Spatially coherent nearest neighbor fields
    1.
    发明授权
    Spatially coherent nearest neighbor fields 有权
    空间相干最近邻域

    公开(公告)号:US09025822B2

    公开(公告)日:2015-05-05

    申请号:US13794125

    申请日:2013-03-11

    Abstract: In embodiments of spatially coherent nearest neighbor fields, initial matching patches of a nearest neighbor field can be determined at image grid locations of a first digital image and a second digital image. Spatial coherency can be enforced for each matching patch in the second digital image with reference to respective matching patches in the first digital image based on motion data of neighboring matching patches. A multi-resolution iterative process can then update each spatially coherent matching patch based on overlapping grid regions of the matching patches that are evaluated for matching regions of the first and second digital images. An optimal, spatially coherent matching patch can be selected for each of the image grid locations of the first and second digital images based on iterative interaction to enforce the spatial coherency of each matching patch and the multi-resolution iterative process to update each spatially coherent matching patch.

    Abstract translation: 在空间相干最近邻域的实施例中,可以在第一数字图像和第二数字图像的图像网格位置处确定最近邻域的初始匹配块。 基于相邻匹配补丁的运动数据,参考第一数字图像中的相应匹配补丁,可以针对第二数字图像中的每个匹配补丁实施空间一致性。 然后,多分辨率迭代过程可以基于为第一和第二数字图像的匹配区域评估的匹配块的重叠网格区域来更新每个空间相干匹配块。 可以基于迭代交互来选择针对第一和第二数字图像的每个图像网格位置的最佳空间相干匹配块,以强制每个匹配块的空间一致性和多分辨率迭代过程以更新每个空间相干匹配 补丁。

    Optical flow accounting for image haze
    2.
    发明授权
    Optical flow accounting for image haze 有权
    图像浊度的光流量

    公开(公告)号:US09031345B2

    公开(公告)日:2015-05-12

    申请号:US13794408

    申请日:2013-03-11

    CPC classification number: G06T5/003 G06T5/50 G06T7/269 G06T2207/10016

    Abstract: In embodiments of optical flow accounting for image haze, digital images may include objects that are at least partially obscured by a haze that is visible in the digital images, and an estimate of light that is contributed by the haze in the digital images can be determined. The haze can be cleared from the digital images based on the estimate of the light that is contributed by the haze, and clearer digital images can be generated. An optical flow between the clearer digital images can then be computed, and the clearer digital images refined based on the optical flow to further clear the haze from the images in an iterative process to improve visibility of the objects in the digital images.

    Abstract translation: 在考虑图像雾度的光学流量的实施例中,数字图像可以包括由数字图像中可见的雾度至少部分地模糊的对象,并且可以确定由数字图像中的雾度贡献的光的估计 。 可以基于由雾度贡献的光的估计,从数字图像中清除雾度,并且可以产生更清晰的数字图像。 然后可以计算更清晰的数字图像之间的光流,并且基于光流改进更清晰的数字图像,以在迭代过程中进一步清除来自图像的雾度,以提高数字图像中的对象的可视性。

    Optical Flow Accounting for Image Haze
    3.
    发明申请
    Optical Flow Accounting for Image Haze 有权
    图像雾度的光流会计

    公开(公告)号:US20140254943A1

    公开(公告)日:2014-09-11

    申请号:US13794408

    申请日:2013-03-11

    CPC classification number: G06T5/003 G06T5/50 G06T7/269 G06T2207/10016

    Abstract: In embodiments of optical flow accounting for image haze, digital images may include objects that are at least partially obscured by a haze that is visible in the digital images, and an estimate of light that is contributed by the haze in the digital images can be determined The haze can be cleared from the digital images based on the estimate of the light that is contributed by the haze, and clearer digital images can be generated. An optical flow between the clearer digital images can then be computed, and the clearer digital images refined based on the optical flow to further clear the haze from the images in an iterative process to improve visibility of the objects in the digital images.

    Abstract translation: 在考虑图像雾度的光学流量的实施例中,数字图像可以包括由数字图像中可见的雾度至少部分地模糊的对象,并且可以确定由数字图像中的雾度贡献的光的估计 可以基于由雾度贡献的光的估计,从数字图像中清除雾度,并且可以产生更清晰的数字图像。 然后可以计算更清晰的数字图像之间的光流,并且基于光流改进更清晰的数字图像,以在迭代过程中进一步清除来自图像的雾度,以提高数字图像中的对象的可视性。

    Video Denoising Using Optical Flow
    5.
    发明申请
    Video Denoising Using Optical Flow 有权
    视频去噪使用光流

    公开(公告)号:US20150262336A1

    公开(公告)日:2015-09-17

    申请号:US14205027

    申请日:2014-03-11

    Abstract: In techniques for video denoising using optical flow, image frames of video content include noise that corrupts the video content. A reference frame is selected, and matching patches to an image patch in the reference frame are determined from within the reference frame. A noise estimate is computed for previous and subsequent image frames relative to the reference frame. The noise estimate for an image frame is computed based on optical flow, and is usable to determine a contribution of similar motion patches to denoise the image patch in the reference frame. The similar motion patches from the previous and subsequent image frames that correspond to the image patch in the reference frame are determined based on the optical flow computations. The image patch is denoised based on an average of the matching patches from reference frame and the similar motion patches determined from the previous and subsequent image frames.

    Abstract translation: 在使用光流的视频去噪的技术中,视频内容的图像帧包括破坏视频内容的噪声。 选择参考帧,并且从参考帧内确定参考帧中的图像块的匹配补丁。 针对相对于参考帧的先前和后续图像帧计算噪声估计。 基于光流计算图像帧的噪声估计,并且可用于确定类似运动补丁对参考帧中的图像补丁进行去噪的贡献。 基于光流计算确定与参考帧中的图像块相对应的来自先前和后续图像帧的类似运动补丁。 基于来自参考帧的匹配补丁的平均值和从先前和后续图像帧确定的类似运动补丁,去除图像补丁。

    Video denoising using optical flow
    6.
    发明授权
    Video denoising using optical flow 有权
    视频去噪使用光流

    公开(公告)号:US09311690B2

    公开(公告)日:2016-04-12

    申请号:US14205027

    申请日:2014-03-11

    Abstract: In techniques for video denoising using optical flow, image frames of video content include noise that corrupts the video content. A reference frame is selected, and matching patches to an image patch in the reference frame are determined from within the reference frame. A noise estimate is computed for previous and subsequent image frames relative to the reference frame. The noise estimate for an image frame is computed based on optical flow, and is usable to determine a contribution of similar motion patches to denoise the image patch in the reference frame. The similar motion patches from the previous and subsequent image frames that correspond to the image patch in the reference frame are determined based on the optical flow computations. The image patch is denoised based on an average of the matching patches from reference frame and the similar motion patches determined from the previous and subsequent image frames.

    Abstract translation: 在使用光流的视频去噪的技术中,视频内容的图像帧包括破坏视频内容的噪声。 选择参考帧,并且从参考帧内确定参考帧中的图像块的匹配补丁。 针对相对于参考帧的先前和后续图像帧计算噪声估计。 基于光流计算图像帧的噪声估计,并且可用于确定类似运动补丁对参考帧中的图像补丁进行去噪的贡献。 基于光流计算确定与参考帧中的图像块相对应的来自先前和后续图像帧的类似运动补丁。 基于来自参考帧的匹配补丁的平均值和从先前和后续图像帧确定的类似运动补丁,去除图像补丁。

    Spatially Coherent Nearest Neighbor Fields
    7.
    发明申请
    Spatially Coherent Nearest Neighbor Fields 有权
    空间相干最近邻域

    公开(公告)号:US20140254933A1

    公开(公告)日:2014-09-11

    申请号:US13794125

    申请日:2013-03-11

    Abstract: In embodiments of spatially coherent nearest neighbor fields, initial matching patches of a nearest neighbor field can be determined at image grid locations of a first digital image and a second digital image. Spatial coherency can be enforced for each matching patch in the second digital image with reference to respective matching patches in the first digital image based on motion data of neighboring matching patches. A multi-resolution iterative process can then update each spatially coherent matching patch based on overlapping grid regions of the matching patches that are evaluated for matching regions of the first and second digital images. An optimal, spatially coherent matching patch can be selected for each of the image grid locations of the first and second digital images based on iterative interaction to enforce the spatial coherency of each matching patch and the multi-resolution iterative process to update each spatially coherent matching patch.

    Abstract translation: 在空间相干最近邻域的实施例中,可以在第一数字图像和第二数字图像的图像网格位置处确定最近邻域的初始匹配块。 基于相邻匹配补丁的运动数据,参考第一数字图像中的相应匹配补丁,可以针对第二数字图像中的每个匹配补丁实施空间一致性。 然后,多分辨率迭代过程可以基于为第一和第二数字图像的匹配区域评估的匹配块的重叠网格区域来更新每个空间相干匹配块。 可以基于迭代交互来选择针对第一和第二数字图像的每个图像网格位置的最佳空间相干匹配块,以强制每个匹配块的空间一致性和多分辨率迭代过程以更新每个空间相干匹配 补丁。

    Statistics of Nearest Neighbor Fields
    8.
    发明申请
    Statistics of Nearest Neighbor Fields 有权
    最近邻域的统计

    公开(公告)号:US20140254881A1

    公开(公告)日:2014-09-11

    申请号:US13794219

    申请日:2013-03-11

    CPC classification number: G06T7/2013 G06T7/215 G06T7/223 G06T7/248

    Abstract: In embodiments of statistics of nearest neighbor fields, matching patches of a nearest neighbor field can be determined at image grid locations of a first digital image and a second digital image. A motion field can then be determined based on motion data of the matching patches. Predominant motion components of the motion field can be determined based on statistics of the motion data to generate a final motion field. The predominant motion components correspond to a motion of objects as represented by a displacement between the first and second digital images. One of the predominant motion components can then be assigned to each of the matching patches to optimize the final motion field of the matching patches.

    Abstract translation: 在最近邻域的统计的实施例中,可以在第一数字图像和第二数字图像的图像网格位置处确定最近邻域的匹配块。 然后可以基于匹配补丁的运动数据来确定运动场。 可以基于运动数据的统计来确定运动场的主要运动分量以产生最终运动场。 主要运动分量对应于由第一和第二数字图像之间的位移表示的物体的运动。 然后可以将主要运动分量中的一个分配给每个匹配补丁以优化匹配补丁的最终运动场。

    Video Denoising using Optical Flow
    9.
    发明申请
    Video Denoising using Optical Flow 审中-公开
    视频去噪使用光流

    公开(公告)号:US20160191753A1

    公开(公告)日:2016-06-30

    申请号:US15063240

    申请日:2016-03-07

    Abstract: In techniques for video denoising using optical flow, image frames of video content include noise that corrupts the video content. A reference frame is selected, and matching patches to an image patch in the reference frame are determined from within the reference frame. A noise estimate is computed for previous and subsequent image frames relative to the reference frame. The noise estimate for an image frame is computed based on optical flow, and is usable to determine a contribution of similar motion patches to denoise the image patch in the reference frame. The similar motion patches from the previous and subsequent image frames that correspond to the image patch in the reference frame are determined based on the optical flow computations. The image patch is denoised based on an average of the matching patches from reference frame and the similar motion patches determined from the previous and subsequent image frames.

    Abstract translation: 在使用光流的视频去噪的技术中,视频内容的图像帧包括破坏视频内容的噪声。 选择参考帧,并且从参考帧内确定参考帧中的图像块的匹配补丁。 针对相对于参考帧的先前和后续图像帧计算噪声估计。 基于光流计算图像帧的噪声估计,并且可用于确定类似运动补丁对参考帧中的图像补丁进行去噪的贡献。 基于光流计算确定与参考帧中的图像块相对应的来自先前和后续图像帧的类似运动补丁。 基于来自参考帧的匹配补丁的平均值和从先前和后续图像帧确定的类似运动补丁,去除图像补丁。

    Statistics of nearest neighbor fields
    10.
    发明授权
    Statistics of nearest neighbor fields 有权
    最近邻域的统计

    公开(公告)号:US09165373B2

    公开(公告)日:2015-10-20

    申请号:US13794219

    申请日:2013-03-11

    CPC classification number: G06T7/2013 G06T7/215 G06T7/223 G06T7/248

    Abstract: In embodiments of statistics of nearest neighbor fields, matching patches of a nearest neighbor field can be determined at image grid locations of a first digital image and a second digital image. A motion field can then be determined based on motion data of the matching patches. Predominant motion components of the motion field can be determined based on statistics of the motion data to generate a final motion field. The predominant motion components correspond to a motion of objects as represented by a displacement between the first and second digital images. One of the predominant motion components can then be assigned to each of the matching patches to optimize the final motion field of the matching patches.

    Abstract translation: 在最近邻域的统计的实施例中,可以在第一数字图像和第二数字图像的图像网格位置处确定最近邻域的匹配块。 然后可以基于匹配补丁的运动数据来确定运动场。 可以基于运动数据的统计来确定运动场的主要运动分量以产生最终运动场。 主要运动分量对应于由第一和第二数字图像之间的位移表示的物体的运动。 然后可以将主要运动分量中的一个分配给每个匹配补丁以优化匹配补丁的最终运动场。

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