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MACHINE LEARNING BASED DYNAMIC COMPOSING IN ENHANCED STANDARD DYNAMIC RANGE VIDEO (SDR+)

机译:基于机器学习的动态组合在增强标准动态范围视频(SDR +)中

摘要

Training image pairs comprising training SDR image and corresponding training HDR images are received. Each training image pair in the training image pairs comprises a training SDR image and a corresponding training HDR image. The training SDR image and the corresponding training HDR image in the training image pair depict same visual content but with different luminance dynamic ranges. Training image feature vectors are extracted from training SDR images in the training image pairs. The training image feature vectors are used to train backward reshaping metadata prediction models for predicting operational parameter values of backward reshaping mappings used to backward reshape SDR images into mapped HDR images.
机译:接收培训图像对包括训练SDR图像和相应的训练HDR图像。 训练图像对中的每个训练图像对包括训练SDR图像和相应的训练HDR图像。 训练图像对中的训练SDR图像和相应的训练HDR图像描绘了相同的视觉内容,但具有不同的亮度动态范围。 从训练图像对中的训练SDR图像中提取训练图像特征向量。 训练图像特征向量用于训练向后复制元数据预测模型,用于预测向后重塑映射的操作参数值,用于向映射的HDR图像中的重塑SDR图像。

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