Dr. Yingbo Wang Profile

Dr. Yingbo Wang

at Beijing Institute of Technology

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Publications (3)

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Proceedings Article | 12 March 2021 Paper

Underwater image restoration based on improved dark channel prior

Yingbo Wang, Jie Cao, Mingyuan Tang, Guoliang Li, Qun Hao, Yami Fang

Proceedings Volume 11763, 117633P (2021) https://doi.org/10.1117/12.2586656

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Underwater image restoration has attracted the attention of many experts due to the demand of underwater rescue, archaeology, resource exploration et al. Water scattering and absorption hinder the linear propagation of light in water, resulting the image degradation. The degraded image visibility can be improved by the image restoration method. Many image restoration methods have been proposed by the experts for underwater images restoration. The dark channel prior method is a classical method for image dehazing, and it also can be used for underwater image restoration. However, the underwater image restored by this method still has the color distortion problem due to the water absorption, and the less visibility due to the inaccuracy transmission estimation. To overcome this problems, we propose an image restoration method based on improved dark channel prior to repair the image degraded by underwater scattering media. The quadtree decomposition is used to find the high intensity region for waterlight estimation. The transmission is estimated by the improved dark channel prior. The underwater degraded image can be restored by our proposed method without color distortion. This method will be helpful to the underwater rescue and resource exploration et al.

Proceedings Article | 5 November 2020 Paper

Degraded image restoration based on quadtree decomposition in scattering media

Yingbo Wang, Jie Cao, Chengqiang Xu, Chenyu Xu, Qun Hao

Proceedings Volume 11566, 1156605 (2020) https://doi.org/10.1117/12.2574335

KEYWORDS: Image restoration, Scattering media, Atmospheric modeling, Image transmission, Image enhancement, Distortion, Scattering, Image segmentation, Image processing, Visualization

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Image restoration has attracted the attention of many scientists due to the image is degraded by the bad weather (such as haze, smog, fog). Clear images provide a means for security surveillance, remote sensing and various military application to understand objective facts. Many dehaze methods have been proposed by the experts for image restoration, especially for image dehaze. The dark channel prior dehaze method is a typical image restoration method based on atmospheric physical model. This method is a kind of statistics of outdoor haze-free images, and it is a simple but effective remove haze from a single input image. However, this method fails to restore the sky region of degraded image, and it has a high computational cost associated with soft matting algorithm. To overcome these problems, we propose an image restoration method based on quadtree decomposition to restore the images degraded by scattering media. The proposed method uses the quadtree decomposition to find the sky region for the atmospheric light estimation. The transmission of sky region is improved by the proposed method to obtain an accurate global transmission of degraded image. The degraded image can be quickly restored by our proposed method without halo effect or color distortion. The proposed method will be helpful to the security surveillance, remote sensing and various military application et al.

Proceedings Article | 12 March 2020 Paper

Noninvasive object imaging with single-shot low-resolution speckle pattern through strongly-scattering turbid layers

Yingbo Wang, Jie Cao, Qun Hao, Chengqiang Xu, Mingyuan Tang

Proceedings Volume 11438, 114380C (2020) https://doi.org/10.1117/12.2542166

KEYWORDS: Speckle pattern, Gaussian filters, Signal to noise ratio, Biomedical optics, Cameras, Speckle

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Noninvasive object imaging through strongly-scattering turbid layers has attracted the attention of many experts due to the potential application in the biomedical imaging and bioscience. The traditional speckle correlation method with Gerchberg-Saxton (GS) algorithm is used to restore object in a single-shot speckle pattern. However, this method suffers from the problems of convergence to local minimums, many iterations and cannot determine the object direction, due to the randomly assign initial value to GS algorithm. Bispectrum analysis method enables the directional Fourier phase retrieved using single-shot speckle pattern, but there are the problems of requiring high-resolution speckle pattern, low SNR and selecting the size of filter window. Therefore, we report an effective noninvasive imaging method through strongly-scattering turbid layers on the basis of bispectrum analysis and GS algorithm to restore the object in a lowresolution speckle pattern. Meanwhile, the new expression of Gaussian filter function is introduced contribute to determine the window size of filter in the processes of bispectrum analysis. In this proposed approach, the window size of filter is determined by the adjust factor according to the new form of Gaussian filter function, and the initial Fourier phase with directional information is generated by bispectrum analysis in a low-resolution speckle pattern. Then the initial Fourier phase is used as the randomly assign initial value to retrieve Fourier phase of object. Hence, the proposed method required no high-resolution, multiple iterations, nor randomly assign initial values to restore directional object. This work carries out simulations and experiments to demonstrates noninvasive object imaging in the low-resolution speckle pattern through strongly-scattering turbid layers.

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