Abstract: A technique for streaming and a client device that uses the technique are disclosed herein. The disclosed technique determines context complexity of streamed data and determines whether to discard or select the streamed data for a future reference frame based on the context complexity of the streamed data. The streamed data is discarded if the content complexity is higher than a content complexity threshold, and the streamed data is selected if the content complexity is not higher than a content complexity threshold. This is based on the realization that error propagation in the case of a less complex video sequence is not very bothersome to the end user experience whereas corruption will be very severe in cases of highly complex sequences.

Abstract: A technique for streaming and a client device that uses the technique are disclosed herein. The disclosed technique determines context complexity of streamed data and determines whether to discard or select the streamed data for a future reference frame based on the context complexity of the streamed data. The streamed data is discarded if the content complexity is higher than a content complexity threshold, and the streamed data is selected if the content complexity is not higher than a content complexity threshold. This is based on the realization that error propagation in the case of a less complex video sequence is not very bothersome to the end user experience whereas corruption will be very severe in cases of highly complex sequences.

Abstract: A viewing device, a method of displaying streamed data frames and a client viewing device are disclosed herein. In one embodiment, the video viewing device includes: (1) a screen, (2) a decoder configured to decode a data frame received in a bitstream from a transmitter to provide a decoded data frame, and (3) an error concealer configured to either discard the decoded data frame or select the decoded data frame for display on the screen based on a complexity of the decoded data frame.

Abstract: Embodiments of the present invention are directed to methods and systems for performing automatic noise reduction in video. According to one aspect of the invention, a video noise-reducing system is provided consisting of a noise estimator, a motion classifier, two stages of filters, each including a spatial and temporal filter, and a combiner. The system adapts to noise level and to scene content to find at each location in the image a balance of noise reduction and detail preservation. Temporal Infinite Impulse Response (IIR) filtering provides a high level of detail-preserving noise reduction where motion allows, while non linear spatial filtering provides edge-preserving noise reduction in areas where the temporal filter would introduce motion artifacts. A spatial-temporal combiner provides smooth transition and balance between the two filtering modes; this block also enables use of external cues to produce a visually pleasing output based on ambient conditions.

Abstract: A method of noise filter parameter adaptation, the method comprising receiving a current video frame comprising a plurality of pixels. A table lookup is performed, using current statistical values associated with the current video frame. Noise filter parameters are adapted, based on current lighting conditions as determined from the performed table lookup. The current lighting conditions correspond to the current statistical values. The current video frame is noise filtered as defined by the adapted noise filter parameters.

Abstract: A viewing device, a method of displaying streamed data frames and a client viewing device are disclosed herein. In one embodiment, the video viewing device includes: (1) a screen, (2) a decoder configured to decode a data frame received in a bitstream from a transmitter to provide a decoded data frame, and (3) an error concealer configured to either discard the decoded data frame or select the decoded data frame for display on the screen based on a complexity of the decoded data frame.

Abstract: Embodiments of the present invention are directed to methods and systems for performing automatic noise reduction in video. According to one aspect of the invention, a video noise-reducing system is provided consisting of a noise estimator, a motion classifier, two stages of filters, each including a spatial and temporal filter, and a combiner. The system adapts to noise level and to scene content to find at each location in the image a balance of noise reduction and detail preservation. Temporal Infinite Impulse Response (IIR) filtering provides a high level of detail-preserving noise reduction where motion allows, while non linear spatial filtering provides edge-preserving noise reduction in areas where the temporal filter would introduce motion artifacts. A spatial-temporal combiner provides smooth transition and balance between the two filtering modes; this block also enables use of external cues to produce a visually pleasing output based on ambient conditions.

Abstract: A method of noise filter parameter adaptation, the method comprising receiving a current video frame comprising a plurality of pixels. A table lookup is performed, using current statistical values associated with the current video frame. Noise filter parameters are adapted, based on current lighting conditions as determined from the performed table lookup. The current lighting conditions correspond to the current statistical values. The current video frame is noise filtered as defined by the adapted noise filter parameters.