November 2022
Spotlight Summary by Manuel MartÃnez-Corral
Enhancement of three-dimensional image visualization under photon-starved conditions
Three-dimensional (3D) imaging in low-light conditions has been a challenge for many applications, such as medical imaging, autonomous unmanned vehicles, or defense. To obtain those images, the photon counting integral image was introduced, which can be modeled by the Poisson distribution and using volumetric computational reconstruction with statistical estimation. However, it may not reconstruct good-quality 3D images under photon-starved conditions.
To overcome this drawback, the authors of this publication propose a preprocessing technique consisting of contrast-limited adaptive histogram equalization (CLAHE) and histogram matching. This enhances the visual quality of 3D images in photon-starved conditions. The utility of the proposed method is demonstrated by computer simulations and by optical experiments. The results are impressive and inspiring. Therefore, the authors prove that the proposed method can provide accurate 3D information under severely photon-starved conditions.
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To overcome this drawback, the authors of this publication propose a preprocessing technique consisting of contrast-limited adaptive histogram equalization (CLAHE) and histogram matching. This enhances the visual quality of 3D images in photon-starved conditions. The utility of the proposed method is demonstrated by computer simulations and by optical experiments. The results are impressive and inspiring. Therefore, the authors prove that the proposed method can provide accurate 3D information under severely photon-starved conditions.
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Article Information
Enhancement of three-dimensional image visualization under photon-starved conditions
Jiheon Lee and Myungjin Cho
Appl. Opt. 61(21) 6374-6382 (2022) View: HTML | PDF