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Visual quality preserving quantization parameter prediction with deep neural network
Visual quality preserving quantization parameter prediction with deep neural network
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机译：基于深度神经网络的视觉质量保留量化参数预测
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摘要
A QP mapping method is capable of preserving consistent visual quality across the encoded frame. It automatically assigns more bits to image blocks which are more sensitive to compression distortion. The texture-descriptive features employed for QP prediction are fast to compute and, together with a deep neural network, are able to effectively approximate the underlying QP mapping strategy deduced from a visual quality measure.
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