Qualcomm Incorporated

Xiaoyun Jiang

Chinchuan Andrew Chiu

Shuxue Quan

Shang-Chih Chuang

Jing Wang

Jiafu Luo

Szepo Robert Hung

Hsiang-Tsun Li

Jingqiang Li

Narayana Karthik Ravirala

Haohong Wang

Kalin Mitkov Atanassov

Khaled Helmi El-Maleh

Hau Hwang

Joseph Cheung

Ying Noyes

Weiliang Liu

Yunqiang Chen

Yi-Chun Lu

Ruben Manuel Velarde

Victor Hokkiu Chan

Shizhong Liu

Xin Zhong

Shilpi Sahu

Hasib Siddiqui

Venkata Ravi Kiran Dayana

Weihua Xiong

Xianbiao Shu

Pradeep Kumar Veeramalla

Ron Gaizman

Chung-Chi Tsai

Wei Zou

Min Li

Feng Li

Andrew Chinchuan Chiu

Stephen Horton

Silei Ma

Ki Sun Song

Ting-Kuei Hu

Hyung Cook Kim

Yun-Chieh Chang

Jianyou Li

Srinath Anekere Narayan

Kuang-Jui Hsu

Hisiang-Tsun Li

Dennis Liu

Eri Haneda

Shu Fei Fan

Younsu Kim

Nyeongkyu Kwon

Jun Zuo Liu

Sreevatsan Madhavan

Hasib Ahmed Siddiqui

Pradeep Veeramalla

Systems and methods for image fusing are described. In examples, a first image of a scene may be obtained associated with a first parameter and a second image of the scene may be obtained associated with a second parameter. The first image and the second image may be fused to obtain at least one first fused image. A third image of the scene may be obtained associated with a third parameter and a fourth image of the scene may be obtained associated with a fourth image. At least one parameter associated with the third image and the fourth image used to obtain the images may be adjusted, wherein the adjustment may be based at least in part on a field of view of the at least one first fused image. The third image and the fourth image may be fused to obtain a second fused image.

Method and apparatus for image capturing

This disclosure provides systems, methods, and devices for image signal processing that support improved demosaicing of color image signal. In a first aspect, a method of image processing includes receiving a first image frame and a second image frame. The method may also include determining a first demosaiced image frame by applying a first demosaic process to the first image frame and determining a second demosaiced image frame by applying a second demosaic process to the first image frame based on the second image frame. Blending weights may be determined based on the first image frame and the second image frame and a blended image frame may be determined by combining pixel values from corresponding portions of the first demosaiced image frame and the second demosaiced image frame according to the blending weights. Other aspects and features are also claimed and described.

Mono guided bayer demosaic image processing

An apparatus for image processing includes one or more processors configured to receive first image data in a first color format that includes a plurality of color planes at a reduced resolution relative to a full resolution, generate second image data in an intermediate color format based on the first image data in the first color format, the intermediate color format includes a first color plane at an increased resolution and at least one of the plurality of color planes at the reduced resolution, store, in the one or more external memories, the second image data, perform image processing based on accessing the second image data, and generate third image data based on the image processing, the third image data is in a third color format that includes the plurality of color planes at a same resolution.

Intermediate color format for image processing

This disclosure provides systems, methods, and devices for image signal processing that support improved detail keeping in photography through increased dynamic range and/or highlight-keeping. The image signal processing may be performed on data received from a split-pixel image sensor with two sets of sensor elements with different sensitivities. The image signal processing may include receiving image data comprising: first data from a first set of sensor elements and second data from a second set of sensor elements capturing a representation of the scene with a different sensitivity that the first set of sensor elements; determining an output dynamic range for an output image frame; and determining an output image frame based on at least one of the first data and the second data and based on the output dynamic range. Other aspects and features are also claimed and described.

Image sensor and data processing for parallel frame capture in high dynamic range (HDR) photography

Imaging systems and techniques are described. An imaging system determines, based on image data of a scene received from an image sensor, a first plurality of pixel values corresponding to a first electromagnetic (EM) frequency domain and a second plurality of pixel values corresponding to a second EM frequency domain. The imaging system reduces the first plurality of pixel values using a plurality of cross-domain contamination values (based on the second plurality of pixel values) to generate a third plurality of pixel values. The imaging system determines a reconstructed pixel value based on a combination of at least an overexposed pixel value of the first plurality of pixel values and a corresponding pixel of the third plurality of pixel values. The imaging system outputs a reconstructed image that includes the reconstructed pixel value and a subset of the third plurality of pixel values.

Systems and methods of imaging with multi-domain image sensor

This disclosure provides systems, methods, and devices for image processing that supports high dynamic range (HDR) photography. In some aspects, a method of generating a full-resolution HDR photograph with in-sensor zoom includes receiving first and second image data corresponding to first and second exposure captures of a scene. First and second full-resolution image frames may be generated from the first and second image data, which are subsequently processed with HDR fusion to obtain an output image frame with higher dynamic range than either the first or second image data. The first full-resolution image frame may be determined from both the first and second image data by compensating the second image data for differences between the first and second exposures. Other aspects and features are also claimed and described.

High dynamic range (HDR) photography with in-sensor zoom

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

Apparatus for generating images using a mechanical infrared cut-off switch are disclosed herein. An example apparatus including an optical system for generating images includes a mechanical infrared light filter movable between a first position and a second position. The mechanical infrared light filter may be configured to allow infrared light to pass through the optical system while in the first position and configured to filter out infrared light from the optical system while in the second position. The example apparatus also includes an imaging sensor including imaging pixels and infrared pixels, and may be configured to receive light from the optical system. Additionally, the example apparatus includes a processor configured to receive visible light data and infrared light data from the image sensor. The processor may further be configured to generate a combined image based on the visible light data and the infrared light data.

Mechanical infrared light filter

A transformer may transform image data from a first color pattern to a second color pattern. The transforming of image data may be applied to image data received from a memory storing an array of intensities corresponding to a first color pattern of a first color filter array (CFA) of an image sensor to a second color pattern. The second color pattern may be a color pattern of a size smaller that the first CFA. Remosaicing may be applied to the second color pattern to obtain image data organized in a Bayer color pattern. The transforming may be configured to operate on data from an image sensor to obtain different zoom levels not available without applying a digital zoom algorithm that involve upscaling, which reduces the image quality of the image data.

Image data processing using non-integer ratio transforming for color arrays

The present disclosure relates to methods and apparatus for image processing. For example, disclosed techniques facilitate a sparse infrared pixel design for image sensors. Aspects of this disclosure include an image sensor including a pattern of pixels, the pattern of pixels including a set of visible light pixels and a set of infrared light pixels. The image sensor may be configured to generate visible light data and infrared light data based on received light. Aspects of the present disclosure also include a processor coupled to the image sensor. The processor may be configured to generate a configurable mask based on the pattern of pixels of the image sensor, and where values of the configurable mask correspond to pixel locations of the image sensor.

Sparse infrared pixel design for image sensors

Methods, systems, and devices for anchor frame switching in an imaging system are described. A device may generate a pixel map based on a set of frames. A first subset of frames of the set of frames have a first exposure and a second subset of frames of the set of frames have a second exposure different than the first exposure. The device may determine a region of the pixel map representing motion between at least two frames of the first set of frames. If the device determines that a quantity of motion pixels in the region is higher than a threshold, the device may select a short exposure frame as an anchor frame, beginning at a later frame. Otherwise, the device may maintain using a long exposure frame as the anchor frame.

Techniques for anchor frame switching

Methods, systems, and devices for minimizing ghosting in high dynamic range image processing are described. The method may include capturing from a sensor of the device a downscaled first frame of a first exposure length and a downscaled second frame of a second exposure length that is longer than the first exposure length, identifying a highlight region associated with the downscaled first frame and a motion region associated with the downscaled first frame and with the downscaled second frame, blending the motion region in accordance with determining whether at least a portion of the motion region overlaps the highlight region, and incorporating the blending of the motion region in a set of full resolution frames.

Minimizing ghosting in high dynamic range image processing

Systems, methods, and computer-readable media are provided for foreground image segmentation. In some examples, a method can include obtaining a first image of a target and a second image of the target, the first image having a first field-of-view (FOV) and the second image having a second FOV; determining, based on the first image, a first segmentation map that identifies a first estimated foreground region in the first image; determining, based on the second image, a second segmentation map that identifies a second estimated foreground region in the second image; generating a third segmentation map based on the first segmentation map and the second segmentation map; and generating, using the second segmentation map and the third segmentation map, a refined segmentation mask that identifies the target as a foreground region of the first and/or second image.

Segmentation for image effects

Aspects of the present disclosure relate to systems and methods for selectively processing tiles of a captured image. The captured image may be parsed into a plurality of tiles. A subset of the plurality of tiles may be selected based at least in part on at least one metric. The selected tiles may be processed according to a first technique, while each unselected tile may be selectively processed according to one or more techniques different from the first technique. The first technique and the one or more techniques may each be either an image demosaicing technique or an image denoising technique.

Tile-selection based deep demosaicing acceleration

Methods, systems, and devices for processing color information are described. The method may include receiving a first set of image data collected at an image sensor based on a first color filter array having a first filter pattern, calculating a color saturation gradient based on the first set of image data, and calculating multiple color gradients based on the color saturation gradient. The multiple color gradients may each be associated with a region of the first set of image data, where each color gradient characterizes a color variation along a different direction of the region. The method may include generating a second set of image data including a color value for the region based on comparing a first direction gradient of the multiple color gradients with a second direction gradient of the multiple color gradients. Color values associated with the regions may be mapped to a second color filter array.

Color filter array pattern conversion

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San Diego, CA, United States of America

Xiaoyun Jiang