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    • 1. 发明授权
    • Video coding using spatio-temporal texture synthesis
    • 视频编码采用时空纹理合成
    • US08208556B2
    • 2012-06-26
    • US11768862
    • 2007-06-26
    • Xiaoyan SunChunbo ZhuFeng WuShipeng Li
    • Xiaoyan SunChunbo ZhuFeng WuShipeng Li
    • H04N11/04
    • G06T7/40G06T2207/10016H04N19/27H04N19/577
    • Systems and methods for video coding using spatio-temporal texture synthesis are described. In one aspect, a video data coding pipeline portion of the codec removes texture blocks from the video data to generate coded video data. The removed texture blocks are selected based on an objective determination that each of the remove texture blocks can be synthesized from spatio-temporal neighboring samples during decoding operations. The objective determinations are made using local block-based motion information independent of global motion models. An indication of which texture blocks were removed is provided to a decoder in addition to the coded video data. Decoding logic of the codec decodes the video data using a standard decoding algorithm. The decoding logic also restores the removed texture blocks via spatio-temporal texture synthesis to generate synthesized video data. The decoded and synthesized video data is presented to a user.
    • 描述使用时空纹理合成的视频编码的系统和方法。 一方面,编解码器的视频数据编码流水线部分从视频数据中去除纹理块以产生编码视频数据。 基于在解码操作期间可以从空时相邻采样中合成每个去除纹理块的目标确定来选择去除的纹理块。 使用与全局运动模型无关的局部基于块的运动信息进行客观确定。 去除了纹理块的指示除了编码的视频数据之外还提供给解码器。 编解码器的解码逻辑使用标准解码算法解码视频数据。 解码逻辑还通过空间 - 时间纹理合成恢复去除的纹理块,以产生合成的视频数据。 解码和合成的视频数据被呈现给用户。
    • 3. 发明授权
    • Image compression based on parameter-assisted inpainting
    • 基于参数辅助修复的图像压缩
    • US08311347B2
    • 2012-11-13
    • US11558755
    • 2006-11-10
    • Xiaoyan SunFeng WuZhiwei XiongShipeng Li
    • Xiaoyan SunFeng WuZhiwei XiongShipeng Li
    • G06K9/36G06K9/46
    • H04N19/17G06K9/0008G06K9/00744G06T9/00H04N19/134
    • Systems and methods provide image compression based on parameter-assisted inpainting. In one implementation of an encoder, an image is partitioned into blocks and the blocks classified as smooth or unsmooth, based on the degree of visual edge content and chromatic variation in each block. Image content of the unsmooth blocks is compressed, while image content of the smooth blocks is summarized by parameters, but not compressed. The parameters, once obtained, may also be compressed. At a decoder, the compressed image content of the unsmooth blocks and the compressed parameters of the smooth blocks are each decompressed. Each smooth block is then reconstructed by inpainting, guided by the parameters in order to impart visual detail from the original image that cannot be implied from the image content of neighboring blocks that have been decoded.
    • 系统和方法提供基于参数辅助修复的图像压缩。 在编码器的一个实现中,基于每个块中的视觉边缘内容的程度和色度变化,将图像划分为块,并将块分类为平滑或不平滑。 不平滑块的图像内容被压缩,而平滑块的图像内容由参数汇总,但不被压缩。 一旦获得的参数也可以被压缩。 在解码器处,解压缩不平滑块的压缩图像内容和平滑块的压缩参数。 然后通过修饰重建每个平滑块,由参数引导,以便从原始图像传递不能从已经被解码的相邻块的图像内容中隐含的视觉细节。
    • 4. 发明申请
    • Learning-Based Image Compression
    • 基于学习的图像压缩
    • US20090067491A1
    • 2009-03-12
    • US11851653
    • 2007-09-07
    • Xiaoyan SunFeng WuShipeng Li
    • Xiaoyan SunFeng WuShipeng Li
    • G06T9/00
    • H04N19/59H04N19/132H04N19/14H04N19/587H04N19/85H04N19/90
    • Learning-based image compression is described. In one implementation, an encoder possessing a first set of learned visual knowledge primitives excludes visual information from an image prior to compression. A decoder possessing an independently learned set of visual knowledge primitives synthesizes the excluded visual information into the image after decompression. The encoder and decoder are decoupled with respect to the information excluded at the encoder and the information synthesized at the decoder. This results in superior data compression since the information excluded at the encoder is dropped completely and not transferred to the decoder. Primitive visual elements synthesized at the decoder may be different than primitive visual elements dropped at the encoder, but the resulting reconstituted image is perceptually equivalent to the original image.
    • 描述基于学习的图像压缩。 在一个实现中,具有第一组学习视觉知识原语的编码器在压缩之前从图像中排除视觉信息。 具有独立学习的视觉知识图元组的解码器在解压缩之后将排除的视觉信息合成到图像中。 编码器和解码器相对于在编码器处排除的信息和在解码器处合成的信息去耦合。 这导致优异的数据压缩,因为在编码器处排除的信息完全丢弃并且不传送到解码器。 在解码器处合成的原始视觉元素可能不同于在编码器处丢弃的原始视觉元素,但是所产生的重构图像在听觉上等同于原始图像。
    • 6. 发明授权
    • Learning-based image compression
    • 基于学习的图像压缩
    • US08223837B2
    • 2012-07-17
    • US11851653
    • 2007-09-07
    • Xiaoyan SunFeng WuShipeng Li
    • Xiaoyan SunFeng WuShipeng Li
    • H04B1/66H04N7/12H04N11/02H04N11/04
    • H04N19/59H04N19/132H04N19/14H04N19/587H04N19/85H04N19/90
    • Learning-based image compression is described. In one implementation, an encoder possessing a first set of learned visual knowledge primitives excludes visual information from an image prior to compression. A decoder possessing an independently learned set of visual knowledge primitives synthesizes the excluded visual information into the image after decompression. The encoder and decoder are decoupled with respect to the information excluded at the encoder and the information synthesized at the decoder. This results in superior data compression since the information excluded at the encoder is dropped completely and not transferred to the decoder. Primitive visual elements synthesized at the decoder may be different than primitive visual elements dropped at the encoder, but the resulting reconstituted image is perceptually equivalent to the original image.
    • 描述基于学习的图像压缩。 在一个实现中,具有第一组学习视觉知识原语的编码器在压缩之前从图像中排除视觉信息。 具有独立学习的视觉知识图元组的解码器在解压缩之后将排除的视觉信息合成到图像中。 编码器和解码器相对于在编码器处排除的信息和在解码器处合成的信息去耦合。 这导致优异的数据压缩,因为在编码器处排除的信息完全丢弃并且不传送到解码器。 在解码器处合成的原始视觉元素可能不同于在编码器处丢弃的原始视觉元素,但是所产生的重构图像在听觉上等同于原始图像。
    • 7. 发明授权
    • Vision-based compression
    • 基于视觉的压缩
    • US08019171B2
    • 2011-09-13
    • US11736900
    • 2007-04-18
    • Xiaoyan SunFeng WuShipeng LiDong Liu
    • Xiaoyan SunFeng WuShipeng LiDong Liu
    • G06K9/36
    • H04N19/12G06T7/12H04N19/17H04N19/61
    • Systems and methods provide vision-based image compression. In one implementation, inpainting is the vision-based technique selected to augment a conventional signal-processing-based technique. For some regions of a source image, an exemplary system efficiently extracts and organizes structural edge information instead of compressing the regions. In one implementation, the system applies binary curve fitting to capture the edge information. A structure-aware inpainter in the decoder can then restore the regions via the edge information, which occupies very little data space or minimal bandwidth in a bitstream that is transmitted from encoder to decoder. Key visual components of the image can still be conventionally compressed. Extracting edge information for some regions instead of compressing them considerably increases overall image compression.
    • 系统和方法提供基于视觉的图像压缩。 在一个实现中,修复是基于视觉的技术,其被选择用于增加常规的基于信号处理的技术。 对于源图像的一些区域,示例性系统有效地提取并组织结构边缘信息,而不是压缩该区域。 在一个实现中,系统应用二进制曲线拟合来捕获边缘信息。 然后,解码器中的结构感知输入器可以经由边缘信息来恢复区域,该边缘信息在从编码器传送到解码器的比特流中占据非常小的数据空间或最小带宽。 图像的主要视觉部件仍然可以被传统地压缩。 为某些区域提取边缘信息而不是压缩边缘信息显着增加了整体图像压缩。
    • 9. 发明授权
    • Vision-based compression
    • 基于视觉的压缩
    • US08396312B2
    • 2013-03-12
    • US13177434
    • 2011-07-06
    • Xiaoyan SunFeng WuShipeng LiDong Liu
    • Xiaoyan SunFeng WuShipeng LiDong Liu
    • G06K9/36
    • H04N19/12G06T7/12H04N19/17H04N19/61
    • Systems and methods provide vision-based image compression. In one implementation, inpainting is the vision-based technique selected to augment a conventional signal-processing-based technique. For some regions of a source image, an exemplary system efficiently extracts and organizes structural edge information instead of compressing the regions. In one implementation, the system applies binary curve fitting to capture the edge information. A structure-aware inpainter in the decoder can then restore the regions via the edge information, which occupies very little data space or minimal bandwidth in a bitstream that is transmitted from encoder to decoder. Key visual components of the image can still be conventionally compressed. Extracting edge information for some regions instead of compressing them considerably increases overall image compression.
    • 系统和方法提供基于视觉的图像压缩。 在一个实现中,修复是基于视觉的技术,其被选择用于增加常规的基于信号处理的技术。 对于源图像的一些区域,示例性系统有效地提取并组织结构边缘信息,而不是压缩该区域。 在一个实现中,系统应用二进制曲线拟合来捕获边缘信息。 然后,解码器中的结构感知输入器可以经由边缘信息来恢复区域,该边缘信息在从编码器传送到解码器的比特流中占据非常小的数据空间或最小带宽。 图像的主要视觉部件仍然可以被传统地压缩。 为某些区域提取边缘信息而不是压缩边缘信息显着增加了整体图像压缩。