Vidiator Enterprises Inc.

Lalit Sarna

Yanda Ma

Gamze Seckin

Raghavendra C Nagaraj

Alan Tseng

Jayank M Bhalod

Data is shared across several simultaneous software video encode/compressions sessions with a common input video source. This reduces the amount of work done by each individual encoder by intelligently sharing/reusing data between encoders at various stages of encoding. Each encoder may use the data from another encoder 'as-is' or may further minimally process the data. This data sharing reduces the overall encoding time of the streams significantly by reducing the duplicative work that would otherwise have to be performed by each encoder. Data sharing thus enables production of more simultaneous unique compressed video streams per encoding station. To allow sharing and reuse of data between encoders, various modules in the encoding pipeline operate in a hierarchical manner and use each other's output data, and cooperate to produce multiple unique video streams that may differ in format, bit rate, resolution, frame rate, or other video characteristic.

Method and system for hierarchical data reuse to improve efficiency in the encoding of unique multiple video streams

A Quality of Experience (QoE) framework provides a technique to assess the end user experience in a mobile wireless communication environment, such as 2.5G or 3G networks, or in any other wireless or hardwired communication environment. The framework is usable in conjunction with media streaming applications and enables a combination of network layer, transport layer, codec layer, and application layer measurements in extracting results. The extracted results can be used to monitor and improve, if necessary, the end user experience over severely variable network conditions.

Quality of experience (QoE) method and apparatus for wireless communication networks

An adaptive pre-processing technique is provided to reduce perceptually unimportant information in a frame (such as some of the high frequency information) so as to optimize compression efficiency and to maximize perceived video quality of a compressed video sequence for a given bit rate. This pre-processing includes a combination of performing pre-filtering of video data to remove high frequency components and to smooth out high frequency texture information within object boundaries, based at least in part on human visual system characteristics. The technique is adaptive in that feedback regarding the current state of the encoder is used to change the filtering strength or region of support for subsequent frames, as needed, in order to maintain the bit budget while still generating visually acceptable video quality.

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Mountain View, CA, United States of America

Lalit Sarna