A Display-Adaptive Pipeline for Dynamic Range Expansion of Standard Dynamic Range Video Content

Recent advancements in high dynamic range (HDR) display technology have significantly enhanced the contrast ratios and peak brightness of modern displays. In the coming years, it is expected that HDR televisions capable of delivering significantly higher brightness and, therefore, contrast levels than today’s models will become increasingly accessible and affordable to consumers. While HDR technology has gained prominence over the past few years, low dynamic range (LDR) content is still consumed due to a substantial volume of historical multimedia content being recorded and preserved in LDR. Although the amount of HDR content will continue to increase as HDR becomes more prevalent, a large portion of multimedia content currently remains in LDR. In addition, it is worth noting that although the HDR standard supports multimedia content with luminance levels up to 10,000 cd/m2 (a standard measure of brightness), most HDR content is typically limited to a maximum brightness of around 1000 cd/m2. This limitation aligns with the current capabilities of consumer HDR TVs but is a factor approximately five times brighter than current LDR TVs. To accurately present LDR content on a HDR display, it is processed through a dynamic range expansion process known as inverse tone mapping (iTM). This LDR to HDR conversion faces many challenges, including the inducement of noise artifacts, false contours, loss of details, desaturated colors, and temporal inconsistencies. This paper introduces complete inverse tone mapping, artifact suppression, and a highlight enhancement pipeline for video sequences designed to address these challenges. Our LDR-to-HDR technique is capable of adapting to the peak brightness of different displays, creating HDR video sequences with a peak luminance of up to 6000 cd/m2. Furthermore, this paper presents the results of comprehensive objective and subjective experiments to evaluate the effectiveness of the proposed pipeline, focusing on two primary aspects: real-time operation capability and the quality of the HDR video output. Our findings indicate that our pipeline enables real-time processing of Full HD (FHD) video (1920 × 1080 pixels), even on hardware that has not been optimized for this task. Furthermore, we found that when applied to existing HDR content, typically capped at a brightness of 1000 cd/m2, our pipeline notably enhances its perceived quality when displayed on a screen that can reach higher peak luminances.