Screen content video (SCV) distinguished from traditional natural video by its unique features, such as rich texture edges and flat areas. However, existing rate control algorithms are better fit for natural video than for SCV. A novel rate control (RC) algorithm for screen content coding (SCC) in Versatile Video Coding (VVC) is proposed in this paper. Specifically, spatial-temporal features at both CTU and frame levels of adjacent original and reconstructed frames are calculated based on 3D-LOG filter to guide bit allocation in CTU level. Considering the visual characteristics of human vision system, the rate distortion (R-D) model is redesigned. Extensive experimental results demonstrate the effectiveness of the proposed method, which improves the R-D performance and the accuracy of the bit-rate control.
Image inpainting aims to fill damaged regions with non-damaged regions and semantic reasonableness while ensuring consistency of an image. The result of inpainting often suffers from smooth edges and blurred details when faced with larger and more complicated damaged regions. In this paper, an end-to-end dual stream network that fuses the texture and structure features, aiming to restore intricate details in filled regions is proposed. For details enhancement, gated convolutions are introduced to pick valid pixels, reducing blur in damaged regions; For more comprehensive features representation, multi-scale parallel dilated convolutions are used to fuse features from different receptive fields and positions in the image. Extensive experimental results on three common datasets demonstrate the superiority of the proposed network in terms of quantitative and qualitative evaluation.
A novel rate control algorithm for immersive video depth map coding is proposed to ensure the immersive video quality in the context of limited bandwidth. The algorithm is developed based on the frame level approach for Versatile Video Coding (VVC) and is optimized using the open-source encoder implementation project, VVenC. Specifically, by considering the content characteristic of different videos, the rate-distortion (R-D) curve is refitted using hyperbolic model for the rate control parameters α and β. And the original α and β values of the depth map are modified to better guide the bit allocation. Experimental results indicate that the proposed rate control algorithm outperforms the VVenC 0.3.1.0 frame level rate control algorithm, achieving an average 4.2% BD-rate saving and 1.616dB gain under random access (RA) configuration, which is superior to existing rate control schemes for immersive video.
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