Single-pixel imaging (SPI) is a novel imaging method, which can reconstruct the object information by a single-pixel detector with no spatial resolution. However, at present, the field of view (FOV) of SPI is limited to the illumination range of the projected patterns; thus, this technology cannot meet the imaging requirements of a large FOV or even 360° view in many vision-based fields. Therefore, in order to extend the illumination range of the projected pattern, as well as the FOV of SPI, here, we design an omnidirectional single-pixel imaging system (OSPIS) by adding a curved mirror, which can illuminate scenes with a 360° omnidirectional FOV. And, a retina-like annular pattern with log-polar structure is designed to match the geometry of the curved mirror. Further, to obtain the panoramic single-pixel images that are adapted to the human vision system, combing the imaging feature of SPI, an unwrapping-free Fourier panoramic singlepixel imaging (FFPSI) is proposed to remove the unwrapping process from the reconstructed omnidirectional images. The proposed FFPSI provides a new way for the application of SPI with large FOV, especially for real-time panoramic SPI.
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.
A bio-inspired Lidar imaging method with a non-uniform curved linear array receiving system is proposed. The receiving system is composed of a curved surface, a microlens array, an aperture array, and an avalanche-photodiode (APD) array. The microlens array and APD array are placed on a curved surface to mimic the large field of view (FOV) feature of the compound eye. The location distribution of the microlens array and APD array on the curved surface is non-uniform to mimic the retina-like property of the human eye. An experimental prototype, which consists of 12 microlenses and APD detectors is built and the effectiveness of the proposed approach has been validated by experiments. The results show that the whole FOV of the proposed system is 25.8° and it has a higher resolution in the central FOV and the lower resolution in the peripheral FOV. Moreover, the results show that the proposed Lidar imaging system has the rotation and scaling invariance property. This method is beneficial for developing a Lidar system with large FOV and high imaging efficiency.
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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