Abstract: An imaging device includes at least a first group of pixels. A driver block is configured to generate at least two shutter signals, each having on-phases periodically alternating with off-phases. The shutter signals might not be in phase. The imaging device may have an optical shutter that is partitioned in two or more parts, or a set of two or more optical shutters. The shutter parts, or the shutters, may receive the shutter signals, and accordingly open and close. A design of the driver block requires reduced power, which is highly desirable for mobile applications. Moreover, 3D imaging may be implemented that uses various time-of-flight configurations.

Abstract: A Dynamic Vision Sensor (DVS) pose-estimation system includes a DVS, a transformation estimator, an inertial measurement unit (IMU) and a camera-pose estimator based on sensor fusion. The DVS detects DVS events and shapes frames based on a number of accumulated DVS events. The transformation estimator estimates a 3D transformation of the DVS camera based on an estimated depth and matches confidence-level values within a camera-projection model such that at least one of a plurality of DVS events detected during a first frame corresponds to a DVS event detected during a second subsequent frame. The IMU detects inertial movements of the DVS with respect to world coordinates between the first and second frames. The camera-pose estimator combines information from a change in a pose of the camera-projection model between the first frame and the second frame based on the estimated transformation and the detected inertial movements of the DVS.

Abstract: Pixels of an array capture values for an input image. The captured values correspond to pixel center points of the pixels that captured the values. Additional values about the input image may be further computed from the captured values. These additional values may correspond to additional center points, which can be different from any of the pixel center points. An output image may be constructed from the captured values plus the additional values. These values may be stored together and/or displayed together as the output image. Embodiments are applicable to images such as from multi-layer sensors. Since the output image can be created from a higher total number of values than those captured by the available number of pixels, such image processing can be called super-resolution, and can be applied to image processing within imaging devices, for still pictures, video and motion pictures, and so on.

Abstract: Exemplary embodiments for a biometric camera system for a mobile device, comprise: a near infrared (NIR) light source on the mobile device that flashes a user of the mobile device with near infrared light during image capture; a biometric camera located on the mobile device offset from the NIR light source, the biometric camera comprising: an extended depth of field (EDOF) imaging lens; a bandpass filter located adjacent to the EDOF imaging lens to reject ambient light during image capture; and an imaging sensor located adjacent the bandpass filter that converts an optical image of an object into an electronic signal for image processing; and a processor configured to receive video images of an iris of a user from the image sensor, and attempt to match the video images of the iris with previously registered images stored in an iris database, wherein if a match is found, the user is authenticated.

Abstract: A method and a system are disclosed that use a double-readout technique to generate timestamps and grayscale values for pixel-specific outputs of a pixel row in a pixel array in which the pixel array forms an image plane and the row of pixels forms an epipolar line of a scanning line on the image plane. For a pixel-specific output that exceeds a threshold, a timestamp value and a grayscale value are generated and associated with the pixel-specific output. If a pixel-specific output does not exceed the threshold and no timestamp is generated (i.e., a missing timestamp), a grayscale value for the pixel-specific output is generated and associated with the pixel-specific output. Timestamps errors may be corrected that may be caused by missing timestamps, timestamps that are associated with pixel clusters and outlier timestamps, i.e., pixel-specific outputs that are not consistent with a monotonic relationship of timestamp values under normal conditions.

Abstract: An embodiment includes a system, comprising: a buffer configured to store a plurality of events, each event including a plurality of bits; an output circuit configured to output events from the buffer; and a controller coupled to the buffer and the output circuit and configured to: cause the output circuit to output a first event from the buffer; and select a second event from the buffer to be output by the output circuit after the first event based on bits associated with the first event.

Abstract: Exemplary embodiments for a biometric camera system for a mobile device, comprise: a near infrared (NIR) light source on the mobile device that flashes a user of the mobile device with near infrared light during image capture; a biometric camera located on the mobile device offset from the NIR light source, the biometric camera comprising: an extended depth of field (EDOF) imaging lens; a bandpass filter located adjacent to the EDOF imaging lens to reject ambient light during image capture; and an imaging sensor located adjacent the bandpass filter that converts an optical image of an object into an electronic signal for image processing; and a processor configured to receive video images of an iris of a user from the image sensor, and attempt to match the video images of the iris with previously registered images stored in an iris database, wherein if a match is found, the user is authenticated.

Abstract: An apparatus and a method. The apparatus includes an image representation unit configured to receive a sequence of frames generated from events sensed by a dynamic vision sensor (DVS) and generate a confidence map from non-noise events; and an image denoising unit connected to the image representation unit and configured to denoise an image in a spatio-temporal domain. The method includes receiving, by an image representation unit, a sequence of frames generated from events sensed by a DVS, and generating a confidence map from non-noise events; and denoising, by an image denoising unit connected to the image representation unit, images formed from the frames in a spatio-temporal domain.

Abstract: The Time-of-Flight (TOF) technique is combined with analog amplitude modulation within each pixel in an image sensor. The pixel may be a two-tap pixel or a one-tap pixel. Two photoelectron receiver circuits in the pixel receive respective analog modulating signals. The distribution of the received photoelectron charge between these two circuits is controlled by the difference (or ratio) of the two analog modulating voltages. The differential signals generated in this manner within the pixel are modulated in time domain for TOF measurement. Thus, the TOF information is added to the received light signal by the analog domain-based single-ended to differential converter inside the pixel itself. The TOF-based measurement of range and its resolution are controllable by changing the duration of modulation. An autonomous navigation system with these features may provide improved vision for drivers under difficult driving conditions like low light, fog, bad weather, or strong ambient light.

Abstract: A method and a system are disclosed that use a double-readout technique to generate timestamps and grayscale values for pixel-specific outputs of a pixel row in a pixel array in which the pixel array forms an image plane and the row of pixels forms an epipolar line of a scanning line on the image plane. For a pixel-specific output that exceeds a threshold, a timestamp value and a grayscale value are generated and associated with the pixel-specific output. If a pixel-specific output does not exceed the threshold and no timestamp is generated (i.e., a missing timestamp), a grayscale value for the pixel-specific output is generated and associated with the pixel-specific output. Timestamps errors may be corrected that may be caused by missing timestamps, timestamps that are associated with pixel clusters and outlier timestamps, i.e., pixel-specific outputs that are not consistent with a monotonic relationship of timestamp values under normal conditions.

Abstract: An apparatus and a method. The apparatus includes an image representation unit configured to receive a sequence of frames generated from events sensed by a dynamic vision sensor (DVS) and generate a confidence map from non-noise events; and an image denoising unit connected to the image representation unit and configured to denoise an image in a spatio-temporal domain. The method includes receiving, by an image representation unit, a sequence of frames generated from events sensed by a DVS, and generating a confidence map from non-noise events; and denoising, by an image denoising unit connected to the image representation unit, images formed from the frames in a spatio-temporal domain.

Abstract: Using one or more patterned markers inside the projector module of a three-dimensional (3D) camera to facilitate automatic calibration of the camera's depth sensing operation. The 3D camera utilizes epipolar geometry-based imaging in conjunction with laser beam point-scans in a triangulation-based approach to depth measurements. A light-sensing element and one or more reflective markers inside the projector module facilitate periodic self-calibration of camera's depth sensing operation. To calibrate the camera, the markers are point-scanned using the laser beam and the reflected light is sensed using the light-sensing element. Based on the output of the light-sensing element, the laser's turn-on delay is adjusted to perfectly align a laser light spot with the corresponding reflective marker. Using reflective markers, the exact direction and speed of the scanning beam over time can be determined as well.

Abstract: A method for training a neural network to perform assessments of image quality is provided. The method includes: inputting into the neural network at least one set of images, each set including an image and at least one degraded version of the image; performing comparative ranking of each image in the at least one set of images; and training the neural network with the ranking information. A neural network and image signal processing tuning system are disclosed.

Abstract: An apparatus and a method. The apparatus includes a dynamic vision sensor (DVS) configured to generate a stream of events, where an event includes a location and a binary value indicating a positive or a negative change in luminance; a sampling unit connected to the DVS and configured to sample the stream of events; and an image formation unit connected to the sampling unit and configured to form an image for each sample of the stream of events, wherein a manner of sampling by the sampling unit is adjusted to reduce variations between images formed by the image formation unit.

Abstract: Ranging devices, systems, and methods are provided. In embodiments, a device includes a casing with four openings and an array with depth pixels. The depth pixels are arranged in four quadrants, so that pixels in each of the quadrants receive light through one of the four openings. The depth pixels may generate samples in response to the received light. For a certain frame, a controller reads out samples from each of the quadrants before completing reading out the samples of any one of the quadrants. In some embodiments, reading out is performed by using interleaved rolling shutter for the rows.

Abstract: Using improved Image Signal Processing (ISP) along with a multi-layer Color Filter Array (CFA) architecture to capture both the Red-Green-Blue (RGB) as well as the Red-X-Blue (RXB) images substantially simultaneously on the same Complementary Metal Oxide Semiconductor (CMOS) image sensor chip in a single shot so that subsequent image processing stage(s) can choose between RGB and RXB images to improve the quality of the final image. The color “X” in the RXB image may be a white color, a yellow color, or a cyan color. In contrast to the individual RWB or RGB imaging based conventional CMOS sensors, the disclosed CMOS sensor with one or more layers of specifically-selected CFAs can capture both the RGB and RXB images in a single shot using associated ISP. The multi-layer sensor may be an organic sensor or a stacked X3 sensor. The dual RGB-RXB imaging may reduce colorblindness, chromatic aberration, and saturation artifacts.

Abstract: An image signal processing (ISP) system is provided. The system includes a neural network trained by inputting a set of raw data images and a correlating set of desired quality output images; the neural network including an input for receiving input image data and providing processed output; wherein the processed output includes input image data that has been adjusted for at least one image quality attribute. A method and an imaging device are disclosed.

Abstract: An imaging apparatus may include an image sensor that includes a Bayer color filter array (CFA) of 2-by-2 cell groups each of which includes a red pixel, a blue pixel, and two green pixels, and an image signal processor for processing raw data from the Bayer CFA. The image signal processor corrects the raw data to reduce artifacts such as image contrast degradation caused by using green pixels with wide transmission spectrum.

Abstract: A method for enhancing at least one image within a series of images is provided. The method includes: selecting the series of images; upscaling each image within the series of images; selecting a reference image among the series of images; performing image registration to align series of images with the reference image; evaluating the series of aligned images for a subset of pixel locations that exhibit high cross-frame variation; performing learning processing to substantially reduce noise and exclude motion biases at the subset of pixel locations; performing pixel fusion from the series of aligned and processed images to produce the super-resolution reference image. A computer program product and an imaging system are disclosed.

Abstract: Using the same image sensor to capture a two-dimensional (2D) image and three-dimensional (3D) depth measurements for a 3D object. A laser point-scans the surface of the object with light spots, which are detected by a pixel array in the image sensor to generate the 3D depth profile of the object using triangulation. Each row of pixels in the pixel array forms an epipolar line of the corresponding laser scan line. Timestamping provides a correspondence between the pixel location of a captured light spot and the respective scan angle of the laser to remove any ambiguity in triangulation. An Analog-to-Digital Converter (ADC) in the image sensor operates as a Time-to-Digital Converter (TDC) to generate timestamps. When the epipolar line is misaligned or curved, multiple TDC arrays acquire timestamps of multiple pixels (in multiple rows) substantially simultaneously. Multiple timestamp values are reconciled to obtain a single timestamp value for a light spot.