Abstract: Devices, methods, and systems are provided. In one example, a device is described to include a device interface that receives data from at least one data source; a data shuffle unit that collects the data received from the at least one data source, receives a descriptor that describes a data shuffle operation to perform on the data received from the at least one data source, performs the data shuffle operation on the collected data to produce shuffled data, and provides the shuffled data to at least one data target.

Abstract: Devices, methods, and systems are provided. In one example, a device is described to include a device interface that receives data from at least one data source; a data shuffle unit that collects the data received from the at least one data source, receives a descriptor that describes a data shuffle operation to perform on the data received from the at least one data source, performs the data shuffle operation on the collected data to produce shuffled data, and provides the shuffled data to at least one data target.

Abstract: Apparatuses, systems, and techniques to optimize memory usage when performing matrix operations. In at least one embodiment, a matrix is optimized to limit memory and storage requirements while minimizing loss of precision for a sum of the members of the matrix.

Abstract: Devices, methods, and systems are provided. In one example, a device is described to include a device interface that receives data from at least one data source; a data shuffle unit that collects the data received from the at least one data source, receives a descriptor that describes a data shuffle operation to perform on the data received from the at least one data source, performs the data shuffle operation on the collected data to produce shuffled data, and provides the shuffled data to at least one data target.

Abstract: Apparatuses, systems, and techniques to optimize memory usage when performing matrix operations. In at least one embodiment, a matrix is optimized to limit memory and storage requirements while minimizing loss of precision for a sum of the members of the matrix.

Abstract: Devices, methods, and systems are provided. In one example, a device is described to include a device interface that receives data from at least one data source; a data shuffle unit that collects the data received from the at least one data source, receives a descriptor that describes a data shuffle operation to perform on the data received from the at least one data source, performs the data shuffle operation on the collected data to produce shuffled data, and provides the shuffled data to at least one data target.

Abstract: Apparatuses, systems, and techniques to optimize memory usage when performing matrix operations. In at least one embodiment, a matrix is optimized to limit memory and storage requirements while minimizing loss of precision for a sum of the members of the matrix.

Abstract: Systems and techniques for noise reduction in video are described. Example implementations provide improved motion-adaptive temporal or spatio-temporal noise reduction that use an improved blending of the current frame with previous frames. The improved blending may be particularly effective for processing video captured in noisy environments such as low-light and/or mobile environments. In some example implementations, the improved blending is based on more accurately distinguishing between pixel difference in adjacent images that are caused by motion rather than noise.

Abstract: Systems and techniques for noise reduction in video are described. Example implementations provide improved motion-adaptive temporal or spatio-temporal noise reduction that use an improved blending of the current frame with previous frames. The improved blending may be particularly effective for processing video captured in noisy environments such as low-light and/or mobile environments. In some example implementations, the improved blending is based on more accurately distinguishing between pixel difference in adjacent images that are caused by motion rather than noise.

Abstract: Systems and methods for generating high dynamic images from interleaved Bayer array data with high spatial resolution and reduced sampling artifacts. Bayer array data are demosaiced into components of the YUV color space before deinterleaving. The Y component and the UV components can be derived from the Bayer array data through demosiac convolution processes. A respective convolution is performed between a convolution kernel and a set of adjacent pixels of the Bayer array that are in the same color channel. A convolution kernel is selected based the mosaic pattern of the Bayer array and the color channels of the set of adjacent pixels. The Y data and UV data are deinterleaved and interpolated into frames of short exposure and long exposures in the second color space. The short exposure and long exposure frames are then blended and converted back to a RGB frame representing a high dynamic range image.

Abstract: Systems and methods for generating high dynamic images from interleaved Bayer array data with high spatial resolution and reduced sampling artifacts. Bayer array data are demosaiced into components of the YUV color space before deinterleaving. The Y component and the UV components can be derived from the Bayer array data through demosiac convolution processes. A respective convolution is performed between a convolution kernel and a set of adjacent pixels of the Bayer array that are in the same color channel. A convolution kernel is selected based the mosaic pattern of the Bayer array and the color channels of the set of adjacent pixels. The Y data and UV data are deinterleaved and interpolated into frames of short exposure and long exposures in the second color space. The short exposure and long exposure frames are then blended and converted back to a RGB frame representing a high dynamic range image.

Abstract: In an apparatus according to one embodiment of the present invention, a video system is disclosed. The video system comprises a pre-processing module, an auto-exposure module, and an image sensor. The image sensor is operable to simultaneously capture a first image at a long exposure and a second image at a short exposure capture. The auto-exposure module is operable to determine an average brightness of a scene for video/image capturing, wherein the determined brightness achieves a desired image quality. The auto-exposure module is further operable to select a dynamic range necessary to preserve desired details in a captured scene. The auto-exposure module is further operable to instruct the image sensor to capture the first image and the second image with a selected exposure ratio to achieve the desired dynamic range. The pre-processing module is operable to combine the first image and the second image into a final image with the desired dynamic range.

Abstract: A lens system for collecting and focusing light emanating from an object comprises: a cuvette housing the object and having a wall of thickness not greater than 1.5 millimeters; a plano-convex lens having a planar surface affixed to the wall; a sequence of at least three meniscus lenses, each meniscus lens having a concave surface toward the object and a convex surface, each successive meniscus lens receiving the light from the immediately preceding meniscus lens and having radii of curvature of its concave and convex surfaces greater than corresponding radii of the preceding meniscus lens; and at least one compound lens chosen from the group consisting of a doublet lens and a triplet lens, the compound lens receiving the light from a last meniscus lens, wherein an image of a geometrical point on the object has a root-mean square spot size equal to or less than 63 ?m.