This paper presents a new processing method for denoising interferograms obtained by digital holographic speckle pattern interferometry (DHSPI) to serve in the structural diagnosis of artworks. DHSPI is a non-destructive and non-contact imaging method that has been successfully applied to the structural diagnosis of artworks by detecting hidden subsurface defects and quantifying the deformation directly from the surface illuminated by coherent light. The spatial information of structural defects is mostly delivered as local distortions interrupting the smooth distribution of intensity during the phase-shifted formation of fringe patterns. Distortions in fringe patterns are recorded and observed from the estimated wrapped phase map, but the inevitable electronic speckle noise directly affects the quality of the image and consequently the assessment of defects. An effective method for denoising DHSPI wrapped phase based on deep learning is presented in this paper. Although a related method applied to interferometry for reducing Gaussian noise has been introduced, it is not suitable for application in DHSPI to reduce speckle noise. Thus, the paper proposes a new method to remove speckle noise in the wrapped phase. Simulated data and experimental captured data from samples prove that the proposed method can effectively reduce the speckle noise of the DHSPI wrapped phase to extract the desired information. The proposed method is helpful for accurately detecting defects in complex defect topography maps and may help to accelerate defect detection and characterization procedures.

Current development in a deep neural network (DNN) has given an opportunity to a novel framework for the reconstruction of a holographic image and a phase recovery method with real‐time performance. There are many deep learning‐based techniques that have been proposed for the holographic image reconstruction, but these deep learning‐based methods can still lack in performance, time complexity, accuracy, and real‐time performance. Due to iterative calculation, the generation of a CGH requires a long computation time. A novel deep generative adversarial network holography (GAN‐Holo) framework is proposed for hologram reconstruction. This novel framework consists of two phases. In phase one, we used the Fresnel‐based method to make the dataset. In the second phase, we trained the raw input image and holographic label image data from phase one acquired images. Our method has the capability of the noniterative process of computer‐generated holograms (CGHs). The experimental results have demonstrated that the proposed method outperforms the existing methods.

Stitching interferometry is a common method for measuring the figure error of high numerical aperture optics. However, subaperture measurement usually requires a fringe-nulling routine, thus making the stitching procedure complex and time-consuming. The challenge when measuring a surface without a fringe-nulling routine is that the rays no longer perpendicularly hit the surface. This violation of the null-test condition can lead to high fringe density and introduce high-order misalignment aberrations into the measurement result. This paper demonstrates that the high-order misalignment aberrations can be characterized by low-order misalignment aberrations; then, an efficient method is proposed to separate the high-order misalignment aberrations from subaperture data. With the proposed method, the fringe-nulling routine is not required. Instead, the subaperture data is measured under a nonzero fringe pattern. Then, all possible misalignment aberrations are removed with the proposed method. Finally, the full aperture map is acquired by connecting all subaperture data together. Experimental results showing the feasibility of the proposed procedure are presented.

An interferogram obtained from a transparent plate contains information on the profiles of both surfaces and on the thickness variation. The present work is devoted to the processing of interferograms of this type. The processing technique is based on a 36-step algorithm developed by the authors for characterization of transparent plates having approximately equal reflections from both sides. The algorithm utilizes weighted multi-step phase shifting that enables one not only separately to extract the front and rear surface profiles together with the thickness variation of the tested plate but also to suppress the coupling errors between the higher harmonics and phase-shift deviation. The proposed measuring method was studied on a wavelength tunable Fizeau interferometer. The tested sample had an optical thickness and surface profile deviations equal to 0.51 µm, 1.38 µm and 0.89 µm, respectively. According to the results obtained using 10 repeated measurements, the root mean square (RMS) errors for determining both surface profiles did not exceed 1.5 nm. Experimental results show that the setup and presented 36-step algorithm are suitable for the measurement of a transparent plate of arbitrary thickness.

Compressive holography is a combination of compressive sensing and holography. In this paper, an approach to expand the amplification ratio and enhance the axial resolution in in-line compressive holography is proposed. Firstly the basic principle of 4f amplified in-line compressive holography is described. Next the feasibility of reconstructing object and analysis of reconstruction quality is verified. Finally, both simulated and real experiments on multilayer objects with non-overlapping and overlapping patterns are demonstrated to validate the approach.

Since the cylinder surface is closed and periodic in the azimuthal direction, traditional stitching interferometry cannot be used to yield the 360° form map. This paper describes a full cylinder stitching interferometry based on the first-order approximation of cylindrical coordinate transformation. First, it introduces cylindrical projection, which allows us to determine the overlap region of the cylinder without ambiguity. Second, the relationship between the variations of radial coordinates and the movement errors of the rotational stage is derived from the first-order approximation of cylindrical coordinate transformation. Based on this relation, a cylinder stitching model is built to connect all sub-apertures together. Finally, we experimentally validate the proposed method by measuring a precision metal shaft. The high resolution and repeatability shown in the experimental results demonstrate our approach to be an attractive and promising technique in the field of precision measurement.