Color three-dimensional (3D) displays have always been the ideal display method because of their strong sense of reality, whereas color 3D displays of monochrome scenes are still challenging and unexplored. A color stereo reconstruction algorithm (CSRA) is proposed to solve the issue. We design a deep learning-based color stereo estimation (CSE) network to obtain color 3D information of monochrome scenes. The vivid color 3D visual effect is verified by our self-made display system. Furthermore, an efficient CSRA-based 3D image encryption scheme is achieved by encrypting a monochrome image with two-dimensional double cellular automata (2D-DCA). The proposed encryption scheme fulfills the requirement for real-time and high-security 3D image encryption with a large key space and the parallel processing capability of 2D-DCA.
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http://dx.doi.org/10.1364/OL.484461 | DOI Listing |
IEEE Trans Pattern Anal Mach Intell
December 2024
Accurately capturing dynamic scenes with wide-ranging motion and light intensity is crucial for many vision applications. However, acquiring high-speed high dynamic range (HDR) video is challenging because the camera's frame rate restricts its dynamic range. Existing methods sacrifice speed to acquire multi-exposure frames.
View Article and Find Full Text PDFSensors (Basel)
May 2024
State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
The emergence of polarization image sensors presents both opportunities and challenges for real-time full-polarization reconstruction in scene imaging. This paper presents an innovative three-stage interpolation method specifically tailored for monochrome polarization image demosaicking, emphasizing both precision and processing speed. The method introduces a novel linear interpolation model based on polarization channel difference priors in the initial two stages.
View Article and Find Full Text PDFColor three-dimensional (3D) displays have always been the ideal display method because of their strong sense of reality, whereas color 3D displays of monochrome scenes are still challenging and unexplored. A color stereo reconstruction algorithm (CSRA) is proposed to solve the issue. We design a deep learning-based color stereo estimation (CSE) network to obtain color 3D information of monochrome scenes.
View Article and Find Full Text PDFThe optimization of trichromatic white light emitting diodes (LEDs) spectrum for application scenes related to the age of lighting users is proposed and demonstrated. Based on the spectral transmissivity of human eyes at different ages, the visual and non-visual responses of human eyes to different wavelengths of light, we have built the blue light hazards (BLH) and circadian action factor (CAF) related to the age of the lighting user. The BLH and CAF are used to evaluate the spectral combinations of high color rendering index (CRI) white LEDs obtained from different radiation flux ratios of red, green, and blue monochrome spectrum.
View Article and Find Full Text PDFWe introduce end-to-end inverse design for multi-channel imaging, in which a nanophotonic frontend is optimized in conjunction with an image-processing backend to extract depth, spectral and polarization channels from a single monochrome image. Unlike diffractive optics, we show that subwavelength-scale "metasurface" designs can easily distinguish similar wavelength and polarization inputs. The proposed technique integrates a single-layer metasurface frontend with an efficient Tikhonov reconstruction backend, without any additional optics except a grayscale sensor.
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