Towards the Definition of a Low-Cost Toolbox for Qualitative Inspection of Painted Historical Vaults by Means of Modified DSLR Cameras, Open Source Programs and Signal Processing Techniques

Abstract

Historical architecture is a primary element containing the identity values of a society. The wide diffusion of many ancient buildings gathering part of these values on painting walls over territories often characterized by poor technological or economic resources brings to consider the development of low-cost protocols to inspect valued surfaces and to give the authorities in charge of preservation and restoration adequate technical information. Here we present the preliminary results of a recent application of remote sensing micro-geophysical techniques to typical architectural targets such as vaults. A modified commercial Digital Single-Lens Reflex (DSLR) camera was used to acquire multispectral datasets on portions of a painted vault. Multispectral datasets were used raw or after the application of a pre-processing step with a Multi Images Stacking (MIS) algorithm. Multispectral images were then processed with spatial wavelet decomposition, histogram enhancing, thresholds application, image fusion, false colors compositing and Principal Component Analysis (PCA) techniques. Software used have been GNU Image Manipulation Program (GIMP) and Mathworks MATLAB (which can be substituted for the processing steps proposed by the built-in functions of GNU OCTAVE open-source software). Processed images were able to highlight features on vault paintings revealing details of the surface or its very shallow layers which were impossible or very difficult to distinguish in raw data. In fact, they emphasized low-visible details, differences in apparently similar finishes or pigments, cracks and probably details of surface preparation.

Imaging Cultural Heritage at Different Scales: Part I, the Micro-Scale (Manufacts)

“…Sometimes, Multi Images Stacking algorithms [49][50][51] are used to improve the outline details related to the artifact contents or to the conditions of the observed objects. In the field of artwork investigation, Multispectral datasets in the form of multispectral cubes can be processed with common image processing and fusion techniques to detect subtle details in painting [53]. In the cited reference, the authors proposed a processing workflow including a 2D wavelet decomposition of spectral-NIR-images, a histogram enhancing their high frequency spatial components and image fusion (removing the lowest frequency in NIR) to the visible datasets.…”