Apple Inc.

Giancarlo Todone

Hao Sun

Farhan A Baqai

Richard David Seely

Gijesh Varghese

Morten Poulsen

Wu Cheng

Richard J Shields

Srivani Pinneli

Devices, methods, and non-transitory program storage devices (NPSDs) for an improved, so-called 'hybrid' image registration process are disclosed herein, comprising: obtaining a first set of captured images, wherein the first set of captured images comprises a reference image and one or more bracketed images; and for each of the one or more bracketed images: performing a first (e.g., global) registration operation and a second (e.g., dense, or other localized) registration operation on the bracketed image with respect to the reference image, wherein each of the first and second registration operations produces an output; generating a blend map for the bracketed image, wherein each value in the blend map indicates whether to use the first or second registration operation output for a corresponding one or more pixels when registering the bracketed image with the reference image; and registering the bracketed image with the reference image, according to the generated blend map.

Hybrid image registration techniques

Devices, methods, and computer-readable media are disclosed, describing an adaptive, subject-aware approach for image bracket selection and fusion, e.g., to generate high quality images in a wide variety of capturing conditions, including low light conditions. An incoming image stream may be obtained from an image capture device, comprising images captured using differing default exposure values, e.g., according to a predetermined pattern. When a capture request is received, it may be detected whether one or more human or animal subjects are present in the incoming image stream. If a subject is detected, an exposure time of one or more images selected from the incoming image stream may be reduced relative to its default exposure time. Prior to the fusion operation, one of the selected images may be designated a reference image for the fusion operation based, at least in part, on a sharpness score and/or a blink score of the image.

Subject-aware low light photography

An adaptive approach to image bracket determination and a more memory-efficient approach to image fusion, which are designed to generate low noise and high dynamic range (HDR) images in a wide variety of capturing conditions, are described. An incoming preview image stream may be obtained from an image capture device. When a capture request is received, an analysis may be performed on an image from the preview image stream that has a predetermined temporal relationship to the image capture request. Based on the analysis, a set of images (and their respective capture parameters, e.g., exposure time) may be determined for the image capture device to capture. As the determined set of images are captured, they may be registered and fused in a memory-efficient manner that, e.g., places an upper limit on the overall memory footprint of the registration and fusion operations&#x2014;regardless of how many images are captured in total.

Progressive image fusion

An incoming image stream may be obtained from an image capture device operating in low-light conditions and/or a simulated long exposure image capture mode. As images are obtained, a weighting operation may be performed on the pixels of the captured images to generate and/or update an accumulative weight map, wherein the weighting is based, e.g., on the proximity of the captured pixels' values to the respective image capture device's maximum observable pixel value. As batches of images are obtained, they may be fused, e.g., according to the accumulative weight map, in a memory-efficient manner that places an upper limit on the overall memory footprint of the fusion operations, to simulate an actual long exposure image capture. In some embodiments, the weight map may be stored at a lower resolution than the obtained images and then upscaled, e.g., via the use of guided filters, before being applied in the fusion operations.

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Mountain View, CA, United States of America

Giancarlo Todone