公开(公告)号：US20100284626A1

公开(公告)日：2010-11-11

申请号：US12377793

申请日：2007-08-16

申请人： Henrik Malm ,  Eric Warrant ,  Jonas Ambeck-Madsen ,  Hiromichi Yanagihara ,  Magnus Oskarsson

发明人： Henrik Malm ,  Eric Warrant ,  Jonas Ambeck-Madsen ,  Hiromichi Yanagihara ,  Magnus Oskarsson

IPC分类号： G06K9/40

CPC分类号： G06T5/002 ,  G06T5/008 ,  G06T5/40 ,  G06T2207/10016

摘要： A method is disclosed for enhancing the quality of an image dataset, such as, e.g., reducing the noise in a noisy image data set and increasing the contrast in the image data set. The method may be used for processing a sequence of image datasets, e.g. night vision image datasets, wherein said sequence comprises at least two image datasets each having at least two pixels, and wherein each pixel has an intensity value. The method comprises calculating a structure tensor for each pixel in an image dataset comprised in the sequence of image datasets; calculating values in a summation kernel based on said structure tensor for each pixel in said image dataset; calculating a weighted intensity value for each pixel in said first image dataset, using as weights the values in said summation kernel; storing said weighted intensity value for each pixel in said image dataset as a processed intensity value for each corresponding pixel in a processed output image dataset; rotating a local coordinate system in which the summation kernel is described resulting in that the coordinate axes of said local coordinate system coincide with the directions of the eigenvectors of said structure tensor, where said eigenvectors are described in the global coordinate system of the image dataset, and scaling the coordinate axes of the local coordinate system in which the summation kernel is described by an amount related to the eigenvalues of the structure tensor via a width function W(λi)=σi, and wherein said eigenvalues depend on the amount of intensity variation in the direction of their corresponding eigenvectors, the width function being a decreasing function such that w(0)=σmax and lima→∞w=σmin. An apparatus and a computer readable medium are also provided.

摘要翻译： 公开了一种用于增强图像数据集的质量的方法，例如降低噪声图像数据集中的噪声并增加图像数据集中的对比度。 该方法可以用于处理图像数据集的序列，例如， 夜视图像数据集，其中所述序列包括至少两个具有至少两个像素的图像数据集，并且其中每个像素具有强度值。 该方法包括：计算包含在图像数据集序列中的图像数据集中的每个像素的结构张量; 基于所述图像数据集中的每个像素的所述结构张量来计算求和核中的值; 使用所述求和核中的值作为权重来计算所述第一图像数据集中的每个像素的加权强度值; 将所述图像数据集中的每个像素的所述加权强度值存储为处理的输出图像数据集中的每个对应像素的处理强度值; 旋转其中描述了求和核的局部坐标系，导致所述局部坐标系的坐标轴与所述结构张量的特征向量的方向一致，其中所述特征向量在图像数据集的全局坐标系中被描述， 以及通过宽度函数W（λi）=＆sgr; i，将与所述结构张量的特征值相关的量描述所述求和核的所述局部坐标系的坐标轴，并且其中所述特征值取决于 其相应特征向量方向的强度变化，宽度函数是递减函数，使得w（0）=＆sgr; max和lima→∞w=＆sgr; min。 还提供了一种装置和计算机可读介质。

公开(公告)号：US08139889B2

公开(公告)日：2012-03-20

申请号：US12377793

申请日：2007-08-16

申请人： Henrik Malm ,  Eric Warrant ,  Jonas Ambeck-Madsen ,  Hiromichi Yanagihara ,  Magnus Oskarsson

发明人： Henrik Malm ,  Eric Warrant ,  Jonas Ambeck-Madsen ,  Hiromichi Yanagihara ,  Magnus Oskarsson

IPC分类号： G06K9/00 ,  G06K9/40

CPC分类号： G06T5/002 ,  G06T5/008 ,  G06T5/40 ,  G06T2207/10016

摘要： Method for processing a sequence of at least two image datasets each having at least two pixels, each pixel having an intensity value by calculating a structure tensor for each pixel in an image dataset included in the sequence of image datasets; calculating values in a summation kernel based on the structure tensor for each pixel in the image dataset; calculating a weighted intensity value for each pixel in the first image dataset, using as weights the values in the summation kernel; storing the weighted intensity value for each pixel in the image dataset as a processed intensity value for each corresponding pixel in a processed output image dataset; rotating a local coordinate system in which the summation kernel is described so that the coordinate axes of said local coordinate system coincide with the directions of the eigenvectors of the structure tensor.

摘要翻译： 用于处理每个具有至少两个像素的至少两个图像数据集的序列的方法，每个像素通过计算包括在所述图像数据集序列中的图像数据集中的每个像素的结构张量而具有强度值; 基于图像数据集中每个像素的结构张量来计算求和核中的值; 计算第一图像数据集中每个像素的加权强度值，使用求和核中的值作为权重; 将每个像素的加权强度值存储在图像数据集中，作为经处理的输出图像数据集中每个相应像素的处理强度值; 旋转其中描述了求和核的局部坐标系，使得所述局部坐标系的坐标轴与结构张量的特征向量的方向一致。