Qualcomm Incorporated

Hsiang-Tsun Li

Hau Hwang

Szepo Robert Hung

Kalin Mitkov Atanassov

Haohong Wang

Sharath Manjunath

Xiaoyun Jiang

Jingqiang Li

Khaled Helmi El-Maleh

Shizhong Liu

Chinchuan Andrew Chiu

Joseph Cheung

Behnam Katibian

Prasanjit Panda

Babak Forutanpour

Yingyong Qi

Ruben Manuel Velarde

Xin Zhong

Ying Noyes

De Dzwo Hsu

Devender Akira Yamakawa

Jose Ricardo Dos Santos

Joseph Jyh-Huei Huang

Stephen Horton

Chang Yong

Kalin Atanssov

Benny Katibian

A monoscopic low-power mobile device is capable of creating real-time images and videos for multiple viewpoints from a single captured view. The device uses statistics from an autofocusing process to create a block depth map of a single capture view. Artifacts in the block depth map are reduced and an image depth map is created. Alternate views are created from the image depth map using a Z-buffer based surface recover process and a disparity map which is a function of a geometric vision model.

Real-time capturing and generating viewpoint images and videos with a monoscopic low power mobile device

Implementations relate to systems and methods for real-time image recognition and mobile visual searching. A mobile device, such as a cellular phone, acquires an image and pre-processes the acquired image to generate a visual search query based on objects detected in the acquired image. The visual search query includes the acquired image or a query image extracted therefrom and metadata associated with the detected objects. The mobile device wirelessly communicates the visual search query to a remote server, and in response to the visual search query, the remote server recognizes an object in the query image based on the associated metadata. The remote server then generates information content based on the recognized object and communicates the information content to the mobile device to be presented via the mobile device.

Systems and methods for image recognition using mobile devices

This disclosure describes techniques for rotating an encoded image, such as an image encoded according to a JPEG standard. In one example, a method for rotating an encoded image comprising reordering minimum coded units (MCUs) of the encoded image according to a specified rotation of the encoded image, rotating image data within the MCUs according to the specified rotation, and generating a rotated version of the encoded image comprising the reordered MCUs and the rotated image data within the MCUs.

Rotational transcoding for JPEG or other coding standards

A monoscopic low-power mobile device is capable of creating real-time stereo images and videos from a single captured view. The device uses statistics from an autofocusing process to create a block depth map of a single capture view. Artifacts in the block depth map are reduced and an image depth map is created. Stereo three-dimensional (3D) left and right views are created from the image depth map using a Z-buffer based 3D surface recover process and a disparity map which is a function of the geometry of binocular vision.

Real-time capturing and generating stereo images and videos with a monoscopic low power mobile device

An apparatus is described. The apparatus includes a digital camera that is capable of shooting at least two images at different effective lens focal lengths. The camera is also capable of high pass filtering (HP) said at least two images, estimating respective spectral densities (SD) of said at least two filtered images and then low pass filtering (LP) the respective estimates of said at least two filtered images prior to combining said at least two images into a single image to produce one or more optical effects.

Digital image combining to produce optical effects

Systems and methods to selectively combine images are disclosed. In a particular embodiment, an apparatus includes a registration circuit configured to generate a set of motion vector data based on first image data corresponding to a first image and second image data corresponding to a second image. The apparatus includes a combination circuit to selectively combine the first image data and adjusted second image data that corresponds to the second image data adjusted according to the motion vector data. The apparatus further includes a control circuit to control the combination circuit to generate third image data.

System and method to selectively combine images

To combine two or more images, an image capture device may compute motion vectors for a plurality of blocks of pixels of one of the images. The image capture device may also interpolate or extrapolate motion vectors for individual pixels or sub-blocks of pixels using the block motion vectors. The image capture device may then average the first and second images by averaging each of the pixels of the first image with pixels of the second image that correspond to a location indicated by the plurality of motion vectors. These techniques may reduce blur in image information resulting from certain movements during image capture or the use of certain image capture technologies.

Block-based image stabilization

This disclosure describes barcode scanning techniques for an image capture device. The image capture device may automatically detect a barcode within an image while the image capture device is operating in a non-barcode image capture mode, such a default image capture mode. In one aspect, the detection of the barcode within the image may be based on a combination of identified edges and low intensity regions within the image. The image capture device may configure, based on the detection of the barcode, one or more image capture properties associated with the image capture device to improve a quality at which the images are captured. The image capture device captures the image in accordance with the configured image capture properties. The techniques may effectively provide a universal and integrated front-end for producing improved quality images of barcodes without requiring significant interaction with a user via a complicated user interface.

Image capture device with integrated barcode scanning

A method and apparatus for generating stereoscopic images of a scene is described. The apparatus may have a first image sensor, a second image sensor spaced apart from the first image sensor, a diversity combine module to combine image data from the first and second image sensors, and an image processing module configured to process combined image data from the diversity combine module may be used to generate stereoscopic images of a scene.

Stereo image and video directional mapping of offset

A device has a processing unit to implement a set of operations to use both luma and chroma information from a scene of an image to dynamically adjust exposure time and sensor gain. The processing unit collects bright near grey pixels and high chroma pixels in the scene. Based on the collected pixels, brightness of the near grey pixels is increased to a predetermined level without saturation. At the same time, the high chroma pixels are kept away from saturation.

Scene-dependent auto exposure control

This disclosure describes techniques for detecting a barcode within an image. An image processor may, for example, process an image to detect regions within the image that may be barcodes. The image processor may identify regions of the image that exhibit a high concentration of edges and a high concentration of pixels with low optical intensity co-instantaneously as potential barcodes. The image processor may identify the regions using a number of morphological operations. The image processor may then determine whether the identified regions are actually barcodes by verifying whether the region have unique barcode features. The barcode detection techniques described in this disclosure may be independent of barcode size, location and orientation within the image. Moreover, the use of morphological operations results in faster and more computationally efficient barcode detection, as well as lower computational complexity.

Barcode detection based on morphological operations

Systems and methods of high dynamic range image combining are disclosed. In a particular embodiment, a device includes a global mapping module configured to generate first globally mapped luminance values within a region of an image, a local mapping module configured to generate second locally mapped luminance values within the region of the image, and a combination module configured to determine luminance values within a corresponding region of an output image using a weighted sum of the first globally mapped luminance values and the second locally mapped luminance values. A weight of the weighted sum is at least partially based on a luminance variation within the region of the image.

High dynamic range image combining

Techniques for complexity-adaptive and automatic two-dimensional (2D) to three-dimensional (3D) image and video conversion which classifies a frame of a 2D input into one of a flat image class and a non-flat image class are described. The flat image class frame is directly converted into 3D stereo for display. The frame that is classified as a non-flat image class is further processed automatically and adaptively, based on complexity, to create a depth map estimate. Thereafter, the non-flat image class frame is converted into a 3D stereo image using the depth map estimate or an adjusted depth map. The adjusted depth map is processed based on the complexity.

Complexity-adaptive 2D-to-3D video sequence conversion

Techniques for identifying and enhancing colors in a digital image associated with one or more target color shades. In an embodiment, the target color shades may include a shade of blue associated with the sky, a shade of green associated with outdoor foliage, or the color red. In an embodiment, the blue chroma (Cb) and red chroma (Cr) coordinates of a pixel are evaluated to determine whether to apply an enhancement factor. The enhancement factor may incorporate an exposure index (EI) auxiliary enhancement factor, a color temperature (D) auxiliary enhancement factor, and a luminance (Y) of each pixel. Further aspects for implementing the techniques in software and hardware are disclosed.

Color enhancement for digital images

Systems and methods of bad pixel cluster detection are disclosed. In a particular embodiment, a method includes determining a correlation value corresponding to a correlation coefficient between image data and at least one bad pixel cluster pattern, and detecting a bad pixel cluster corresponding to the at least one bad pixel cluster pattern based on the correlation value exceeding a threshold.

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San Diego, CA, United States of America

Hsiang-Tsun Li