Luminance-Guided Chrominance Image Enhancement for HEVC Intra Coding
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Abstract (arXiv)
In this paper, we propose a luminance-guided chrominance image enhancement convolutional neural network for HEVC intra coding. Specifically, we firstly develop a gated recursive asymmetric-convolution block to restore each degraded chrominance image, which generates an intermediate output. Then, guided by the luminance image, the quality of this intermediate output is further improved, which finally produces the high-quality chrominance image. When our proposed method is adopted in the compression of color images with HEVC intra coding, it achieves 28.96% and 16.74% BD-rate gains over HEVC for the U and V images, respectively, which accordingly demonstrate its superiority.
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References · 11
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- 2019ACNet: Strengthening the Kernel Skeletons for Powerful CNN via Asymmetric Convolution Blockscited by 178
- 2015Compression Artifacts Reduction by a Deep Convolutional Networkcited by 136
- 2021Diverse Branch Block: Building a Convolution as an Inception-like Unitcited by 87
- 2016A Convolutional Neural Network Approach for Post-Processing in HEVC Intra Codingcited by 27
- 2019Partition-Aware Adaptive Switching Neural Networks for Post-Processing in HEVCcited by 8
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