Qualcomm Incorporated

Pradeep Kumar Veeramalla

Soman Ganesh Nikhara

Bapineedu Chowdary Gummadi

Ravi Shankar Kadambala

Edwin Chongwoo Park

Xiaoyun Jiang

Jiafu Luo

Micha Galor Gluskin

Shizhong Liu

Weiliang Liu

Shang-Chih Chuang

Ho Sang Lee

Wenbin Wang

Narayana Karthik Ravirala

Loic Francois Segapelli

Ron Gaizman

Nan Cui

Kyuseo Han

Wei Zou

Srinath Anekere Narayan

Ankita Anil Kumar Chaudha

Nikunj Dahyabhai Patel

Methods, systems, computer-readable media, and apparatuses for region-of-interest (ROI) automatic gain or exposure control are presented. In one example, a method includes receiving a first image from an image sensor captured with a first field of view (FOV) and comprising a first plurality of pixels, receiving a second image from the image sensor captured with a second FOV and comprising a second plurality of pixels, determining an ROI in the second image, the ROI comprising a subset of the second plurality of pixels in the second image, determining an ROI weight for the ROI in the second image, determining statistics based on the first plurality of pixels in the first image, the subset of the second plurality of pixels in the second image, and the ROI weight for the ROI in the second image, and adjusting a gain or exposure setting for the image sensor based on the statistics.

Systems and methods region-of-interest automatic gain or exposure control

Systems, methods, and non-transitory media are provided for automatic exposure control. An example method can include receiving pixel values captured by a photosensor pixel array (PPA) of an image sensor, wherein one or more pixel values from the pixel values correspond to one or more sensitivity-biased photosensor (SBP) pixels in the PPA and one or more saturated pixel values from the pixel values correspond to one or more other photosensor pixels in the PPA; determining, based on the one or more pixel values, an actual pixel value for the one or more pixel values and/or the one or more saturated pixel values; determining an adjustment factor for at least one of the pixel values based on the actual pixel value and a target exposure value; and based on the adjustment factor, correcting an exposure setting associated with the image sensor and/or at least one of the pixel values.

Sensitivity-biased pixels

Methods, systems, computer-readable media, and apparatuses for region-of-interest automatic gain or exposure control are presented. One example method includes receiving an image from an image sensor, the image comprising a plurality of pixels, determining a region of interest ('ROI') in the image, the ROI comprising a subset of the plurality of pixels in the image, determining a ROI weight for pixels in the subset of the plurality of pixels, determining statistics for the image based on the plurality of pixels in the image and the ROI weight, and adjusting a gain or exposure setting for the image sensor based on the statistics.

Image frames for computational photography may be corrected, such as through rolling shutter correction (RSC), prior to fusion of the image frames to reduce wobble and jitter artifacts present in a video sequence of HDR-enhanced image frames. First and second motion data regarding motion of the image capture device may be determined for times corresponding to the capturing of the first and second image frames, respectively. The rolling shutter correction (RSC) may be applied to the first and second image frames based on both the first and second motion data. The corrected first and second image frames may then be aligned and fused to obtain a single output image frame with higher dynamic range than either of the first or second image frames.

Image alignment for computational photography

Methods and devices are described for image or video capture while in a manual mode. In some aspects, a device includes one or more processors. The device also includes a memory coupled to the one or more processors. The memory includes instructions that, when executed by the one or more processors, causes the device to generate a first image frame of a scene using manual mode settings and generate a second image frame of the scene using automatic mode settings different from the manual mode settings.

Generating an image using automatic mode settings while in manual mode

Aspects of the present disclosure relate to systems and methods for performing automatic white balance (AWB). An example device may include a memory and a processor coupled to the memory. The processor may be configured to receive a first image of a scene, measure a first illuminant of the first received image, compare the first illuminant and a first illuminant value, determine the scene is changing between the first received image and a previous image based on the comparison, adjust a first AWB convergence rate to a second AWB convergence rate in response to determining the scene is changing, and converge from a first balancing factor to a second balancing factor for one or more white balance operations based on the second AWB convergence rate.

Systems and methods for automatic white balance

Methods, systems, and devices for dual phase detection auto focus (PDAF) power optimization are described. A camera device may capture a frame including a pixel array representing a scene. In some examples, each pixel of the pixel array may be a phase detection (PD) pixel having one or more values, or one or more PD pixels positioned randomly across the pixel array. The camera device may identify a configuration of the pixel array, and determine a condition of the pixel array relative to the configuration. The configuration may be a binning configuration or a frame pattern configuration, and the condition may include an illumination condition related to the pixel array representing the scene. The camera device may determine and apply a reconfiguration to at least a portion of the pixel array based on the condition of the pixel array, and determine a lens position of the camera device therewith.

Dual phase detection power optimizations

A method of operating a device that includes an image sensor including a plurality of pixels includes: detecting visible light communication (VLC) signals with the image sensor; obtaining image data based on the VLC signals, the image data including a set of brightness components and possibly a set of chrominance components, and each brightness component of the set of brightness components being associated with a respective pixel of the plurality of pixels and (if available) each chrominance component of the set of chrominance components being associated with a respective pixel of the plurality of pixels; and decoding the set of brightness components to obtain information encoded in the VLC signals using a processor of the device without decoding, if available, the set of chrominance components.

Growing community of inventors

Hyderabad Telangana, India

Pradeep Kumar Veeramalla