Multi-Image Color Refinement with Application to Disparity Estimation

    公开(公告)号:US20170104976A1

    公开(公告)日:2017-04-13

    申请号:US14882106

    申请日:2015-10-13

    Applicant: Apple Inc.

    Inventor: Thomas E. Bishop

    Abstract: Systems, methods, and computer-readable media to improve multi-image color-refinement operations are disclosed for refining color differences between images in a multi-image camera system with application to disparity estimation. Recognizing that corresponding pixels between two (or more) images of a scene should have not only the same spatial location, but the same color, can be used to improve the spatial alignment of two (or more) such images and the generation of improved disparity maps. After making an initial disparity estimation and using it to align the images, colors in one image may be refined toward that of another image. (The image being color corrected may be either the reference image or the image(s) being registered with the reference image.) Repeating this process in an iterative manner allows improved spatial alignment between the images and the generation of superior disparity maps between the two (or more) images.

    Single And Multi-Camera Calibration
    3.
    发明申请
    Single And Multi-Camera Calibration 审中-公开
    单和多相机校准

    公开(公告)号:US20170070731A1

    公开(公告)日:2017-03-09

    申请号:US15256526

    申请日:2016-09-03

    Applicant: Apple Inc.

    CPC classification number: H04N17/002 G06T7/337 G06T7/80 G06T7/85

    Abstract: Camera calibration includes capturing a first image of an object by a first camera, determining spatial parameters between the first camera and the object using the first image, obtaining a first estimate for an optical center, iteratively calculating a best set of optical characteristics and test setup parameters based on the first estimate for the optical center until the difference in a most recent calculated set of optical characteristics and previously calculated set of optical characteristics satisfies a predetermined threshold, and calibrating the first camera based on the best set of optical characteristics. Multi-camera system calibration may include calibrating, based on a detected misalignment of features in multiple images, the multi-camera system using a context of the multi-camera system and one or more prior stored contexts.

    Abstract translation: 相机校准包括通过第一相机捕获对象的第一图像,使用第一图像确定第一相机和对象之间的空间参数,获得光学中心的第一估计值,迭代地计算最佳的一组光学特性和测试设置 基于光学中心的第一估计的参数,直到最近计算出的光学特性集合的差异和先前计算出的光学特性的组合满足预定阈值,并且基于最佳的光学特性集来校准第一相机。 多摄像机系统校准可以包括基于检测到的多个图像中的特征的不对准,使用多摄像机系统的上下文和一个或多个先前存储的上下文来校准多摄像机系统。

    Multi-image color-refinement with application to disparity estimation

    公开(公告)号:US10785466B2

    公开(公告)日:2020-09-22

    申请号:US16154098

    申请日:2018-10-08

    Applicant: Apple Inc.

    Inventor: Thomas E. Bishop

    Abstract: Systems, methods, and computer-readable media to improve multi-image color-refinement operations are disclosed for refining color differences between images in a multi-image camera system with application to disparity estimation. Recognizing that corresponding pixels between two (or more) images of a scene should have not only the same spatial location, but the same color, can be used to improve the spatial alignment of two (or more) such images and the generation of improved disparity maps. After making an initial disparity estimation and using it to align the images, colors in one image may be refined toward that of another image. (The image being color corrected may be either the reference image or the image(s) being registered with the reference image.) Repeating this process in an iterative manner allows improved spatial alignment between the images and the generation of superior disparity maps between the two (or more) images.

    Photo-realistic Shallow Depth-of-Field Rendering from Focal Stacks
    5.
    发明申请
    Photo-realistic Shallow Depth-of-Field Rendering from Focal Stacks 审中-公开
    从焦点堆栈的照片逼真的浅景深渲染

    公开(公告)号:US20170070720A1

    公开(公告)日:2017-03-09

    申请号:US14864650

    申请日:2015-09-24

    Applicant: Apple Inc.

    Abstract: Generating an image with a selected level of background blur includes capturing, by a first image capture device, a plurality of frames of a scene, wherein each of the plurality of frames has a different focus depth, obtaining a depth map of the scene, determining a target object and a background in the scene based on the depth map, determining a goal blur for the background, and selecting, for each pixel in an output image, a corresponding pixel from the focus stack.

    Abstract translation: 生成具有所选择的背景模糊级别的图像包括由第一图像捕获装置捕获场景的多个帧,其中多个帧中的每一个具有不同的焦点深度,获得场景的深度图,确定 基于深度图的场景中的目标对象和背景,确定背景的目标模糊,以及从输出图像中的每个像素选择来自焦点堆栈的对应像素。

    Optimizing Capture Of Focus Stacks
    6.
    发明申请
    Optimizing Capture Of Focus Stacks 有权
    优化焦点堆栈的捕获

    公开(公告)号:US20160360091A1

    公开(公告)日:2016-12-08

    申请号:US14864565

    申请日:2015-09-24

    Applicant: Apple Inc.

    Abstract: Generating a focus stack, including receiving initial focus data that identifies a plurality of target depths, positioning a lens at a first position to capture a first image at a first target depth of the plurality of target depths, determining, in response to capturing the first image and prior to capturing additional images, a sharpness metric for the first image, capturing, in response to determining that the sharpness metric for the first image is an unacceptable value, a second image at a second position based on the sharpness metric, wherein the second position is not included in the plurality of target depths, determining that a sharpness metric for the second image is an acceptable value, and generating a focus stack using the second image.

    Abstract translation: 生成焦点堆叠,包括接收识别多个目标深度的初始聚焦数据,将透镜定位在第一位置以在多个目标深度的第一目标深度捕获第一图像,响应于捕获第一 图像,并且在捕获附加图像之前,针对第一图像的锐度度量,响应于确定第一图像的锐度度量是不可接受的值,捕获,基于锐度度量在第二位置处的第二图像,其中 第二位置不包括在多个目标深度中,确定第二图像的锐度度量是可接受的值,并且使用第二图像生成焦点堆叠。

    Depth Map Calculation in a Stereo Camera System

    公开(公告)号:US20190208125A1

    公开(公告)日:2019-07-04

    申请号:US16298272

    申请日:2019-03-11

    Applicant: Apple Inc.

    Abstract: A method for generating a depth map is described. The method includes obtaining a first image of a scene from a first image capture unit, the first image having a first depth-of-field (DOF), obtaining a second image of the scene from a second image capture unit, the second image having a second DOF that is different than the first DOF. Each pixel in the second image has a corresponding pixel in the first image. The method also includes generating a plurality of third images, each corresponding to a blurred version of the second image at each of a plurality of specified depths, generating a plurality of fourth images, each representing a difference between the first image and one or the plurality of third images, and generating a depth map where each pixel in the depth map is based on the pixels in one of the plurality of fourth images.

    Depth map calculation in a stereo camera system

    公开(公告)号:US10237473B2

    公开(公告)日:2019-03-19

    申请号:US14864603

    申请日:2015-09-24

    Applicant: Apple Inc.

    Abstract: A method for generating a depth map is described. The method includes obtaining a first image of a scene from a first image capture unit, the first image having a first depth-of-field (DOF), obtaining a second image of the scene from a second image capture unit, the second image having a second DOF that is different than the first DOF. Each pixel in the second image has a corresponding pixel in the first image. The method also includes generating a plurality of third images, each corresponding to a blurred version of the second image at each of a plurality of specified depths, generating a plurality of fourth images, each representing a difference between the first image and one or the plurality of third images, and generating a depth map where each pixel in the depth map is based on the pixels in one of the plurality of fourth images.

    Multi-Image Color-refinement with Application to Disparity Estimation

    公开(公告)号:US20190052860A1

    公开(公告)日:2019-02-14

    申请号:US16154098

    申请日:2018-10-08

    Applicant: Apple Inc.

    Inventor: Thomas E. Bishop

    Abstract: Systems, methods, and computer-readable media to improve multi-image color-refinement operations are disclosed for refining color differences between images in a multi-image camera system with application to disparity estimation. Recognizing that corresponding pixels between two (or more) images of a scene should have not only the same spatial location, but the same color, can be used to improve the spatial alignment of two (or more) such images and the generation of improved disparity maps. After making an initial disparity estimation and using it to align the images, colors in one image may be refined toward that of another image. (The image being color corrected may be either the reference image or the image(s) being registered with the reference image.) Repeating this process in an iterative manner allows improved spatial alignment between the images and the generation of superior disparity maps between the two (or more) images.

    Multi-image color refinement with application to disparity estimation

    公开(公告)号:US10097805B2

    公开(公告)日:2018-10-09

    申请号:US14882106

    申请日:2015-10-13

    Applicant: Apple Inc.

    Inventor: Thomas E. Bishop

    Abstract: Systems, methods, and computer-readable media to improve multi-image color-refinement operations are disclosed for refining color differences between images in a multi-image camera system with application to disparity estimation. Recognizing that corresponding pixels between two (or more) images of a scene should have not only the same spatial location, but the same color, can be used to improve the spatial alignment of two (or more) such images and the generation of improved disparity maps. After making an initial disparity estimation and using it to align the images, colors in one image may be refined toward that of another image. (The image being color corrected may be either the reference image or the image(s) being registered with the reference image.) Repeating this process in an iterative manner allows improved spatial alignment between the images and the generation of superior disparity maps between the two (or more) images.

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