Abstract
WCDGAN: Weakly Connected Dense Generative Adversarial Network for Artifact Removal of Highly Compressed Images
Highlights
J PEG [1] is a widely used image format that represents rich and vivid contents due to the sophisticated compression algorithm
Since the methods involved in comparison do not consider color distortion, we design more comparative experiments to verify the feasibility and effectiveness of WCDGAN
All the approaches including the proposed WCDGAN are implemented with the Pytorch toolbox [54]
Summary
J PEG [1] is a widely used image format that represents rich and vivid contents due to the sophisticated compression algorithm. It first converts an RGB image into YCbCr color space and downsamples chroma components. The quantized DCT coefficients are converted into bitstream for transmission according to the encoding rules. It can be seen from Eq (1) that due to the floor function, the DCT coefficients at the encoding end and the DCT coefficients at the decoding end are different
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