High Dynamic Range (HDR) video is a technology that signilicantly enhances the visual experience by expanding therange of contrast and color in video content. Unlike standard dynamic range (sDR) video, HoR allows for brighterhighlights, deeper shadows, and a wider color gamut This results in more realistic and vibrant images that closely mimiethe way the human cye perceives the real world, in this segment, we will delve into the fundamental principles of HDRexploring how it works, the technical standards behind it [such as HDR10, Dolby Vision, and HLG), and the benefits itbrings to varlous types of content, from movles and Ty shows to video games and lve broadcasts in this talk, i will talkabout the following:
HDR lmage ReconstructionHigh dynamic range (HDR) image reconstruction is a process that aims to create images with a greater range ofluminancelevels than what is achievable with standard digital imaging techniques, This allows for the capture of both very brightand very dark detalls in a scone, closely mimicking, human vision, By combining multiple images takan at differentexposure levels, HDR reconstruction technlques can produce visually stunning and highly detalled lmages that betterrepresent the ranpe oflight present in real-world scenes.
ElN: Exposure lnduced Metwork for Single lmage HDR ReconstructionThe Exposure linduced Network, (ElN) for single image HDR Reconstruction is a novel deep learning approach designed togenerate HbR images from a single standard dynamic range ($bR) input, Unlike traditional methods that require multipleexposures, ElN leverages a neural network to predict and reconstruct HbR content by learning the relatlonships betweendiferent exposure levels, Thls enables the creatlon of high-quality HDR lmages even in situatlons where only a singleexposure is available, making HDR imaging more practical and accessible forvarious applications.
LGFM: HDR Image QualityAssessment Dased on Frequency Disparity
The Local and Globa! Frequency Modulation (LGFM) method for HDR image quality assessment is a sophisticatedapproach that avaluates the quality of HbR images based on the disparity in frequency components, By analyzing bothlocal and global frequency information, LGFM can more accurately reflect the human visual system's sensitivity todiferent types of artifacts and dlstortlons In HDR content, Thls results In a more rellable and comprehenslve assessmentofHoR image quality.