Due to climate change a slowly increasing annual temperature may be experienced by structures. Relative humidity (RH) fluctuations affect the equiibrium moisture content of materials. Repeated RH cycling leads to mechanical failure and may endanger an object's structural integrity. Preventive conservation is based on adopting measures that will prevent fracture. Real-time interferometry allows the acquisition of sequential high-resolution full-field surface images from hygroscopic materials used in cultural heritage by recording during cycles of changing RH. The differential images allow the development of a preventive methodology directly through surface responses. Indications of the natural onset of degradation can be followed and traced before visible damage occurs, allowing preventive measures to be taken in advance. An ongoing study (Climate for Culture European project (FP7-ENV-2008-1 CfC no. 226973)) aims to experimentally classify structural deterioration as a function of acclimatization and confirm the hypothesis that surface responses before deformation can indicate deformation threshold values as reference points for the onset of RH-induced deterioration.

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.

Cultural heritage conservation is an active field of research, where there is an ever‐growing demand for nondestructive and noninvasive diagnostic techniques, for performing remote analysis and diagnosis of the condition of historical structures and pieces of art, often of very high cultural and historical value. In this context, holographic interferometry is a very well‐established optical technique for research in cultural heritage, which brings together some very basic and critical properties such as contactless examination and nondestructivity, accuracy, repeatability, and a wide range of applicability. In this paper, the optical technique of digital holographic interferometry is tested on mock‐up, art‐related targets, with 2 different light sources, in an attempt to expand the technique towards a new approach that will profit from an easy‐to‐operate, inexpensive, and tunable source, offering a broad spectrum and wavelength selectivity, according to the needs of the experiments. Examples are presented, and the results demonstrate the effectiveness of the proposed modified experimental scheme for defect mapping, to be used in structural documentation reports, and for its exploitation in future hybrid optical diagnostic systems and data processing.

No abstract