Abstract: A method is provided to better detect a scene change to provide a prediction to an encoder to enable more efficient encoding. The method uses a Motion Compensated Temporal Filter (MCTF) that provides motion estimation and is located prior to an encoder. The MCTF provides a Motion Compensated Residual (MCR) used to detect the scene change transition. When a scene is relatively stable, the MCR score is also relatively stable. However, when a scene transition is in process, the MCR score behavior changes, Algorithmically, the MCR score is used by comparing the sliding mean of the MCR score to the sliding median. This comparison highlights the transition points. In the case of a scene cut, the MCR score exhibits a distinct spike. In the case of a fade or dissolve, the MCR score exhibits a transitional period of degradation followed by recovery. By implementing the above detection using the MCR, the location of the I-pictures in the downstream encoding process can be accurately determined for the encoder.

Abstract: A system for providing improved video quality and compression efficiency during encoding by detecting video segments having film grain approaching the “Red Lady” problem. The system detects when film grain approaches the level of the “Red Lady” problem by measuring frame-by-frame temporal differences (ME scores). From the ME scores, two key indicators are identified: (1) The average temporal difference in frames with an intermediate motion level higher than frames of non-noisy video; and (2) The fluctuation of the temporal differences between frames in a group is very small. When these indicators identify a high film video, a signal is provided to an encoder which allocates less bits to I frames and more bits to P and B frames than for other frames of video without comparable film grain.

Abstract: A system for providing improved video quality and compression efficiency during encoding by detecting video segments having film grain approaching the “Red Lady” problem. The system detects when film grain approaches the level of the “Red Lady” problem by measuring frame-by-frame temporal differences (ME scores). From the ME scores, two key indicators are identified: (1) The average temporal difference in frames with an intermediate motion level higher than frames of non-noisy video; and (2) The fluctuation of the temporal differences between frames in a group is very small. When these indicators identify a high film video, a signal is provided to an encoder which allocates less bits to I frames and more bits to P and B frames than for other frames of video without comparable film grain.

Abstract: A method is provided to better detect a scene change to provide a prediction to an encoder to enable more efficient encoding. The method uses a Motion Compensated Temporal Filter (MCTF) that provides motion estimation and is located prior to an encoder. The MCTF provides a Motion Compensated Residual (MCR) used to detect the scene change transition. When a scene is relatively stable, the MCR score is also relatively stable. However, when a scene transition is in process, the MCR score behavior changes, Algorithmically, the MCR score is used by comparing the sliding mean of the MCR score to the sliding median. This comparison highlights the transition points. In the case of a scene cut, the MCR score exhibits a distinct spike. In the case of a fade or dissolve, the MCR score exhibits a transitional period of degradation followed by recovery. By implementing the above detection using the MCR, the location of the I-pictures in the downstream encoding process can be accurately determined for the encoder.

Abstract: A method is provided to better detect a scene change to provide a prediction to an encoder to enable more efficient encoding. The method uses a Motion Compensated Temporal Filter (MCTF) that provides motion estimation and is located prior to an encoder. The MCTF provides a Motion Compensated Residual (MCR) used to detect the scene change transition. When a scene is relatively stable, the MCR score is also relatively stable. However, when a scene transition is in process, the MCR score behavior changes, Algorithmically, the MCR score is used by comparing the sliding mean of the MCR score to the sliding median. This comparison highlights the transition points. In the case of a scene cut, the MCR score exhibits a distinct spike. In the case of a fade or dissolve, the MCR score exhibits a transitional period of degradation followed by recovery. By implementing the above detection using the MCR, the location of the I-pictures in the downstream encoding process can be accurately determined for the encoder.

Abstract: A method of encoding video is provides encoding of panic scenes efficiently. The method includes receiving an input video at an encoder, reviewing lookahead information from a second encoder that processed the input video ahead of the encoder that indicates positions of panic scenes within the input video that caused the second encoder to enter a panic encoding mode during which it skipped the encoding of frames, entering a pre-panic stage with the encoder ahead of said panic scenes, entering a semi-panic stage with the encoder during the panic scenes when it produces a bitstream having a number of bits exceeding a predetermined data size within an encoder buffer, and entering a full panic stage when the semi-panic stage does not bring the number of bits in the bitstream below the predetermined data size.

Abstract: A video encoding method is provided when three scenes are separated by two closely spaced scene changes. For scene changes spaced greater than a threshold, scene changes are programmed with I frames in a normal fashion. If less than the threshold, the method encodes depending on complexity of the first, second and third scene to determine how to encode the scene changes. To compare complexities, the process begins by using X1, X2, and X3 to note respectively the complexities of the first, the second and the third scenes. If the absolute difference of X1 and X2 is higher than a first threshold and the absolute difference of X2 and X3 is higher than a second threshold, the first scene change is more significant than the second scene change, so in that case the process encodes the first scene change as an I-frame and picks a quantization parameter (QP) based on the complexity blended from the complexity of scene 2 (X2) and scene 3 (X3).

Abstract: A method of encoding video is provides encoding of panic scenes efficiently. The method includes receiving an input video at an encoder, reviewing lookahead information from a second encoder that processed the input video ahead of the encoder that indicates positions of panic scenes within the input video that caused the second encoder to enter a panic encoding mode during which it skipped the encoding of frames, entering a pre-panic stage with the encoder ahead of said panic scenes, entering a semi-panic stage with the encoder during the panic scenes when it produces a bitstream having a number of bits exceeding a predetermined data size within an encoder buffer, and entering a full panic stage when the semi-panic stage does not bring the number of bits in the bitstream below the predetermined data size.