# A Display-Adaptive Pipeline for Dynamic Range Expansion of Standard Dynamic Range Video Content
## 3 Materials and Methods: A Pipeline for Dynamic Range Expansion of Video Sequences  
In the previous section, we explored various methods to convert LDR video sequences into HDR. These methods can produce high-quality HDR content characterized by sharp contrasts and luminous highlights, and have the capacity to restore missing details in overexposed regions. However, these methods also exhibit several of the limitations commonly present in LDR-to-HDR conversion methods. These include, but are not limited to, the manifestation of temporal and spatial artifacts. Furthermore, these methods are constrained to producing HDR content with lower peak luminance levels, which becomes an important drawback as television technology evolves to support higher brightness levels. Moreover, the complexity inherent to some of these techniques and their resource-intensive nature makes them less viable for practical implementations. This includes scenarios like real-time LDR to HDR conversion and integration into devices with limited computational capabilities, thus restricting their applicability in everyday technologies such as smart TVs and decoders. Given these factors, our research has produced a novel pipeline designed for efficient conversion of LDR video sequences into HDR. The primary aim of our method extends beyond the simple reversal of existing tone mapping, comprising both artistic nuances and technological constraints inherent to LDR content. Instead, our approach is designed to execute a comprehensive LDR-to-HDR conversion process. This meticulously crafted process seamlessly converts the original LDR footage into HDR, ensuring alignment with the enhanced artistic vision often associated with HDR imagery. Such a vision encompasses the achievement of deeper blacks, more luminous highlights, and vivid colors, all while preserving the scene's inherent naturalism. The focus on video sequences in LDR-to-HDR conversion is important for several reasons. Video sequences represent a significant portion of content production, from television and film to online streaming and gaming. In addition, with a vast amount of existing LDR content and the expectation that HDR screens will become standard in the near future, there is a growing demand for innovative techniques to convert LDR video sequences to HDR and, therefore, to take advantage of the enhanced contrast and brightness of upcoming HDR displays. Furthermore, new optimized algorithms capable of real-time processing on display devices will be essential to meet this demand. These algorithms must be designed to work efficiently within the limited resources typical of consumer displays while ensuring frame-to-frame consistency to maintain visual coherence and prevent temporal artifacts. Such consistency is particularly important in video sequences, where even minor discrepancies between frames can negatively affect the viewing experience. Our proposed pipeline extends the dynamic range of an LDR video sequence to be suitable for reproduction on an HDR display with highlights that can reach a maximum peak luminance of 6000 cd/m\({}^{2}\), far surpassing most existing techniques. Our pipeline enables a nuanced enhancement of the visual experience, faithfully reflecting the creators' artistic intentions within the technological framework of HDR display capabilities. The flowchart in Figure 2 illustrates our proposed pipeline, consisting of five key stages:  
* Artifact suppression: Prior to dynamic range expansion, artifacts (e.g., arising from compression) and noise in the LDR input image are effectively reduced. * Dynamic range expansion: The luminance from the filtered LDR image undergoes dynamic range expansion into HDR using a global operator. In this step, the maximum luminance intensity is expanded to 4000 cd/m\({}^{2}\), while the remaining 2000 cd/m\({}^{2}\) are allocated for additional highlight boosting.