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公开(公告)号：US11562470B2
公开(公告)日：2023-01-24
申请号：US17224830
申请日：2021-04-07
申请人： Apple Inc.
发明人： Marius Tico , Alok Deshpande , Anita Nariani Schulze , Hao Sun , Jun Hu , Justin Michael Faryabi-Allen , Morten Poulsen , Tak Shing Wong , Wu Cheng
摘要： Devices, methods, and computer-readable media are disclosed describing an adaptive approach for image bracket selection and fusion, e.g., to generate low noise and high dynamic range (HDR) images in a wide variety of capturing conditions. An incoming image stream may be obtained from an image capture device, wherein the incoming image stream comprises a variety of differently-exposed captures, e.g., EV0 images, EV− images, EV+ images, long exposure (or synthetic long exposure) images, EV0/EV− image pairs, etc., which are received according to a particular pattern. When a capture request is received, a set of rules and/or a decision tree may be used to evaluate one or more capture conditions associated with the images from the incoming image stream and determine which two or more images to select for a fusion operation. A noise reduction process may optionally be performed on the selected images before (or after) the registration and fusion operations.
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公开(公告)号：US11151702B1
公开(公告)日：2021-10-19
申请号：US16564508
申请日：2019-09-09
申请人： Apple Inc.
发明人： Marius Tico , Tiffany Jou Cheng , Jun Hu
摘要： Electronic devices, methods, and program storage devices for leveraging machine learning to perform improved image fusion and/or noise reduction are disclosed. An incoming image stream may be obtained from an image capture device, wherein the incoming image stream comprises a variety of differently-exposed captures, e.g., EV0 images, EV− images, EV+ images, long exposure images, EV0/EV− image pairs, etc., which are received according to a particular pattern. When a capture request is received, two or more intermediate assets may be generated based on determined combinations of images from the incoming image stream, and the intermediate assets may then be fed into a neural network that has been trained to determine one or more sets of parameters to optimally fuse and/or noise reduce the intermediate assets. In some embodiments, the network may be trained to operate on levels of pyramidal decompositions of the intermediate assets independently, for increased efficiency and memory utilization.
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公开(公告)号：US11488374B1
公开(公告)日：2022-11-01
申请号：US16578825
申请日：2019-09-23
申请人： Apple Inc.
发明人： Wei Sun , Jun Hu , Marius Tico , Xuemei Zhang
摘要： The disclosure pertains to techniques for image processing. One such technique comprises a method for image selection, comprising obtaining a sequence of images, detecting one or more objects in one or more images of the sequence of images, determining a location for each detected object in the one or more images, determining a trajectory for each detected object based on a determined location for each respective detected object in two or more images of the sequence of images, determining a trajectory waypoint score for the trajectory of each detected object, determining a set of selected images based on an aggregation of trajectory waypoint scores for each detected object in each respective image, and outputting the set of selected images for presentation.
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公开(公告)号：US20170358094A1
公开(公告)日：2017-12-14
申请号：US15620131
申请日：2017-06-12
申请人： Apple Inc.
发明人： Wei Sun , Jun Hu , Tongbo Chen
CPC分类号： G06T7/194 , G06T7/11 , G06T7/174 , G06T2207/10148 , G06T2207/20028
摘要： Adaptive focus sweep (AFS) techniques for image processing are described. For one technique, an AFS logic/module can obtain an AFS representing a scene, where the AFS is a sequence of images representing the scene that includes: (i) a first image representing the scene captured at a first focus position; and (ii) a second image representing the scene captured at a second focus position that differs from the first focus position. The first focus position can be associated with a first depth of field (DOField) that is determined based on an autofocus technique. The second focus position can be associated with a second DOField, where the second focus position is at least two DOFields away from the first focus position. The AFS logic/module can detect a foreground of the scene in the first image based on information acquired from the first and second images. Other embodiments are described.
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公开(公告)号：US10977778B2
公开(公告)日：2021-04-13
申请号：US16426448
申请日：2019-05-30
申请人： Apple Inc.
发明人： Marius Tico , Alok Deshpande , Anita Nariani Schulze , Hao Sun , Jun Hu , Justin Michael Faryabi-Allen , Morten Poulsen , Tak Shing Wong , Wu Cheng
摘要： Devices, methods, and computer-readable media are disclosed describing an adaptive approach for image bracket selection and fusion, e.g., to generate low noise and high dynamic range (HDR) images in a wide variety of capturing conditions. An incoming image stream may be obtained from an image capture device, wherein the incoming image stream comprises a variety of differently-exposed captures, e.g., EV0 images, EV− images, EV+ images, long exposure (or synthetic long exposure) images, EV0/EV− image pairs, etc., which are received according to a particular pattern. When a capture request is received, a set of rules and/or a decision tree may be used to evaluate one or more capture conditions associated with the images from the incoming image stream and determine which two or more images to select for a fusion operation. A noise reduction process may optionally be performed on the selected images before (or after) the registration and fusion operations.
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公开(公告)号：US20210256669A1
公开(公告)日：2021-08-19
申请号：US17224830
申请日：2021-04-07
申请人： Apple Inc.
发明人： Marius Tico , Alok Deshpande , Anita Nariani Schulze , Hao Sun , Jun Hu , Justin Michael Faryabi-Allen , Morten Poulsen , Tak Shing Wong , Wu Cheng
摘要： Devices, methods, and computer-readable media are disclosed describing an adaptive approach for image bracket selection and fusion, e.g., to generate low noise and high dynamic range (HDR) images in a wide variety of capturing conditions. An incoming image stream may be obtained from an image capture device, wherein the incoming image stream comprises a variety of differently-exposed captures, e.g., EV0 images, EV− images, EV+ images, long exposure (or synthetic long exposure) images, EV0/EV− image pairs, etc., which are received according to a particular pattern. When a capture request is received, a set of rules and/or a decision tree may be used to evaluate one or more capture conditions associated with the images from the incoming image stream and determine which two or more images to select for a fusion operation. A noise reduction process may optionally be performed on the selected images before (or after) the registration and fusion operations.
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