Accurate estimation of camera response function for high dynamic range measurement

Li, Ji; Guan, Jingtian; Wang, Yukun; Chen, Xiaobo; Xi, Juntong

doi:10.1364/ao.440744

Cited by 7 publications

(2 citation statements)

References 28 publications

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“…In the camera imaging process, CRF converts camera exposure values into image pixel intensities. In this work, an estimation method [36] is applied to obtain the CRF. The intensities of pixels in the captured image can be expressed as…”

Section: Determination Of Exposure Time Rangementioning

confidence: 99%

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Adaptive optimal exposure selection based on time cost function for 3D reconstruction of high dynamic range surfaces

Li,

Guan,

Chen

et al. 2023

Meas. Sci. Technol.

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High dynamic range surfaces are prone to overexposure and underexposure in the camera imaging process, which poses a challenging issue for 3D reconstruction. Capturing multiple images of high dynamic range surfaces at different exposure times is widely used for 3D reconstruction, and the exposure sequence can significantly affect reconstruction performance. However, most existing methods select the exposure sequence based on the overall performance of the image or groups of image pixels, without considering individual pixels in the image. To circumvent the problem, this paper presents the adaptive optimal exposure sequence selection based on time cost function for the 3D reconstruction of high dynamic range surfaces. Different from existing methods that use the overall performance, the acceptable exposure time range for each pixel in the image is determined independently. Furthermore, the time cost function is established to evaluate the priority of each exposure time and used to select the optimal exposure sequence iteratively. Experimental results verify both the reconstruction performance and suitability of the proposed method.

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Section: Determination Of Exposure Time Rangementioning

confidence: 99%

“…where T can be empirically set to 0.1 (according to [36]). l max is the maximum accepted exposure value.…”

Section: Determination Of Exposure Time Rangementioning

confidence: 99%

Adaptive optimal exposure selection based on time cost function for 3D reconstruction of high dynamic range surfaces

Li,

Guan,

Chen

et al. 2023

Meas. Sci. Technol.

Self Cite

View full text Add to dashboard Cite

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Recent Progress of Full-Field Three-Dimensional Shape Measurement Based on Phase Information

Bai,

Zhang,

et al. 2024

Nanomanuf Metrol

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Full-field three-dimensional (3D) measurement technology based on phase information has become an indispensable part of geometric dimension measurement in modern scientific research and engineering applications. This field has been developing and evolving for the study of highly reflective phenomena, diffuse reflections, and specular surfaces, and many novel methods have emerged to increase the speed of measurements, enhance data accuracy, and broaden the robustness of the system. Herein, we will discuss the latest research progress in full-field 3D shape measurement based on phase information systematically and comprehensively. First, the fundamentals of 3D shape measurement based on phase information are introduced, namely, phase-shifting and transform-based methods. Second, recent technological innovations are highlighted, including increases in measurement speed and automation and improvements in robustness in complex environments. In particular, the challenges faced by these technological advances in solving highly dynamic, composite surface measurement problems are presented, i.e., with multiexposure techniques proposed for high dynamics that extend the dynamic range of the camera to reduce the effects of overexposure but increase the cost of time and have high hardware requirements, fringe adaptive techniques that overcome light variations but are computationally complex, and multipolarized camera techniques that reduce the effects of light variations but are sensitive to the light source. Third, the phase-shifting method combined with coding is proposed to improve the measurement speed, but the accuracy is slightly reduced. Deep learning techniques are proposed to cope with measurements in complex environments, but the dataset computation process is cumbersome. Finally, future research directions are suggested, and the challenges are presented. Overall, this work provides a reference for researchers and engineers.

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Exposure Map Fusion for Precise 3-D Reconstruction of High Dynamic Range Surfaces

Guan

Chen

et al. 2022

IEEE Trans. Instrum. Meas.

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Accurate estimation of camera response function for high dynamic range measurement

Cited by 7 publications

References 28 publications

Adaptive optimal exposure selection based on time cost function for 3D reconstruction of high dynamic range surfaces

Adaptive optimal exposure selection based on time cost function for 3D reconstruction of high dynamic range surfaces

Recent Progress of Full-Field Three-Dimensional Shape Measurement Based on Phase Information

Exposure Map Fusion for Precise 3-D Reconstruction of High Dynamic Range Surfaces

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