# A Display-Adaptive Pipeline for Dynamic Range Expansion of Standard Dynamic Range Video Content
Common examples of temporal artifacts include flickering, object incoherence, and brightness incoherence. In this paper, we present comprehensive inverse tone mapping, artifact suppression, and a highlight enhancement pipeline for video sequences designed to address the challenges described above. This work significantly advances our earlier contributions, strategically extending our inverse tone mapping approach for LDR images, initially introduced in [13; 32], and seamlessly integrating it with our decontouring algorithm detailed in [31] to formulate a comprehensive LDR-to-HDR conversion pipeline optimized for video content. Furthermore, we introduce new steps for artifact suppression and a novel step for highlight enhancement, with the explicit aim of elevating the quality of the resultant HDR video sequence. Furthermore, we introduce an innovative application of our pipeline that increases the brightness of existing HDR content in a careful way. Typically, HDR content is limited to a peak brightness of around 1000 cd/m\({}^{2}\). Our approach enables an increase in peak brightness up to 6000 cd/m\({}^{2}\), markedly improving its visual quality. The main contributions of our research are as follows:  
1. We developed a comprehensive LDR-to-HDR conversion pipeline for video sequences capable of adapting to the peak brightness of different displays. Our pipeline can create HDR video sequences that significantly exceed the peak brightness capabilities of current state-of-the-art iTM techniques. This capability is particularly significant given that future television technologies are expected to support even greater brightness levels than those currently available. 2. We propose a novel method to detect and enhance highlights in HDR content. Our method is designed to identify and boost highlights while staying within the technical limits of the display device. This simultaneously maximizes the dynamic range and enhances the visual impact of the HDR video. 3. We present an innovative application of our pipeline to significantly increase the overall brightness of existing HDR content acquired at lower luminance levels. This results in HDR video sequences with peak brightness exceeding current HDR standards, thereby delivering a considerable improvement in visual quality. 4. We present the results of comprehensive objective and subjective experiments evaluating the effectiveness of our proposed LDR-to-HDR conversion pipeline. We focused on two primary aspects: real-time operation capability and the quality of the HDR video output. HDR video quality was assessed via three experiments: (1) objective evaluation of LDR-to-HDR converted videos obtained from our pipeline and two state-of-the-art methods, (2) subjective evaluation of LDR to HDR converted videos obtained from our pipeline versus original LDR content, and (3) subjective evaluation of HDR to xHDR converted videos using an alternative application of our pipeline. The structure of this paper is organized as follows: Section 2 provides an overview of prior works in the field. In Section 3, we delve into the details of our proposed LDR-to-HDR pipeline. The experimental setup and outcomes are presented in Section 4, including an evaluation of our pipeline for enhancing the perceived quality of existing HDR content. Finally, Section 5 presents our concluding remarks and future research directions.