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    • 1. 发明申请
    • Architecture for stack robust fine granularity scalability
    • 堆栈的架构稳健的细粒度可扩展性
    • US20050195896A1
    • 2005-09-08
    • US10793830
    • 2004-03-08
    • Hsiang-Chun HuangChung-Neng WangTihao ChiangHsuch-Ming Hang
    • Hsiang-Chun HuangChung-Neng WangTihao ChiangHsuch-Ming Hang
    • H04N7/12
    • H04N19/36H04N19/34H04N19/61
    • The present invention relates to an architecture for stack robust fine granularity scalability (SRFGS), more particularly, SRFGS providing simultaneously temporal scalability and SNR scalability. SRFGS first simplifies the RFGS temporal prediction architecture and then generalizes the prediction concept as the following: the quantization error of the previous layer can be inter-predicted by the reconstructed image in the previous time instance of the same layer. With this concept, the RFGS architecture can be extended to multiple layers that forming a stack to improve the temporal prediction efficiency. SRFGS can be optimized at several operating points to fit the requirements of various applications while the fine granularity and error robustness of RFGS are still remained. The experiment results show that SRFGS can improve the performance of RFGS by 0.4 to 3.0 dB in PSNR.
    • 本发明涉及用于堆栈鲁棒的精细粒度可伸缩性(SRFGS)的架构,更具体地说,涉及提供同时时间可扩展性和SNR可伸缩性的SRFGS。 SRFGS首先简化RFGS时间预测架构,然后将预测概​​念概括如下:先前层的量化误差可以由同一层的先前时间实例中的重建图像进行预测。 利用这个概念,RFGS架构可以扩展到形成堆栈的多个层,以提高时间预测效率。 SRFGS可以在几个操作点进行优化,以适应各种应用的要求,同时仍保持RFGS的细粒度和误差鲁棒性。 实验结果表明,SRFGS可以在PSNR中将RFGS的性能提高0.4〜3.0dB。
    • 2. 发明授权
    • Architecture and method for fine granularity scalable video coding
    • 精细粒度可扩展视频编码的架构和方法
    • US07072394B2
    • 2006-07-04
    • US10229580
    • 2002-08-27
    • Hsiang-Chun HuangChung-Neng WangTihao ChiangHsueh-Ming Hang
    • Hsiang-Chun HuangChung-Neng WangTihao ChiangHsueh-Ming Hang
    • H04B1/66
    • H04N19/34H04N19/33
    • A robust fine granularity scalability video encoding includes a base layer encoder and an enhancement layer encoder in which motion compensated difference images are generated by comparing an original image to predicted images at base layer and enhancement layer with motion compensation. Based on leaky and partial predictions, a high quality reference image is constructed at the enhancement layer to improve temporal prediction. In the construction of the high quality reference image, one parameter β controls the number of bitplanes of the enhancement layer difference coefficients used and another parameter α controls the amount of predictive leak. A spatial scalability module allows the processed pictures at the base layer and the enhancement layer to have identical or different spatial resolutions.
    • 强大的细粒度可伸缩性视频编码包括基本层编码器和增强层编码器,其中通过将原始图像与基本层和具有运动补偿的增强层的预测图像进行比较来生成运动补偿差分图像。 基于泄漏和部分预测,在增强层构建高质量参考图像以改善时间预测。 在构建高质量参考图像时,一个参数β控制所使用的增强层差分系数的位平面数,另一参数α控制预测泄漏量。 空间可扩展性模块允许基础层和增强层处理的图像具有相同或不同的空间分辨率。
    • 4. 发明授权
    • Architecture and method for fine granularity scalable video coding
    • 精细粒度可扩展视频编码的架构和方法
    • US07203235B2
    • 2007-04-10
    • US11136780
    • 2005-05-25
    • Hsiang-Chun HuangChung-Neng WangTi-Hao ChiangHsueh-Ming Hang
    • Hsiang-Chun HuangChung-Neng WangTi-Hao ChiangHsueh-Ming Hang
    • H04B1/66
    • H04N19/34H04N19/33
    • A robust fine granularity scalability video encoding includes a base layer encoder and an enhancement layer encoder in which motion compensated difference images are generated by comparing an original image to predicted images at base layer and enhancement layer with motion compensation. Based on leaky and partial predictions, a high quality reference image is constructed at the enhancement layer to improve temporal prediction. In the construction of the high quality reference image, one parameter β controls the number of bitplanes of the enhancement layer difference coefficients used and another parameter α controls the amount of predictive leak. A spatial scalability module allows the processed pictures at the base layer and the enhancement layer to have identical or different spatial resolutions.
    • 强大的细粒度可伸缩性视频编码包括基本层编码器和增强层编码器,其中通过将原始图像与基本层和具有运动补偿的增强层的预测图像进行比较来生成运动补偿差分图像。 基于泄漏和部分预测,在增强层构建高质量参考图像以改善时间预测。 在构建高质量参考图像时,一个参数β控制所使用的增强层差分系数的位平面数,另一参数α控制预测泄漏量。 空间可扩展性模块允许基础层和增强层处理的图像具有相同或不同的空间分辨率。
    • 8. 发明授权
    • System for topology based automatic focus
    • 基于拓扑的自动对焦系统
    • US08508654B1
    • 2013-08-13
    • US13252381
    • 2011-10-04
    • Hsiang-Chun HuangChiHong John Ju
    • Hsiang-Chun HuangChiHong John Ju
    • H04N5/232
    • H04N5/23212
    • A camera including a first queue, a second queue, and a processor. The processor is generally coupled to the first queue and the second queue. The processor embodies routines that, when executed by the processor, cause the processor to (i) record a first topology in the first queue and a second topology in the second queue and (ii) compare the first topology with the second topology. Recording of the second topology is generally started after the first topology is completely recorded. A focus of the camera is automatically adjusted based upon one or more similarities between the first topology and the second topology.
    • 包括第一队列,第二队列和处理器的相机。 处理器通常耦合到第一队列和第二队列。 处理器体现了当由处理器执行时使得处理器(i)在第一队列中记录第一拓扑并且在第二队列中记录第二拓扑并且(ii)将第一拓扑与第二拓扑进行比较的例程。 通常在完全记录第一个拓扑结构后开始记录第二个拓扑。 基于第一拓扑和第二拓扑之间的一个或多个相似性自动调整相机的焦点。