Qualcomm Incorporated

Google Inc.

Szepo Robert Hung

Ruben Manuel Velarde

Hsiang-Tsun Li

Ying Noyes

Jingqiang Li

Jinglun Gao

Gang Sun

Liang Liang

Xiaoyun Jiang

Ying Chen Lou

Chinchuan Andrew Chiu

Lin Lu

Suk Hwan Lim

Kalin Mitkov Atanassov

Chung Chun Wan

Choon Ping Chng

Thomas Wesley Osborne

Haiyin Wang

Timothy Robert Povlick

Babak Forutanpour

Albert Meixner

Ananthapadmanabhan Arasanipalai Kandhadai

Blaise Hilary Aguera-Arcas

Hau Hwang

Ofer Shacham

Daniel Finchelstein

Shuxue Quan

Hengzhou Ding

Edward Y Chang

Xin Zhong

Carlos Manuel Puig

De Dzwo Hsu

David L Bednar

Subramaniam Venkatraman

Behnam Katibian

Sandeep Chaman Dhar

Qiurui He

Andrew Chinchuan Chiu

Sushil Nath

Nathaniel Jay Tobias Salazar

Kiran Murthy

Kohsia S Huang

Edward G Atrero

Jingqiang Liang

Hisiang-Tsun Li

Hsiang-Tsun Liu

Leung Chun Chan

Ying Xie Noyes

Thomas W Osborne

Ying X Noyes

The present disclosure describes systems and techniques directed to producing an all-in-focus image with a camera of a mobile device, in particular, cameras with shallow depth-of-field. User equipment includes a sensor for determining distance to an object in a camera's field-of-view. Based on a depth map of the field-of-view, a plurality of segments is inferred, each segment defining a unique focus area within the camera's field-of-view. An autofocus lens of the camera sweeps to a respective focal distance associated with each of the plurality of segments. The camera captures sample images at each focal distance swept by the autofocus lens. The user equipment produces an all-in-focus image by combining or merging portions of the captured sample images.

Automatic generation of all-in-focus images with a mobile camera

A method includes detecting, based on sensor data from a sensor on a mobile device, an environmental brightness measurement, where the mobile device comprises a display screen configured to adjust display brightness based on environmental brightness. The method further includes determining, based on image data from a camera on the mobile device, an extent to which the detected environmental brightness measurement is caused by reflected light from the display screen. The method additionally includes setting a rate of exposure change for the camera based on the determined extent to which the detected environmental brightness measurement is caused by reflected light from the display screen.

Exposure change control in low light environments

Techniques and apparatuses are described for reducing a flicker effect of multiple light sources in an image captured with an imaging device. A lighting frequency associated with each of the multiple light sources is detected and prioritized relative to a flicker effect upon the image to identify at least a first-prioritized lighting frequency and a second-prioritized lighting frequency. A first exposure-time factorization set is determined for the first-prioritized lighting frequency, and a second exposure-time factorization set is determined for the second-prioritized lighting frequency. An exposure time of the imaging device is adjusted to an exposure time identified in the first exposure-time factorization set that matches, or aligns near-to-matching, an exposure time identified in the second exposure-time factorization set.

Reducing a flicker effect of multiple light sources in an image

The present disclosure relates to a low-light autofocus technique. One example embodiment includes a method. The method includes receiving an indication of a low-light condition for a camera system. The method also includes determining an extended exposure time for a low-light autofocus procedure of the camera system. Further, the method includes capturing, by the camera system, an extended frame for the low-light autofocus procedure. The extended frame is captured by die camera system using the determined extended exposure time. In addition, the method includes determining, based on the captured extended frame, an in-focus lens setting for a lens of the camera system.

Low-light autofocus technique

A method is described that includes loading an array of content into a two-dimensional shift register. The two-dimensional shift register is coupled to an execution lane array. The method includes repeatedly performing a first sequence including: shifting with the shift register first content residing along a particular row or column into another parallel row or column where second content resides and performing operations with a particular corresponding row or column of the execution lane array on the first and second content. The method also includes repeatedly performing a second sequence including: shifting with the shift register content from a set of first locations along a resultant row or column that is parallel with the rows or columns of the first sequence into a corresponding set of second locations along the resultant row or column. The resultant row or column has values determined from the operations of the first sequence.

Statistics operations on two dimensional image processor

An apparatus is described. The apparatus includes a smart image sensor having a memory and a processor that are locally integrated with an image sensor. The memory is to store first program code to be executed by the processor. The memory is coupled to the image sensor and the processor. The memory is to store second program code to be executed by the processor. The first program code is to cause the smart image sensor to perform an analysis on one or more images captured by the image sensor. The analysis identifies a region of interest within the one or more images with machine learning from previously captured images. The second program code is to cause the smart image sensor to change an image sensing and/or optical parameter in response to the analysis of the one or more images performed by the execution of the first program code.

Smart image sensor having integrated memory and processor

This disclosure describes techniques for improving functionalities of a video encoder, using parameters detected and estimated by a front-end video capture device. The techniques may involve estimating a blurriness level associated with frames captured during a refocusing process. Based on the estimated blurriness level, the quantization parameter (QP) used to encode blurry frames is adjusted either in the video capture device or in the video encoder. The video encoder uses the adjusted QP to encode the blurry frames. The video encoder also uses the blurriness level estimate to adjust encoding algorithms by simplifying motion estimation and compensation in the blurry frames.

Control of video encoding based on one or more video capture parameters

Apparatus and methods for conditional display of a stereoscopic image pair on a display device are disclosed. In some aspects, a vertical disparity between two images is corrected. If the corrected vertical disparity is below a threshold, a three dimensional image may be generated based on the correction. In some cases, the corrected vertical disparity may still be significant, for example, above the threshold. In these instances, the disclosed apparatus and methods may display a two dimensional image.

Methods and apparatus for conditional display of a stereoscopic image pair

An apparatus is described. The apparatus includes a smart image sensor having a memory and a processor that are locally integrated with an image sensor. The memory is to store first program code to be executed by the processor. The memory is coupled to the image sensor and the processor. The memory is to store second program code to be executed by the processor. The first program code is to cause the smart image sensor to perform an analysis on one or more images captured by the image sensor. The analysis identifies a region of interest within the one or more images with machine learning from previously captured images. The second program code is to cause the smart image sensor to change an image sensing and/or optical parameter in response to the analysis of the one or more images performed by the execution of the first program code. Alternatively or in combination, the memory is to store third program code to be executed by the processor and fourth program code to be executed by the processor. The third program code is to store multiple images captured by the image sensor in the memory. The fourth program code is to merge the multiple images in the memory.

Growing community of inventors

Carlsbad, CA, United States of America

Szepo Robert Hung