In critical sectors such as aerospace, automotive manufacturing, and defense, material performance at high temperatures significantly influences stability and reliability. With advancing technology, there is an increasing need to measure the mechanical properties of materials under high-temperature conditions. Traditional high-temperature contact measurement techniques, such as strain gauges and laser extensometers, provide only localized deformation data, which is insufficient for applications requiring full-field deformation information. Consequently, digital image correlation (DIC) technology, known for its non-contact, full-field measurement capability, has gained prominence in high-temperature measurements. However, thermal radiation and disturbance inherent in high-temperature environments pose significant challenges, causing image overexposure, quality degradation, and calculation errors. Moreover, temperature gradients in non-vacuum environments can induce pixel drift and jitter, further reducing measurement accuracy. In this paper, we propose a high-temperature DIC measurement method combining the automatic color equalization (ACE) algorithm and image inverse filtering to address these issues. This approach significantly improves the accuracy of high-temperature DIC environments, offering practical value for material performance evaluation in extreme environments.

The research methodology consists of two main steps. First, the ACE algorithm is employed to address thermal radiation and haze-like phenomena in high-temperature environments. Based on Retinex theory, the algorithm adjusts pixel values by calculating the relative brightness and darkness of target pixels and their surrounding pixels, thus enhancing image contrast. The ACE algorithm operates in two stages. The first stage, color space adjustment, achieves color constancy and contrast enhancement through regional adaptive filtering and chromatic aberration correction. In the second stage, output range configuration, linear scaling is applied to stretch the pixel values of the intermediate results to the dynamic range of [0, 255], ensuring accurate tone mapping and luminance constancy. Next, image inverse filtering technology is utilized to mitigate the effects of thermal disturbance. This approach improves image quality and measurement accuracy by performing inverse filtering in the frequency domain to correct images degraded by thermal disturbances. The principle involves counteracting refractive index variations caused by inhomogeneous thermal flow field, which result from temperature gradients in high-temperature environments and distort the light propagation path. In this paper, a frequency-limiting filtering method is employed to enhance the process. By reducing the filter radius and minimizing zero-value occurrences, the method effectively improves image quality and the precision of DIC measurements. Finally, the proposed method’s effectiveness is validated through experiments on image dehazing and thermal disturbance elimination conducted at 1000 ℃.

Experimental results demonstrate that the proposed high-temperature DIC measurement method, based on the ACE algorithm and image inverse filtering technology, can effectively produce high-contrast, clear speckle patterns under extreme conditions of 1000 ℃. In the image dehazing experiments, the ACE algorithm significantly suppresses background light and thermal haze, improving image contrast and making speckle features more distinct (Fig. 8). In both static and dynamic thermal disturbance experiments, images processed with inverse filtering show a smoother displacement gradient and notably reduced displacement values, effectively mitigating errors caused by thermal disturbance (Fig. 10). Particularly in dynamic experiments, the displacement results after inverse filtering closely align with theoretical true values, demonstrating higher accuracy. In contrast, displacement curves without inverse filtering fluctuate around the true value, indicating substantial measurement errors. These findings confirm that the proposed method can not only deliver high-quality measured images but also achieve high-precision measurements, with full-field displacement measurement errors controlled to within 5% (Fig. 12).

The high-temperature DIC measurement method, combining the ACE algorithm and image inverse filtering technology, offers an innovative solution for specimen imaging and thermal disturbance elimination in high-temperature environments. This software-based method effectively mitigates the effects of thermal radiation and disturbances, significantly enhancing the accuracy of high-temperature DIC measurements. Compared to traditional methods, this technique eliminates reliance on costly optical hardware or vacuum environments, making it both practical and economical. Experimental validation at 1000 ℃ confirms its capability to produce clear images and perform high-precision displacement field calculations. This advancement provides robust technical support for studying high-temperature material properties. In conclusion, this research not only improves the accuracy of high-temperature DIC measurement technology but also broadens its application scope in high-temperature measurements, offering substantial value for advancing industrial and scientific research fields.