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We propose a decoder-friendly chrominance enhancement method for the compressed images. Our proposed method is developed based on the luminance-guided chrominance enhancement network (LGCEN) and online learning. With LGCEN, the textures of the compressed chrominance components are enhanced by the guidance of luminance component. Moreover, LGCEN is constructed with the recursive design and the light-weight channel attention mechanism to achieve high performance as well as low complexity. It is arranged at both encoder and decoder sides. Given the input image, we train LGCEN at encoder side by using online learning. With online learning, we partially update network parameters and transmit them to decoder to update LGCEN arranged there. The adoption of online learning effectively reduces the workload of decoder and guarantee high robustness. Compared with the state-of-the-art methods, our proposed approach achieves superior performance.
Yang et al. (Tue,) studied this question.