Ming-Chen Chien

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— This work proposes a complexity-control algorithm that efficiently utilizes encoding tools of an H.264 video coding system under different power status. Experiments performed on a power-scalable embedded system 1 reveal the excellent rate-distortion performance with various power constraints. Specifically, the power consumption can be adjusted around 77%(More)
The allowable computational complexity of video encoding is limited in a power-constrained system. Different video frames are associated with different motions and contexts, and so are associated with different computational complexities if no complexity control is utilized. Variation in computational complexity leads to encoding delay jittering. Typically(More)
—Video quality under rate constraint is mainly controlled by the frame rate and the quantization parameter. This work proposes a mechanism to obtain the optimal frame rate that maximizes video quality under rate constraint. Based on an objective metric of video quality that can reflect subjective quality, this work first proposes a video quality—frame(More)
SUMMARY This research proposes a Coding-Gain-Based (CGB) complexity control method for real-time H.264 video encoding in complexity-constrained systems such as wireless handsets. By allocating more complexity to the encoding tools which have higher coding efficiency, the CGB method is able to maximize the overall coding efficiency of the encoder.
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