Abstract: Presented herein are systems and methods for an end-to-end solution for object removal from a video using adaptive learning. In one or more embodiments, using a pre-trained image inpainting model, in-scene training data may be generated using optical-flow guided sampling. In one or more embodiments, the sampled patches are used to generate a training dataset, which is used to further train the image inpainting model until reaching a stop condition. The adaptively trained inpainting model may be used to generate a modified video in which the desired object or objects have been removed and the corresponding removed portion(s) have been filled (or inpainted) to preserve the integrity of the image.

Abstract: Presented herein are embodiments of systems and methods for training a system and using a trained system to generate super-resolution imagery from low-resolution imagery. Embodiments for generating super-resolution imagery from low-resolution imagery include obtaining an input trade-off parameter that indicates a preference regarding low distortion or high perceptual quality for a generated SR image and obtaining a latent variable from a distribution defined, at least in part, by a trade-off parameter. Embodiments include inputting an LR image and the latent variable into an embodiment of an invertible rescaling network (IRNN) in an inverse upscaling direction of the IRNN to generate an output SR image that comprises accuracy and perception qualities conditioned by the input trade-off parameter.

Abstract: A preparation method for a concrete additive for a maritime work environment includes: S1, compounding a volcanic ash material containing aluminum oxide and lime in proportion, loading a mixture into a sugar coating machine, and spraying a proper amount of alcohol, to prepare spherical particles; S2, adding the spherical particles in S1 and cement into the sugar coating machine, uniformly spraying deionized water in a rotating process, and coating surface layers of the spherical particles with a layer of cement for maintenance; and S3, placing the maintained particles in S2 into a hydrophobic emulsion, and coating the surface layers of the particles with a layer of hydrophobic emulsion, to obtain a concrete additive.

Abstract: Described herein are embodiments of a deep residual network dedicated to color filter array mosaic patterns. A mosaic stride convolution layer is introduced to match the mosaic pattern of a multispectral filter arrays (MSFA) or a color filter array raw image. Embodiments of a data augmentation using MSFA shifting and dynamic noise are applied to make the model robust to different noise levels. Embodiments of network optimization criteria may be created by using the noise standard deviation to normalize the L1 loss function. Comprehensive experiments demonstrate that embodiments of the disclosed deep residual network outperform the state-of-the-art denoising algorithms in MSFA field.

Abstract: According to one embodiment, a method is provided for video repainting performed by at least one processor of a computer device. The method includes receiving a video sequence having one or more image frames; detecting presences of a target object within the one or more image frames and determining pose condition and style shift of the detected objects; generating content representing a replacement object for the one or more image frames by applying the corresponding pose condition and style shift to the replacement object; and repainting the detected target object in the one or more image frames with the generated content.

Abstract: A preparation method for a concrete additive for a maritime work environment includes: S1, compounding a volcanic ash material containing aluminum oxide and lime in proportion, loading a mixture into a sugar coating machine, and spraying a proper amount of alcohol, to prepare spherical particles; S2, adding the spherical particles in S1 and cement into the sugar coating machine, uniformly spraying deionized water in a rotating process, and coating surface layers of the spherical particles with a layer of cement for maintenance; and S3, placing the maintained particles in S2 into a hydrophobic emulsion, and coating the surface layers of the particles with a layer of hydrophobic emulsion, to obtain a concrete additive.

Abstract: Described herein are systems and embodiments for multispectral image demosaicking using deep panchromatic image guided residual interpolation. Embodiments of a ResNet-based deep learning model are disclosed to reconstruct the full-resolution panchromatic image from multispectral filter array (MSFA) mosaic image. In one or more embodiments, the reconstructed deep panchromatic image (DPI) is deployed as the guide to recover the full-resolution multispectral image using a two-pass guided residual interpolation methodology. Experiment results demonstrate that the disclosed method embodiments outperform some state-of-the-art conventional and deep learning demosaicking methods both qualitatively and quantitatively.

Abstract: Presented herein are systems and methods for an end-to-end solution for object removal from a video using adaptive learning. In one or more embodiments, using a pre-trained image inpainting models, in-scene training data may be generated using optical-flow guided sampling. In one or more embodiments, the sampled patches are used to generate a training dataset, which is used to further train the image inpainting model until reaching a stop condition. The adaptively trained inpainting model may be used to generate a modified video in which the desired object or objects have been removed and the corresponding removed portion(s) have been filled (or inpainted) to preserve the integrity of the image.

Abstract: Network architecture search (NAS) received a lot of attention. The supernet-based differentiable approach is popular because it can effectively share the weights and lead to more efficient search. However, the mismatch between the architecture and weights caused by weight sharing still exists. Moreover, the coupling effects among different operators are also neglected. To alleviate these problems, embodiments of an effective NAS methodology by similarity-based operator ranking are presented herein. With the aim of approximating each layer's output in the supernet, a similarity-based operator ranking based on statistical random comparison is used. In one or more embodiments, then the operator that possibly causes the least change to feature distribution discrepancy is pruned. In one or more embodiments, a fair sampling process may be used to mitigate the operators' Matthew effect that happened frequently in previous supernet approaches.

Abstract: Described herein are embodiments of a deep residual network dedicated to color filter array mosaic patterns. A mosaic stride convolution layer is introduced to match the mosaic pattern of a multispectral filter arrays (MSFA) or a color filter array raw image. Embodiments of a data augmentation using MSFA shifting and dynamic noise are applied to make the model robust to different noise levels. Embodiments of network optimization criteria may be created by using the noise standard deviation to normalize the L1 loss function. Comprehensive experiments demonstrate that embodiments of the disclosed deep residual network outperform the state-of-the-art denoising algorithms in MSFA field.

Abstract: Described herein are systems and embodiments for multispectral image demosaicking using deep panchromatic image guided residual interpolation. Embodiments of a ResNet-based deep learning model are disclosed to reconstruct the full-resolution panchromatic image from multispectral filter array (MSFA) mosaic image. In one or more embodiments, the reconstructed deep panchromatic image (DPI) is deployed as the guide to recover the full-resolution multispectral image using a two-pass guided residual interpolation methodology. Experiment results demonstrate that the disclosed method embodiments outperform some state-of-the-art conventional and deep learning demosaicking methods both qualitatively and quantitatively.

Abstract: Under one aspect, a method of displaying medical information about a subject having a plurality of regions includes: resolving light obtained from each region of the plurality of regions into a corresponding spectrum; selecting a portion of each spectrum, the selected portion including medical information about the corresponding region; constructing an image based on the selected portion of each spectrum; and projecting the image onto the subject. Under another aspect, a method of displaying medical information about a subject that has a plurality of regions includes: resolving light obtained from each region of the plurality of regions into a corresponding spectrum; selecting a portion of each spectrum, the selected portion including medical information about the corresponding region; constructing a spectral image based on the selected portion of each spectrum; displaying an image of the plurality of regions; and displaying the spectral image overlying the image of the plurality of regions.

Abstract: Provided are systems and methods for imaging with compensation functions. An imaging device comprises a plurality of light source sets, of which two or more light source sets emit light of a same specific spectral range to compensate intensity differences among different spectral ranges. The imaging device can be integrated with a mobile device. A method comprises a subtraction procedure to compensate ambient light effect, a normalization procedure to compensate incidence angle effect, a 3D reconstruction procedure to compensate distance effect, or any combination of these procedures. The method is performed at an imaging device comprising a controller. At least one program is non-transiently stored in the controller and executable by the controller.

Abstract: Provided are systems and methods for imaging with compensation functions. An imaging device comprises a plurality of light source sets, of which two or more light source sets emit light of a same specific spectral range to compensate intensity differences among different spectral ranges. The imaging device can be integrated with a mobile device. A method comprises a subtraction procedure to compensate ambient light effect, a normalization procedure to compensate incidence angle effect, a 3D reconstruction procedure to compensate distance effect, or any combination of these procedures. The method is performed at an imaging device comprising a controller. At least one program is non-transiently stored in the controller and executable by the controller.

Abstract: An apparatus for analyzing a subject including a hyperspectral image module is provided. It is used to identify a suspect region of a subject by using a hyperspectral sensor (for obtaining a hyperspectral image of the subject), a control computer including a processor unit (PU) and a computer readable memory (CRM) (for controlling and is in electronic communication with the sensor), a control software module including instructions stored in the CRM and executed by the PU (for controlling said at least one operating parameter of the sensor), a spectral calibrator module including instructions stored in the CRM and executed by the PU (for applying a wavelength dependent spectral calibration standard constructed for the sensor to a hyperspectral image), and a light source for illuminating the subject. An optional contact probe module is used to collect a signal of the suspect region for medical diagnosis.

Abstract: An apparatus for analyzing a subject including a hyperspectral image module is provided. It is used to identify a suspect region of a subject by using a hyperspectral sensor (for obtaining a hyperspectral image of the subject), a control computer including a processor unit (PU) and a computer readable memory (CRM) (for controlling and is in electronic communication with the sensor), a control software module including instructions stored in the CRM and executed by the PU (for controlling said at least one operating parameter of the sensor), a spectral calibrator module including instructions stored in the CRM and executed by the PU (for applying a wavelength dependent spectral calibration standard constructed for the sensor to a hyperspectral image), and a light source for illuminating the subject. An optional contact probe module is used to collect a signal of the suspect region for medical diagnosis.

Abstract: Systems and methods for imaging using a plurality of light sources is provided. An imaging device comprises a housing, a lens within the housing, a plurality of light source sets attached or integrated into the housing, a two-dimensional pixelated detector within the housing in optical communication with the lens, memory and a controller. Each respective light source set comprises a plurality of lights uniformly radially distributed about the lens. A first light source set in the plurality sets emits light substantially limited to a first spectral range. A second light source set in the plurality of sets emits light substantially limited to a second spectral range other than the first range. At least one program non-transiently stored in the memory and executable by the controller sequentially and independently fired each light source set while collecting light using the pixelated detector. An imaging device can be integrated with a mobile device.

Abstract: Under one aspect, a method of displaying medical information about a subject having a plurality of regions includes: resolving light obtained from each region of the plurality of regions into a corresponding spectrum; selecting a portion of each spectrum, the selected portion including medical information about the corresponding region; constructing an image based on the selected portion of each spectrum; and projecting the image onto the subject. Under another aspect, a method of displaying medical information about a subject that has a plurality of regions includes: resolving light obtained from each region of the plurality of regions into a corresponding spectrum; selecting a portion of each spectrum, the selected portion including medical information about the corresponding region; constructing a spectral image based on the selected portion of each spectrum; displaying an image of the plurality of regions; and displaying the spectral image overlying the image of the plurality of regions.

Abstract: Systems and methods for imaging using a plurality of light sources is provided. An imaging device comprises a housing, a lens within the housing, a plurality of light source sets attached or integrated into the housing, a two-dimensional pixelated detector within the housing in optical communication with the lens, memory and a controller. Each respective light source set comprises a plurality of lights uniformly radially distributed about the lens. A first light source set in the plurality sets emits light substantially limited to a first spectral range. A second light source set in the plurality of sets emits light substantially limited to a second spectral range other than the first range. At least one program non-transiently stored in the memory and executable by the controller sequentially and independently fired each light source set while collecting light using the pixelated detector. An imaging device can be integrated with a mobile device.

Abstract: A method for capturing and consolidating multi-spectral image data for regions of interest using one or more spectral boost mechanisms or techniques is disclosed. A first multi-spectral or hyperspectral workflow comprising time-stamped two-dimensional pixelated images of a region of interest is obtained by a first computer-enabled imaging device. Each of the images corresponds to image data captured for a respective frequency band of a plurality of frequency bands. First meta data is associated with the images of the first workflow and includes: a plurality of first positions and first orientations of the first imaging device indicating first positional and orientation data for the first imaging device, and indications of a respective frequency band for each of the images of the first workflow. A consolidated multi-spectral workflow for the region of interest is generated, which includes spectrally and spatially consolidating the images of the first workflow using the first meta data.