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公开(公告)号：US20150206289A1
公开(公告)日：2015-07-23
申请号：US14160424
申请日：2014-01-21
Applicant: Adobe Systems Incorporated
Inventor： Jue Wang , Sunghyun Cho , Dun-Yu Hsiao , Shuaicheng Liu
IPC: G06T5/00
CPC classification number: G06T5/003 , G06T5/50 , G06T2207/10016 , G06T2207/20016 , G06T2207/20021 , G06T2207/20182 , G06T2207/20201
Abstract: Joint video deblurring and stabilization techniques are described. In one or more implementations, a deblurring and stabilization module is configured to jointly deblur and stabilize a video by grouping video frames into spatial-neighboring frame clusters, and building local mesh homographies for video frames in each spatial-neighboring frame cluster.
Abstract translation: 描述了联合视频去模糊和稳定技术。 在一个或多个实现中，去模糊和稳定模块被配置为通过将视频帧分组成空间相邻帧群集并且为每个空间相邻帧群集中的视频帧构建局部网格同画物来共同去除和稳定视频。
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公开(公告)号：US20150110403A1
公开(公告)日：2015-04-23
申请号：US14061098
申请日：2013-10-23
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Sunghyun Cho , JUE WANG , JEN-CHAN CHIEN , DONG FENG
IPC: G06T5/00
CPC classification number: G06K9/52 , G06K9/6218 , G06K2009/4666 , G06T5/00 , G06T5/003 , G06T7/60 , G06T2207/20024 , G06T2207/20048 , G06T2207/20172 , G06T2207/20192
Abstract: A computer-implemented method and apparatus are described for deblurring an image. The method may include accessing the image that has at least one blurred region and, automatically, without user input, determining a first value for a first size for a blur kernel for the at least one blurred region. Thereafter, automatically, without user input, a second value for a second size for the blur kernel is determined for the at least one blurred region. A suggested size for the blur kernel is then determined based on the first value and the second value.
Abstract translation: 描述了用于去图像的计算机实现的方法和装置。 该方法可以包括访问具有至少一个模糊区域的图像，并且在没有用户输入的情况下，自动确定用于至少一个模糊区域的模糊核心的第一尺寸的第一值。 此后，自动地，在没有用户输入的情况下，为至少一个模糊区域确定用于模糊核的第二大小的第二值。 然后基于第一值和第二值确定模糊内核的建议大小。
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3.发明申请公开(公告)号：US20150063716A1
公开(公告)日：2015-03-05
申请号：US14488441
申请日：2014-09-17
Applicant: Adobe Systems Incorporated
Inventor： Jue Wang , Sunghyun Cho , Lin Zhong
IPC: G06T5/00
Abstract: Systems and methods are provided for providing improved de-noising image content by using directional noise filters to accurately estimate a blur kernel from a noisy blurry image. In one embodiment, an image manipulation application applies multiple directional noise filters to an input image to generate multiple filtered images. Each of the directional noise filters has a different orientation with respect to the input image. The image manipulation application determines multiple two-dimensional blur kernels from the respective filtered images. The image manipulation application generates a two- two-dimensional blur kernel for the input image from the two-dimensional blur kernels for the filtered images. The image manipulation application generates a de-blurred version of the input image by executing a de-blurring algorithm based on the two-dimensional blur kernel for the input image.
Abstract translation: 提供了系统和方法，用于通过使用定向噪声滤波器从嘈杂的模糊图像中精确地估计模糊核来提供改进的去噪图像内容。 在一个实施例中，图像处理应用将多个定向噪声滤波器应用于输入图像以生成多个滤波图像。 每个方向噪声滤波器相对于输入图像具有不同的取向。 图像处理应用从相应的滤波图像确定多个二维模糊内核。 图像处理应用为来自二维模糊内核的滤波图像的输入图像生成二维模糊核心。 图像处理应用程序通过执行基于用于输入图像的二维模糊核心的去模糊算法来生成输入图像的去模糊版本。
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公开(公告)号：US10032258B2
公开(公告)日：2018-07-24
申请号：US15452620
申请日：2017-03-07
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Sunghyun Cho , Jue Wang , Jen-Chan Chien , Dong Feng
Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed towards automatic selection of regions for blur kernel estimation. In one embodiment, a process divides a blurred image into a regions. From these regions a first region and a second region can be selected based on a number of edge orientations within the selected regions. A first blur kernel can then be estimated based on the first region and a second blur kernel can be estimated for the second region. The first and second blur kernel can then be utilized to respectively deblur a first and second portion of the image to produce a deblurred image. Other embodiments may be described and/or claimed.
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公开(公告)号：US09349165B2
公开(公告)日：2016-05-24
申请号：US14061131
申请日：2013-10-23
Applicant: Adobe Systems Incorporated
Inventor： Sunghyun Cho , Jue Wang , Jen-Chan Chien , Dong Feng
CPC classification number: G06T5/003 , G06T5/20 , G06T11/001 , G06T2207/10024 , G06T2207/20192 , G06T2207/20201 , G06T2207/20221
Abstract: A computer-implemented method and apparatus are described for automatically selecting a region in a blurred image for blur kernel estimation. The method may include accessing a blurred image and defining a size for each of a plurality of regions in the image. Thereafter, metrics for at least two of the plurality of regions are determined, wherein the metrics are based on a number of edge orientations within each region. A region is selected from the plurality of regions based on the determined metrics, and a blur kernel for deblurring the blurred image is then estimated for the selected region. The blurred image is then deblurred using the blur kernel.
Abstract translation: 描述了用于自动选择模糊图像中的区域以进行模糊核估计的计算机实现的方法和装置。 该方法可以包括访问模糊图像并且为图像中的多个区域中的每一个定义大小。 此后，确定多个区域中的至少两个的度量，其中度量基于每个区域内的边缘取向的数量。 基于所确定的度量，从多个区域中选择区域，然后针对所选择的区域估计用于去模糊模糊图像的模糊核心。 然后使用模糊内核去除模糊的图像。
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Patent Agency Ranking
公开(公告)号：US09299132B2
公开(公告)日：2016-03-29
申请号：US14061098
申请日：2013-10-23
Applicant: Adobe Systems Incorporated
Inventor： Sunghyun Cho , Jue Wang , Jen-Chan Chien , Dong Feng
CPC classification number: G06K9/52 , G06K9/6218 , G06K2009/4666 , G06T5/00 , G06T5/003 , G06T7/60 , G06T2207/20024 , G06T2207/20048 , G06T2207/20172 , G06T2207/20192
Abstract: A computer-implemented method and apparatus are described for deblurring an image. The method may include accessing the image that has at least one blurred region and, automatically, without user input, determining a first value for a first size for a blur kernel for the at least one blurred region. Thereafter, automatically, without user input, a second value for a second size for the blur kernel is determined for the at least one blurred region. A suggested size for the blur kernel is then determined based on the first value and the second value.
Abstract translation: 描述了用于去图像的计算机实现的方法和装置。 该方法可以包括访问具有至少一个模糊区域的图像，并且在没有用户输入的情况下，自动确定用于至少一个模糊区域的模糊核心的第一尺寸的第一值。 此后，自动地，在没有用户输入的情况下，为至少一个模糊区域确定用于模糊核的第二大小的第二值。 然后基于第一值和第二值确定模糊内核的建议大小。
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公开(公告)号：US09076205B2
公开(公告)日：2015-07-07
申请号：US13680952
申请日：2012-11-19
Applicant: Adobe Systems Incorporated
Inventor： Sunghyun Cho , Jue Wang , Lin Zhong
Abstract: An image de-blurring system obtains a blurred input image and generates, based on the blurred input image, a blur kernel. The blur kernel is an indication of how the image capture device was moved and/or how the subject captured in the image moved during image capture. Based on the blur kernel and the blurred input image, a de-blurred image is generated. The blur kernel is generated based on the direction of edges identified in the blurred input image and/or based on curves having a high curvature identified in the image (e.g., corners identified in the image).
Abstract translation: 图像去模糊系统获得模糊的输入图像，并且基于模糊的输入图像生成模糊核。 模糊内核是图像捕获设备如何被移动的指示和/或在图像捕获期间如何在图像中捕获的图像移动。 基于模糊内核和模糊输入图像，生成去模糊图像。 基于在模糊输入图像中识别的边缘的方向和/或基于在图像中识别的具有高曲率的曲线（例如，图像中标识的角），生成模糊核。
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公开(公告)号：US20150172547A1
公开(公告)日：2015-06-18
申请号：US14105554
申请日：2013-12-13
Applicant: Adobe Systems Incorporated
Inventor： Jue Wang , Sunghyun Cho , Zhe Hu
IPC: H04N5/232
CPC classification number: H04N5/23267 , G06T5/003
Abstract: A blurred image having a spatially invariant motion blur resulting from camera motion during image capture is deblurred based on one or more light streaks identified and extracted from the blurred image. A blur kernel for the blurred image is estimated by performing an optimization procedure having a blur kernel constraint based at least in part on the light streak. One or more light streaks can in some embodiments be posed as the blur kernel constraint. A modeled light streak may be defined as a convolution between the blur kernel and a simulated light source, with the optimization procedure being to minimize a distance between the modeled light streak and the corresponding identified light streak from the blurred image.
Abstract translation: 基于从模糊图像识别和提取的一条或多条光条纹，在图像拍摄期间具有由相机运动产生的空间不变运动模糊的模糊图像被去毛刺。 用于模糊图像的模糊内核通过至少部分地基于光条纹执行具有模糊内核约束的优化过程来估计。 在一些实施例中，可以提供一个或多个光条纹作为模糊核心约束。 模拟的光条可以被定义为模糊核与模拟光源之间的卷积，优化过程是将建模的条纹与从模糊图像相应的识别光条纹之间的距离最小化。
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公开(公告)号：US20140140626A1
公开(公告)日：2014-05-22
申请号：US13680952
申请日：2012-11-19
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Sunghyun Cho , Jue Wang , Lin Zhong
IPC: G06T5/00
Abstract: An image de-blurring system obtains a blurred input image and generates, based on the blurred input image, a blur kernel. The blur kernel is an indication of how the image capture device was moved and/or how the subject captured in the image moved during image capture. Based on the blur kernel and the blurred input image, a de-blurred image is generated. The blur kernel is generated based on the direction of edges identified in the blurred input image and/or based on curves having a high curvature identified in the image (e.g., corners identified in the image).
Abstract translation: 图像去模糊系统获得模糊的输入图像，并且基于模糊的输入图像生成模糊核。 模糊内核是图像捕获设备如何被移动的指示和/或在图像捕获期间如何在图像中捕获的图像移动。 基于模糊内核和模糊输入图像，生成去模糊图像。 基于在模糊输入图像中识别的边缘的方向和/或基于在图像中识别的具有高曲率的曲线（例如，图像中标识的角），生成模糊核。
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公开(公告)号：US09779489B2
公开(公告)日：2017-10-03
申请号：US15161073
申请日：2016-05-20
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Sunghyun Cho , Jue Wang , Jen-Chan Chien , Dong Feng
CPC classification number: G06T5/003 , G06T5/20 , G06T11/001 , G06T2207/10024 , G06T2207/20192 , G06T2207/20201 , G06T2207/20221
Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed towards automatic selection of regions for blur kernel estimation. In one embodiment, a process divides a blurred image into a regions. From these regions a first region and a second region can be selected based on a number of edge orientations within the selected regions. A first blur kernel can then be estimated based on the first region and a second blur kernel can be estimated for the second region. The first and second blur kernel can then be utilized to respectively deblur a first and second portion of the image to produce a deblurred image. Other embodiments may be described and/or claimed.
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