# Versatile Video Coding-Post Processing Feature Fusion:
## 1 Introduction  
The proliferation of video data has become an integral part of our digital landscape, with an astonishing volume of footage being captured and generated at an unprecedented rate of millions of hours daily. The emergence of video streaming has dramatically transformed the way we engage with visual content, turning the digital world into a lively and engaging space. As high-speed internet, smartphones, and smart devices became widespread, video streaming became a crucial aspect of daily life, offering easy access to a vast selection of entertainment, educational, and informative content at users' fingertips. With social media platforms, online movie theaters, video conferencing tools, and live event broadcasts, the growth of video streaming has created new opportunities for creators, viewers, and businesses, reshaping the way we connect, learn, and enjoy ourselves. The surge in video streaming applications has led to a substantial escalation in bandwidth consumption, thereby imposing considerable strain on network infrastructure, data centers, and devices. The growing popularity of high-definition and 4K video content has, in turn, triggered a pioneering demand for bandwidth, exerting immense pressure on networks. This has resulted in bandwidth constraints, which can lead to slower speeds, buffering, and poor video quality. The significance of advanced video compression technologies is emphasized by the need to deliver high-quality video content over networks with limited bandwidth. By reducing the amount of data required to transmit video, these solutionsenable seamless video streaming even in environments where bandwidth is scarce. This is achieved through sophisticated algorithms that compress video data, minimizing the strain on networks while maintaining an optimal viewing experience. Several lossy video compression technologies, including High Efficiency Video Coding/H.265 (HEVC) [1] and Versatile Video Coding/H.266 (VVC) [2], have been developed to attain a balance between bitrate and distortion, enabling efficient compression of video data. VVC offers a substantial compression gain, reducing the bitrate by half while preserving the same level of video quality as HEVC, which result in a notable enhancement in compression performance. VVC retains the conventional block-based hybrid video coding framework but incorporates numerous innovative coding tools, each with its own unique compression capabilities, to enhance overall coding efficiency. The VVC framework consists of a range of essential components, including transform, quantization, entropy coding, intra prediction, inter prediction, and loop filtering, which work together to enable efficient video compression. The transform unit plays a crucial role in VVC, converting video frames from the time domain to the frequency domain, thereby compacting energy into the low-frequency regions, which facilitates more efficient compression. The quantization module serves to limit the dynamic range of the image, thereby addressing the primary source of video coding distortion, which is essential for achieving efficient compression. Entropy coding is a method used in encoding to convert data into compact binary streams, enabling efficient data storage and transmission by reducing the amount of data required to represent the information. Intra- and inter-prediction methods are used to eliminate spatial and temporal redundancies, respectively. Additionally, a loop filter module is applied during video coding to improve video frame quality and optimize compression efficiency, comprising three key components: a deblocking filter (DBF), a sample adaptive offset (SAO), and an adaptive loop filter (ALF). Despite its superior performance, VVC-encoded videos still exhibit visual quality issues, indicating that the advanced tools and algorithms used in VVC are not enough to eliminate visual degradation in reconstructed videos. The block-based design of VVC can compromise video quality through various forms of distortion.