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Enhanced DI Correlation Using WHWC Model Spanning the Visible and Near-Infrared Spectrum
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DOI：10.4025/actascitechnol.v48i1.73644.png)
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Abstract
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Digital Image Correlation (DIC) is an advanced technique used for precise measurement of deformations, displacements, and strains on material surfaces through the analysis of digital images taken before and after loading. This paper introduces an alternative approach to DIC that integrates the Windowed Harmonic Weighted Correlation (WHWC) model, designed to improve accuracy and stability in the analysis of spectral images within the visible and near-infrared (NIR) spectrum. The WHWC model incorporates harmonic weighting and sinusoidal factors to enhance sensitivity to local changes, reduce the influence of noise, and maintain robustness across wavelengths ranging from 446 nm to 765 nm, covering both visible and NIR regions. Through experimental comparison with the Normalized Cross-Correlation (NCC) method, the WHWC model demonstrates significant improvements in stability and precision, achieving a correlation accuracy increase of 23% to 31%. The model was rigorously tested on a dataset of 600 spectral images, with results presented mathematically, visually, and descriptively, underscoring WHWC's capability for precise material analysis and reliable detection of subtle variations. These qualities position WHWC as a valuable tool in fields such as material science and biomedical imaging, where consistent, high-accuracy measurements are critical for structural analysis, environmental monitoring, and diagnostic imaging.
Keywords:
Digital image processing
digital image correlation
visible spectrum
image quality evaluation
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