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公开(公告)号：US09087390B2
公开(公告)日：2015-07-21
申请号：US13481477
申请日：2012-05-25
申请人： Hailin Jin , Alper Ayvaci , Zhe Lin , Scott D. Cohen
发明人： Hailin Jin , Alper Ayvaci , Zhe Lin , Scott D. Cohen
CPC分类号： G06T3/4053 , G06T3/4076 , G06T5/002
摘要： A method, system, and computer-readable storage medium are disclosed for upscaling an image sequence. An upsampled frame is generated based on an original frame in an original image sequence comprising a plurality of frames. A smoothed image sequence is generated based on the original image sequence. A plurality of patches are determined in the upsampled frame. Each patch comprises a subset of image data in the upsampled frame. Locations of a plurality of corresponding patches are determined in a neighboring set of the plurality of frames in the smoothed image sequence. A plurality of high-frequency patches are generated. Each high-frequency patch is based on image data at the locations of the corresponding patches in the original image sequence. The plurality of high-frequency patches are added to the upsampled frame to generate a high-quality upscaled frame.
摘要翻译： 公开了一种用于升高图像序列的方法，系统和计算机可读存储介质。 基于包括多个帧的原始图像序列中的原始帧生成上采样帧。 基于原始图像序列生成平滑图像序列。 在上采样帧中确定多个补丁。 每个贴片包括上采样帧中的图像数据的子集。 在平滑图像序列中的多个帧的相邻集合中确定多个对应的片段的位置。 产生多个高频补丁。 每个高频片基于原始图像序列中相应片段位置处的图像数据。 将多个高频贴片添加到上采样帧以产生高质量的放大的帧。
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2.发明授权Robust patch regression based on in-place self-similarity for image upscaling 有权基于图像放大的就地自相似性的鲁棒贴片回归公开(公告)号：US08687923B2
公开(公告)日：2014-04-01
申请号：US13565411
申请日：2012-08-02
申请人： Zhe Lin , Scott D. Cohen , Jen-Chan Chien , Sarah A. Kong , Jianchao Yang
发明人： Zhe Lin , Scott D. Cohen , Jen-Chan Chien , Sarah A. Kong , Jianchao Yang
CPC分类号： G06T3/4053
摘要： Methods and systems for image upscaling are disclosed. In one embodiment, a low frequency band image intermediate is obtained from an input image. The input image is upsampled by a scale factor to obtain an upsampled image intermediate. A result image is estimated based at least in part on the upsampled image intermediate, the low frequency band image intermediate, and the input image, wherein the input image is of a smaller scale than the result image.
摘要翻译： 公开了用于图像放大的方法和系统。 在一个实施例中，从输入图像获得低频带图像中间体。 输入图像由比例因子上采样，以获得上采样图像中间值。 至少部分地基于上采样图像中间，低频带图像中间和输入图像来估计结果图像，其中输入图像比结果图像小一些。
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公开(公告)号：US08655109B2
公开(公告)日：2014-02-18
申请号：US13565334
申请日：2012-08-02
申请人： Zhe Lin , Scott D. Cohen , Jen-Chan Chien , Sarah A. Kong , Jianchao Yang
发明人： Zhe Lin , Scott D. Cohen , Jen-Chan Chien , Sarah A. Kong , Jianchao Yang
CPC分类号： G06T3/4053
摘要： Methods and systems for a regression-based learning model in image upscaling are disclosed. In one embodiment, a set of image patch pairs for each of a set of images is generated. Each of the image patch pairs contains a natural image and a corresponding downscaled lower-resolution image. A regression model based at least in part on the set of image patch pairs is defined. The regression model represents a gradient of a function of the downscaled lower-resolution image. An image is upscaled based at least in part on the regression model.
摘要翻译： 公开了一种基于回归的学习模型在图像放大中的方法和系统。 在一个实施例中，生成用于一组图像中的每一个的一组图像补丁对。 每个图像补丁对包含自然图像和对应的缩小的较低分辨率图像。 定义了至少部分基于图像补丁对集合的回归模型。 回归模型表示缩小的较低分辨率图像的函数的梯度。 至少部分基于回归模型，图像被放大。
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公开(公告)号：US08542923B2
公开(公告)日：2013-09-24
申请号：US13493620
申请日：2012-06-11
IPC分类号： G06K9/00
摘要： Methods, systems, and apparatus, including computer program products, feature receiving user input defining a sample of pixels from an image, the image being defined by a raster of pixels. While receiving the user input, the following actions are performed one or more times: pixels are coherently classified in the raster of pixels as being foreground or background based on the sample of pixels; and a rendering of the image is updated on a display to depict classified foreground pixels and background pixels as the sample is being defined.
摘要翻译： 方法，系统和装置，包括计算机程序产品，特征在于接收从图像中定义像素样本的用户输入，所述图像由像素光栅定义。 在接收用户输入时，执行以下动作一次或多次：基于像素样本，像素被相干地分类为像素的光栅作为前景或背景; 并且在显示器上更新图像的呈现以描绘正在定义样本的分类的前景像素和背景像素。
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5.发明授权公开(公告)号：US08503801B2
公开(公告)日：2013-08-06
申请号：US12956996
申请日：2010-11-30
IPC分类号： G06K9/62
CPC分类号： G06T11/60 , G06K9/209 , G06K9/40 , G06K9/4647 , G06K9/6278
摘要： A blur classification module may compute the probability that a given pixel in a digital image was blurred using a given two-dimensional blur kernel, and may store the computed probability in a blur classification probability matrix that stores probability values for all combinations of image pixels and the blur kernels in a set of likely blur kernels. Computing these probabilities may include computing a frequency power spectrum for windows into the digital image and/or for the likely blur kernels. The blur classification module may generate a coherent mapping between pixels of the digital image and respective blur states, or may perform a segmentation of the image into blurry and sharp regions, dependent on values stored in the matrix. Input image data may be pre-processed. Blur classification results may be employed in image editing operations to automatically target image subjects or background regions, or to estimate the depth of image elements.
摘要翻译： 模糊分类模块可以使用给定的二维模糊核心来计算数字图像中的给定像素模糊的概率，并且可以将所计算的概率存储在模糊分类概率矩阵中，所述模糊分类概率矩阵存储图像像素的所有组合的概率值， 一组可能的模糊内核中的模糊内核。 计算这些概率可以包括计算窗口进入数字图像和/或可能的模糊内核的频率功率谱。 模糊分类模块可以产生数字图像的像素和相应的模糊状态之间的相干映射，或者可以根据存储在矩阵中的值来执行图像到模糊和锐利区域的分割。 可以预处理输入图像数据。 可以在图像编辑操作中使用模糊分类结果来自动对象图像对象或背景区域，或者估计图像元素的深度。
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公开(公告)号：US20130083021A1
公开(公告)日：2013-04-04
申请号：US13629309
申请日：2012-09-27
IPC分类号： G06T17/00
CPC分类号： G06T17/00 , G06T19/00 , H04N13/246 , H04N13/271 , H04N13/275
摘要： Embodiments of methods and systems for stereo-aware image editing are described. A three-dimensional model of a stereo scene is built from one or more input images. Camera parameters for the input images are computed. The three-dimensional model is modified. In some embodiments, the modifying the three-dimensional model includes modifying one or more of the images and applying results of the modifying one or more of the images to corresponding model vertices. The scene is re-rendered from the camera parameters to produce an edited stereo pair that is consistent with the three-dimensional model.
摘要翻译： 描述了用于立体感知图像编辑的方法和系统的实施例。 一个立体场景的三维模型是由一个或多个输入图像构成的。 计算输入图像的相机参数。 修改三维模型。 在一些实施例中，修改三维模型包括修改一个或多个图像并将修改一个或多个图像的结果应用于对应的模型顶点。 从相机参数重新渲染场景，以产生与三维模型一致的编辑立体声对。
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7.发明申请System and Method for Estimating Spatially Varying Defocus Blur in a Digital Image 有权用于估计数字图像中空间变化的散焦模糊的系统和方法公开(公告)号：US20130071028A1
公开(公告)日：2013-03-21
申请号：US13562618
申请日：2012-07-31
申请人： Stepen N. Schiller , Scott D. Cohen , Xiang Zhu
发明人： Stepen N. Schiller , Scott D. Cohen , Xiang Zhu
IPC分类号： G06K9/34
CPC分类号： G06T5/003 , G06T7/11 , G06T2207/10024 , G06T2207/20064 , G06T2207/20076
摘要： An image editing application (or a blur classification module thereof) may automatically estimate a coherent defocus blur map from a single input image. The application may represent the blur spectrum as a differentiable function of radius r, and the optimal radius may be estimated by optimizing the likelihood function through a gradient descent algorithm. The application may generate the spectrum function over r through polynomial-based fitting. After fitting, the application may generate look-up tables to store values for the spectrum and for its first and second order derivatives, respectively. The use of these tables in the likelihood optimization process may significantly reduce the computational costs of a given blur estimation exercise. The application may minimize an energy function that includes a data term, a smoothness term, and a smoothness parameter that is adaptive to local image content. The output blur map may be used for image object depth estimation.
摘要翻译： 图像编辑应用（或其模糊分类模块）可以从单个输入图像自动估计相干散焦模糊图。 应用可以将模糊光谱表示为半径r的可微分函数，并且可以通过梯度下降算法优化似然函数来估计最佳半径。 该应用可以通过基于多项式的拟合来生成基于r的频谱函数。 在拟合之后，应用程序可以生成查找表以分别存储频谱的值和其第一和第二阶导数。 在可能性优化过程中使用这些表可以显着降低给定模糊估计练习的计算成本。 应用可以最小化能量函数，其包括适应于局部图像内容的数据项，平滑度项和平滑度参数。 输出模糊图可以用于图像对象深度估计。
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公开(公告)号：US20130034313A1
公开(公告)日：2013-02-07
申请号：US13565334
申请日：2012-08-02
申请人： Zhe Lin , Scott D. Cohen , Jen-Chan Chien , Sarah A. Kong , Jianchao Yang
发明人： Zhe Lin , Scott D. Cohen , Jen-Chan Chien , Sarah A. Kong , Jianchao Yang
IPC分类号： G06K9/32
CPC分类号： G06T3/4053
摘要： Methods and systems for a regression-based learning model in image upscaling are disclosed. In one embodiment, a set of image patch pairs for each of a set of images is generated. Each of the image patch pairs contains a natural image and a corresponding downscaled lower-resolution image. A regression model based at least in part on the set of image patch pairs is defined. The regression model represents a gradient of a function of the downscaled lower-resolution image. An image is upscaled based at least in part on the regression model.
摘要翻译： 公开了一种基于回归的学习模型在图像放大中的方法和系统。 在一个实施例中，生成用于一组图像中的每一个的一组图像补丁对。 每个图像补丁对包含自然图像和对应的缩小的较低分辨率图像。 定义了至少部分基于图像补丁对集合的回归模型。 回归模型表示缩小的较低分辨率图像的函数的梯度。 至少部分基于回归模型，图像被放大。
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公开(公告)号：US20130034311A1
公开(公告)日：2013-02-07
申请号：US13565379
申请日：2012-08-02
申请人： Zhe Lin , Scott D. Cohen , Jen-Chan Chien , Sarah A. Kong , Jianchao Yang
发明人： Zhe Lin , Scott D. Cohen , Jen-Chan Chien , Sarah A. Kong , Jianchao Yang
IPC分类号： G06K9/40
CPC分类号： G06T3/4053
摘要： Methods and systems for denoising and artifact removal in image upscaling are disclosed. In one embodiment, a low frequency band image intermediate is obtained from an input image. An upsampled image intermediate is obtained from the input image by upsampling. A result image is estimated, based at least in part on the upsampled image intermediate, the low frequency band image intermediate, and the input image. The input image is of a smaller scale than the result image. The estimating the result image further includes eliminating from the result image noise that is present in the input image.
摘要翻译： 公开了在图像升高中去除和去除伪影的方法和系统。 在一个实施例中，从输入图像获得低频带图像中间体。 通过上采样从输入图像获得上采样图像中间值。 至少部分地基于上采样图像中间，低频带图像中间和输入图像来估计结果图像。 输入图像的尺寸小于结果图像。 估计结果图像还包括消除输入图像中存在的结果图像噪声。
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公开(公告)号：US20120294529A1
公开(公告)日：2012-11-22
申请号：US13493620
申请日：2012-06-11
IPC分类号： G06K9/34
摘要： Methods, systems, and apparatus, including computer program products, feature receiving user input defining a sample of pixels from an image, the image being defined by a raster of pixels. While receiving the user input, the following actions are performed one or more times: pixels are coherently classified in the raster of pixels as being foreground or background based on the sample of pixels; and a rendering of the image is updated on a display to depict classified foreground pixels and background pixels as the sample is being defined.
摘要翻译： 方法，系统和装置，包括计算机程序产品，特征在于接收从图像中定义像素样本的用户输入，所述图像由像素光栅定义。 在接收用户输入时，执行以下动作一次或多次：基于像素样本，像素被相干地分类为像素的光栅作为前景或背景; 并且在显示器上更新图像的呈现以描绘正在定义样本的分类的前景像素和背景像素。
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