle patterns are used. In the traditional optical cryptosystems based on computational ghost imaging, a large number of phase-only masks or speckle patterns are generated to reconstruct the object image with high visual quality. At the same time, this kind of massive data, which is usually considered as the security keys to enhance the security of the cryptosystem, needs to be stored and transmitted and leads to low efficiency in practical applications. To address this issue, a computational ghost imaging method based on sparse reconstruction with the Barzilai-Borwein gradient projection is proposed from a new perspective of applying the compressive sensing technique in this paper. The measured intensities of the object image are collected by the means of traditional computational ghost imaging, while the security key composed of speckle patterns is compressed using compressive sensing and then transmitted in the secure channel in the proposed method. Consequently, the burden of key management such as storage and transmission can be considerably decreased. Moreover, when a significantly small part of the security key is shared in the secure channel, original information still can be authenticated without clear visualization by calculating the nonlinear correlation map between the object image and its reconstruction. The optical experiments illustrate the feasibility and effectiveness of the proposed method and demonstrate that it can provide an effective alternative for enriching the related research on computational ghost imaging techniques. [ABSTRACT FROM AUTHOR]