公开(公告)号：US20130315478A1

公开(公告)日：2013-11-28

申请号：US13958044

申请日：2013-08-02

Applicant: Adobe Systems Incorporated

Inventor： Stephen N. Schiller ,  Scott D. Cohen ,  Jingnan Wang

IPC: G06T11/60

CPC classification number: G06T11/60 ,  G06K9/209 ,  G06K9/40 ,  G06K9/4647 ,  G06K9/6278

Abstract: 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, and/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.

Abstract translation: 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，和/或可以根据存储在矩阵中的值，将图像分割成模糊和清晰的区域。 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。

公开(公告)号：US08818082B2

公开(公告)日：2014-08-26

申请号：US13958044

申请日：2013-08-02

Applicant: Adobe Systems Incorporated

Inventor： Stephen N. Schiller ,  Scott D. Cohen ,  Jingnan Wang

IPC: G06K9/62 ,  G06K9/20 ,  G06T11/60 ,  G06K9/46 ,  G06K9/40

CPC classification number: G06T11/60 ,  G06K9/209 ,  G06K9/40 ,  G06K9/4647 ,  G06K9/6278

Abstract: 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, and/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.

Abstract translation: 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，和/或可以根据存储在矩阵中的值，将图像分割成模糊和清晰的区域。 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。