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公开(公告)号：US09934560B2
公开(公告)日：2018-04-03
申请号：US15081924
申请日：2016-03-27
Applicant: Google Inc.
Inventor： Daniel Pettigrew , Jason Chang , Ronald Frank Wotzlaw , Sevket Derin Babacan , Aravind Krishnaswamy
IPC: G06K9/40 , G06T5/00 , G06F3/0484 , G06K9/00 , G06T5/40 , G11B27/034 , G11B27/34
CPC classification number: G06T5/008 , G06F3/04845 , G06F3/04847 , G06K9/00228 , G06T5/002 , G06T5/007 , G06T5/009 , G06T5/40 , G06T2207/20016 , G11B27/034 , G11B27/34
Abstract: Methods and systems for modifying an image by applying an effect to an image are described. The effects include a pop effect, a light adjustment, or a color adjustment to an image. The methods and systems include providing a user slider for applying an effect to the image. The methods and systems further include determining a first portion of the image including a face and creating a protection mask to protect the face in the first portion during image modification. The protection mask may include an enhancement threshold for modifying the first portion of the image. The modification of the image may include modifying the second portion of the image differently than the first portion of the image. A method for enforcing different resolutions of a same input image to produce similar visual results is also described.
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公开(公告)号：US09582860B2
公开(公告)日：2017-02-28
申请号：US14808208
申请日：2015-07-24
Applicant: Google Inc.
Inventor： Timothy Sepkoski St. Clair , Tinglin Liu , Sevket Derin Babacan
CPC classification number: G06T5/002 , G06K9/00536 , G06K9/00711 , G06K9/40 , G06K9/6256 , G06K9/66 , G06T5/20 , G06T5/50 , G06T2207/10016
Abstract: Implementations generally relate to enhancing a video. In some implementations, a method includes classifying one or more objects in one or more frames of the video. The method further includes determining one or more filter parameters of one or more filters based on the classifying of the one or more objects. The method further includes smoothing one or more of the determined filter parameters based on the classifying of the one or more objects. The method further includes applying one or more of the filters with corresponding smoothed filter parameters to one or more frames of the video.
Abstract translation: 实施通常涉及增强视频。 在一些实现中，一种方法包括对视频的一个或多个帧中的一个或多个对象进行分类。 该方法还包括基于一个或多个对象的分类来确定一个或多个过滤器的一个或多个过滤器参数。 该方法还包括基于一个或多个对象的分类来平滑一个或多个所确定的过滤器参数。 该方法还包括将一个或多个具有对应的平滑滤波器参数的滤波器应用于视频的一个或多个帧。
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13.发明授权Noise estimation for images using polynomial relationship for pixel values of image features 有权使用图像特征像素值的多项式关系的图像噪声估计公开(公告)号：US09330340B1
公开(公告)日：2016-05-03
申请号：US14704918
申请日：2015-05-05
Applicant: Google Inc.
Inventor： Stephen Joseph Diverdi , Sevket Derin Babacan , Aravind Krishnaswamy
CPC classification number: G06T7/0002 , G06T2207/30168
Abstract: Implementations relate to estimating noise in images using a polynomial relationship for pixel values of image features. In some implementations, a computer-implemented method to estimate noise in an image includes determining a plurality of patches of pixels in the image. For each patch of pixels, the method determines feature pixels in the patch that are included in a particular image feature at least partially depicted in the patch. The method determines an error estimate for each patch of pixels, where each error estimate is based on an amount by which pixel values of the feature pixels in the patch of pixels are different from an estimated polynomial relationship between the feature pixels in the patch of pixels. One of the error estimates is selected as a noise level estimate for the image.
Abstract translation: 实现涉及使用图像特征的像素值的多项式关系来估计图像中的噪声。 在一些实现中，用于估计图像中的噪声的计算机实现的方法包括确定图像中的多个像素块。 对于每个像素块，该方法确定补丁中包括在补丁中至少部分描绘的特定图像特征中的特征像素。 该方法确定每个像素块的误差估计，其中每个误差估计基于像素块中的特征像素的像素值与像素块中的特征像素之间的估计多项式关系不同的量 。 选择其中一个误差估计作为图像的噪声水平估计。
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Patent Agency Ranking
公开(公告)号：US20140341466A1
公开(公告)日：2014-11-20
申请号：US13894364
申请日：2013-05-14
Applicant: Google Inc.
Inventor： Sevket Derin Babacan
IPC: G06K9/40
Abstract: Implementations relate to estimating noise in images. In some implementations, a method includes extracting a plurality of sample blocks of pixels from a received image, where each sample block includes a subset of pixels of the image. One or more of the sample blocks are examined for texture content based on whether the sample blocks include one or more edges based on a predetermined threshold. At least one sample block determined to include texture content is removed. The method determines one or more average color variances based on the remaining sample blocks that have not been removed, where noise estimations for the image are based on the average color variances.
Abstract translation: 实现涉及估计图像噪声。 在一些实现中，一种方法包括从接收到的图像提取多个像素样本块，其中每个样本块包括图像的像素子集。 基于样本块是否包括基于预定阈值的一个或多个边缘来检查样本块中的一个或多个样本块的纹理内容。 确定包含纹理内容的至少一个采样块被去除。 该方法基于尚未被去除的剩余样本块确定一个或多个平均颜色方差，其中图像的噪声估计基于平均颜色方差。
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公开(公告)号：US10380447B1
公开(公告)日：2019-08-13
申请号：US14555120
申请日：2014-11-26
Applicant: Google Inc.
Inventor： Krzysztof Kulewski , Aravind Krishnaswamy , Sevket Derin Babacan
Abstract: Implementations generally relate to providing regions of interest in an image. In some implementations, a method includes receiving an image. The method further includes determining one or more image features. The method further includes grouping the one or more image features into one or more regions of interest.
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公开(公告)号：US09519957B1
公开(公告)日：2016-12-13
申请号：US14323911
申请日：2014-07-03
Applicant: Google Inc.
Inventor： Krzysztof Kulewski , Aravind Krishnaswamy , Sevket Derin Babacan
CPC classification number: G06T5/008 , G06T19/006 , G06T19/20 , G06T2207/10024 , G06T2207/20208
Abstract: Aspects of the subject technology relate to automatically and selectively applying a fill light filter to an image. A process includes determining an edge-preserved, smoothed version of the image, and determining a grayscale version of the image. The process also includes comparing each pixel of the edge-preserved, smoothed version of the image to each corresponding pixel of the grayscale version of the image. The process also includes applying the fill light filter to the image based on the comparison. The fill light filter is automatically adjusted based on identifying regions in the image. Selectively applying the fill light filter can reduce artifacts and noise from forming or being amplified as a result of the fill light filter.
Abstract translation: 主题技术的方面涉及对图像自动和选择性地应用填充光过滤器。 一个过程包括确定图像的边缘保留，平滑版本，以及确定图像的灰度版本。 该过程还包括将图像的边缘保留，平滑版本的每个像素与图像的灰度版本的每个对应像素进行比较。 该过程还包括基于比较将填充光过滤器应用于图像。 基于图像中的识别区域自动调整补光过滤器。 选择性地施加填充光滤波器可以减少由于填充光滤波器而造成的伪影和噪声而形成或被放大。
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公开(公告)号：US08983152B2
公开(公告)日：2015-03-17
申请号：US13894384
申请日：2013-05-14
Applicant: Google Inc.
Inventor： Justin Lewis , Gavin James , Grayson Lang , Aravind Krishnaswamy , Sevket Derin Babacan
CPC classification number: G06K9/00234 , G06K9/00248 , G06K9/342 , G06K9/4652 , G06T5/002 , G06T5/008 , G06T7/11 , G06T7/194 , G06T2207/10024 , G06T2207/30201
Abstract: In some implementations, a method includes identifying one or more face regions of an image, the face regions including pixels that depict at least a portion of one or more faces of persons. The face regions are identified based on identifying facial landmarks of the faces. The method determines an associated face mask for each of the faces based on the face regions, where each face mask indicates which pixels in the image depict the corresponding face. Face pixels can be selected for processing by applying the face masks, and image pixels outside the faces can be selected by inversely applying the face masks. The selected pixels can be provided to a processing operation for adjustment of the selected pixels.
Abstract translation: 在一些实现中，一种方法包括识别图像的一个或多个面部区域，所述面部区域包括描绘人的一个或多个面部的至少一部分的像素。 基于识别面部的面部标志来识别面部区域。 该方法基于面部区域确定每个面部的相关面罩，其中每个面罩指示图像中的哪些像素描绘对应的面部。 可以通过应用面罩来选择面部像素进行处理，并且可以通过反面应用面罩来选择面部之外的图像像素。 可以将所选择的像素提供给用于调整所选像素的处理操作。
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公开(公告)号：US08953877B2
公开(公告)日：2015-02-10
申请号：US13894364
申请日：2013-05-14
Applicant: Google Inc.
Inventor： Sevket Derin Babacan
Abstract: Implementations relate to estimating noise in images. In some implementations, a method includes extracting a plurality of sample blocks of pixels from a received image, where each sample block includes a subset of pixels of the image. One or more of the sample blocks are examined for texture content based on whether the sample blocks include one or more edges based on a predetermined threshold. At least one sample block determined to include texture content is removed. The method determines one or more average color variances based on the remaining sample blocks that have not been removed, where noise estimations for the image are based on the average color variances.
Abstract translation: 实现涉及估计图像噪声。 在一些实现中，一种方法包括从接收到的图像提取多个像素样本块，其中每个样本块包括图像的像素子集。 基于样本块是否包括基于预定阈值的一个或多个边缘来检查样本块中的一个或多个样本块的纹理内容。 确定包含纹理内容的至少一个采样块被去除。 该方法基于尚未被去除的剩余样本块确定一个或多个平均颜色方差，其中图像的噪声估计基于平均颜色方差。
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