公开(公告)号：US08805104B1

公开(公告)日：2014-08-12

申请号：US13105610

申请日：2011-05-11

申请人： Michele Covell ,  Vivek Kwatra ,  Mei Han ,  Saurabh Mathur ,  Shumeet Baluja

发明人： Michele Covell ,  Vivek Kwatra ,  Mei Han ,  Saurabh Mathur ,  Shumeet Baluja

IPC分类号： G06K9/36

CPC分类号： H04N19/97

摘要： An image processing system is provided for encoding images based on example-based compression. The system selects a set of candidate dictionary predictor entries to encode a portion of an image based at least in part on the neighbors of the portion. The spatial continuity between portions of the image is exploited by the image processing system by selecting corresponding dictionary predictor entries that have the same offset vector as the portion of the image and its neighboring portions.

摘要翻译： 提供了一种基于基于实例的压缩来对图像进行编码的图像处理系统。 该系统至少部分地基于该部分的邻居来选择一组候选词典预测变量条目以对图像的一部分进行编码。 图像部分之间的空间连续性由图像处理系统通过选择与图像及其相邻部分具有相同偏移矢量的相应词典预测词条来利用。

公开(公告)号：US08724701B1

公开(公告)日：2014-05-13

申请号：US13088856

申请日：2011-04-18

申请人： Michele Covell ,  Vivek Kwatra ,  Mei Han ,  Saurabh Mathur ,  Shumeet Baluja

发明人： Michele Covell ,  Vivek Kwatra ,  Mei Han ,  Saurabh Mathur ,  Shumeet Baluja

IPC分类号： H04N7/12 ,  H04N11/02

CPC分类号： H04N19/23 ,  H04N19/94

摘要： An image processing system is provided for encoding videos based on example-based compression. To select the dictionary predictor entries to encode a video, the image processing system reduces the complexity of the video by decomposing the video into smaller pieces. By breaking the video into the simpler pieces, it is easier to locate dictionary predictor entries that are similar to the pieces of the video. The image processing system may decompose the video into one more space-time tubes. For each space-time tube, the image processing system selects dictionary predictor entries to encode the tube.

摘要翻译： 提供了一种基于基于实例的压缩来对视频进行编码的图像处理系统。 为了选择字典预测器条目来编码视频，图像处理系统通过将视频分解成较小的部分来降低视频的复杂性。 通过将视频分解成更简单的部分，可以更容易地找到类似于视频片段的字典预测变量条目。 图像处理系统可以将视频分解成更多的时空管。 对于每个时空管，图像处理系统选择字典预测器条目来对管进行编码。

公开(公告)号：US08515193B1

公开(公告)日：2013-08-20

申请号：US13083493

申请日：2011-04-08

申请人： Mei Han ,  Michele Covell ,  Saurabh Mathur ,  Shumeet Baluja ,  Vivek Kwatra

发明人： Mei Han ,  Michele Covell ,  Saurabh Mathur ,  Shumeet Baluja ,  Vivek Kwatra

IPC分类号： G06K9/36

CPC分类号： G06K9/6219 ,  G06K9/6807 ,  H04N19/30 ,  H04N19/90

摘要： An exemplar dictionary is built from example image blocks for determining predictor blocks for encoding and decoding images. The exemplar dictionary comprises a hierarchical organization of example image blocks. The hierarchical organization of image blocks is obtained by clustering a set of example image blocks, for example, based on k-means clustering. Performance of clustering is improved by transforming feature vectors representing the image blocks to fewer dimensions. Principal component analysis is used for determining feature vectors with fewer dimensions. The clustering performed at higher levels of the hierarchy uses fewer dimensions of feature vectors compared to lower levels of hierarchy. Performance of clustering is improved by processing only a sample of the image blocks of a cluster. The clustering performed at higher levels of the hierarchy uses lower sampling rates as compared to lower levels of hierarchy.

摘要翻译： 从用于确定用于对图像进行编码和解码的预测器块的示例图像块构建示范字典。 示例性字典包括示例图像块的分级组织。 通过例如基于k均值聚类来聚类一组示例图像块来获得图像块的分级组织。 通过将表示图像块的特征向量变换为较少的维度来提高聚类的性能。 主成分分析用于确定尺寸较小的特征向量。 在层次较高的层次上执行的聚类与较低级别的层次相比，使用较少的特征向量维度。 通过仅处理集群的图像块的样本来提高聚类的性能。 与较低级别的层次相比，在较高层次上执行的聚类使用较低的采样率。

公开(公告)号：US08712930B1

公开(公告)日：2014-04-29

申请号：US13100872

申请日：2011-05-04

申请人： Michele Covell ,  Mei Han ,  Saurabh Mathur ,  Shumeet Baluja ,  Vivek Kwatra

发明人： Michele Covell ,  Mei Han ,  Saurabh Mathur ,  Shumeet Baluja ,  Vivek Kwatra

IPC分类号： G06F15/18

CPC分类号： G06K9/6202 ,  G06F17/30247 ,  G06K9/00684 ,  G06K9/4604 ,  G06K9/6267 ,  G06K9/6292 ,  G06K9/66 ,  G06T1/0021 ,  H04N19/105 ,  H04N19/17 ,  H04N19/189

摘要： An exemplar dictionary is built from exemplars of digital content for determining predictor blocks for encoding and decoding digital content. The exemplar dictionary organizes the exemplars as clusters of similar exemplars. Each cluster is mapped to a label. Machine learning techniques are used to generate a prediction model for predicting a label for an exemplar. The exemplar dictionary is used to encode digital content. Clusters of exemplars are obtained by applying a prediction model to a target block of digital content for encoding. A predictor block is selected for encoding the target block based on frequency of occurrence of exemplars in the clusters. The target block is encoded using the predictor block.

摘要翻译： 由数字内容的示例构建示范字典，用于确定用于对数字内容进行编码和解码的预测器块。 示范字典将样本组织成类似样本的集群。 每个集群映射到一个标签。 机器学习技术用于生成用于预测样本的标签的预测模型。 示范字典用于对数字内容进行编码。 通过将预测模型应用于用于编码的数字内容的目标块来获得样本簇。 基于群集中的样本的出现频率，选择预测块来对目标块进行编码。 使用预测器块对目标块进行编码。

公开(公告)号：US08478057B1

公开(公告)日：2013-07-02

申请号：US12692574

申请日：2010-01-22

申请人： Jingyu Cui ,  Vivek Kwatra ,  Michele Covell ,  Mei Han ,  Saurabh Mathur

发明人： Jingyu Cui ,  Vivek Kwatra ,  Michele Covell ,  Mei Han ,  Saurabh Mathur

IPC分类号： G06K9/36

CPC分类号： G06T9/004 ,  G06K9/6219

摘要： Compression of an image is performed based on prediction of target blocks of an image from candidate source blocks of the image. Heuristics are used for identifying the candidate source blocks, for example, source blocks are selected from within a cluster of similar blocks obtained by K-means clustering. For each target block, a region adjacent to the target block is identified and a set of candidate source blocks along with candidate source regions adjacent to the candidate source blocks are identified. The candidate source regions are ranked based on the differences between the candidate source regions and the target source region. Each candidate source block is described using its rank and residual information describing differences between the candidate source block and the target block. The candidate source block that can be described using a minimum amount of information is selected for predicting the target block.

摘要翻译： 基于来自图像的候选源块的图像的目标块的预测来执行图像的压缩。 启发式用于识别候选源块，例如，从通过K均值聚类获得的相似块的簇内选择源块。 对于每个目标块，识别与目标块相邻的区域，并且识别一组候选源块以及与候选源块相邻的候选源区。 基于候选源区域和目标源区域之间的差异对候选源区域进行排序。 使用其等级和残差信息描述候选源块和目标块之间的差异来描述每个候选源块。 选择可以使用最小量的信息描述的候选源块用于预测目标块。

公开(公告)号：US08938119B1

公开(公告)日：2015-01-20

申请号：US13461482

申请日：2012-05-01

申请人： Mei Han ,  Vivek Kwatra ,  Shengyang Dai ,  Sergey Ioffe

发明人： Mei Han ,  Vivek Kwatra ,  Shengyang Dai ,  Sergey Ioffe

IPC分类号： G06K9/00

CPC分类号： G06K9/4661 ,  G06T5/008

摘要： An image comprising color pixels with varying illumination is selected. Instances of a repeating pattern in the image are determined. Illumination values for illuminated pixels at locations within instances of the repeating pattern are calculated based on pixel intensities of non-illuminated pixels at corresponding locations in other instances of the repeating pattern. The illumination variation is removed from the illuminated pixels based on the calculated illumination values to produce enhanced pixels. Color from the non-illuminated pixels at the corresponding locations in other instances of the repeating pattern is propagated to the enhanced pixels.

摘要翻译： 选择包括具有变化的照明的彩色像素的图像。 确定图像中的重复图案的实例。 基于重复图案的其他实例中的相应位置处的非照明像素的像素强度来计算在重复图案的实例内的位置处的照明像素的照明值。 基于所计算的照明值，从照明像素去除照明变化以产生增强像素。 来自重复图案的其他实例中的相应位置处的非照明像素的颜色被传播到增强像素。

公开(公告)号：US08867859B1

公开(公告)日：2014-10-21

申请号：US13610479

申请日：2012-09-11

申请人： Vivek Kwatra ,  Mei Han ,  Shengyang Dai

发明人： Vivek Kwatra ,  Mei Han ,  Shengyang Dai

IPC分类号： G06K9/40

CPC分类号： G06T5/008 ,  G06K9/2036 ,  G06K9/4661

摘要： An image comprising varying illumination is selected. Instances of a repeating pattern in the image is determined. Illumination values for pixels at locations within instances of the repeating pattern are calculated responsive to pixel intensities of pixels at corresponding locations in other instances of the repeating pattern. The varying illumination is removed form the image responsive to the illumination values.

摘要翻译： 选择包括变化照明的图像。 确定图像中重复图案的实例。 响应于重复图案的其他实例中的相应位置处的像素的像素强度来计算在重复图案的实例内的位置处的像素的照明值。 根据照明值从图像中去除变化的照明。

公开(公告)号：US08385662B1

公开(公告)日：2013-02-26

申请号：US12432989

申请日：2009-04-30

申请人： Sangho Yoon ,  Jay Yagnik ,  Mei Han ,  Vivek Kwatra

发明人： Sangho Yoon ,  Jay Yagnik ,  Mei Han ,  Vivek Kwatra

IPC分类号： G06K9/62

CPC分类号： G06K9/6247 ,  G06K9/6223

摘要： Clustering algorithms such as k-means clustering algorithm are used in applications that process entities with spatial and/or temporal characteristics, for example, media objects representing audio, video, or graphical data. Feature vectors representing characteristics of the entities are partitioned using clustering methods that produce results sensitive to an initial set of cluster seeds. The set of initial cluster seeds is generated using principal component analysis of either the complete feature vector set or a subset thereof. The feature vector set is divided into a desired number of initial clusters and a seed determined from each initial cluster.

摘要翻译： 诸如k均值聚类算法的聚类算法被用于处理具有空间和/或时间特征的实体的应用中，例如表示音频，视频或图形数据的媒体对象。 使用产生对初始集群种子集合敏感的结果的聚类方法对代表实体特征的特征向量进行分区。 使用完整特征向量集或其子集的主成分分析来生成初始簇种子集合。 特征向量集合被分为期望数量的初始簇和从每个初始簇确定的种子。

公开(公告)号：US20120141044A1

公开(公告)日：2012-06-07

申请号：US13308411

申请日：2011-11-30

申请人： Vivek Kwatra ,  Mei Han

发明人： Vivek Kwatra ,  Mei Han

IPC分类号： G06K9/36

CPC分类号： G06T5/008 ,  G06T2207/10032 ,  G06T2207/30181

摘要： An image comprising varying illumination is selected. Patches of pixels from among the plurality of pixels with the image are identified. Similarities between pairs of patches of pixels based on pixel intensities associated with the pairs of patches of pixels are calculated. Illumination values for the plurality of pixels within the image based on the calculated similarities between the pairs of patches of pixels is calculated. The illumination variation from the image is removed based on the calculated illumination values for the plurality of pixels within the image.

摘要翻译： 选择包括变化照明的图像。 识别具有图像的多个像素中的像素的补片。 计算基于与像素块对相关联的像素强度的像素块之间的相似性。 基于所计算的像素块对的相似度，计算图像内的多个像素的照明值。 基于图像内的多个像素的计算出的照明值来去除来自图像的照明变化。

公开(公告)号：US08798393B2

公开(公告)日：2014-08-05

申请号：US13308411

申请日：2011-11-30

申请人： Vivek Kwatra ,  Mei Han

发明人： Vivek Kwatra ,  Mei Han

IPC分类号： G06K9/40

CPC分类号： G06T5/008 ,  G06T2207/10032 ,  G06T2207/30181

摘要： An image comprising varying illumination is selected. Patches of pixels from among the plurality of pixels with the image are identified. Similarities between pairs of patches of pixels based on pixel intensities associated with the pairs of patches of pixels are calculated. Illumination values for the plurality of pixels within the image based on the calculated similarities between the pairs of patches of pixels is calculated. The illumination variation from the image is removed based on the calculated illumination values for the plurality of pixels within the image.

摘要翻译： 选择包括变化照明的图像。 识别具有图像的多个像素中的像素的补片。 计算基于与像素块对相关联的像素强度的像素块之间的相似性。 基于所计算的像素块对的相似度，计算图像内的多个像素的照明值。 基于图像内的多个像素的计算出的照明值来去除来自图像的照明变化。