期刊
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
卷 31, 期 5, 页码 1711-1723出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCSVT.2020.3014679
关键词
Brightness; Visualization; Sensitivity; Dynamic range; Task analysis; Standards; Electronic mail; High dynamic range (HDR); digital video; inverse tone mapping
资金
- Natural Sciences and Engineering Research Council of Canada (NSERC) [PG 11R12450]
- TELUS Communications Inc. [PG 11R10321]
The introduction of High Dynamic Range (HDR) technologies has brought about significant visual improvements and opened up new markets for a wide range of industries. Owners of legacy Standard Dynamic Range (SDR) content now have the opportunity to convert their content to the HDR standard and take advantage of the enhanced capabilities of HDR displays. A novel high visual quality video inverse Tone Mapping Operator (iTMO) has been proposed, which is based on human visual perception and employs a segmentation method according to the Human Visual System (HVS) sensitivity, resulting in high visual quality HDR videos.
The drastic visual improvements introduced by High Dynamic Range (HDR) technologies open new markets for a wide range of industries. Among them, a significant opportunity is offered to owners of legacy Standard Dynamic Range (SDR) content that can be converted to the new standard to take advantage of the enhanced capabilities of the HDR displays. Similarly, since SDR broadcasting infrastructure will continue to be around for the time being, such conversion process is becoming an obvious necessity. To this end, different approaches have tried to efficiently convert SDR images and videos to HDR format, a procedure well known as inverse Tone Mapping. In this paper, we propose a novel high visual quality video inverse Tone Mapping Operator (iTMO) that addresses the inadequacies of the state-of-the-art methods, resulting in high visual quality HDR videos that match the capabilities of the HDR technology. Our approach is based on human visual perception and employs a segmentation method according to the Human Visual System (HVS) sensitivity to brightness changes in different regions of the frame and constructs the mapping curve using the brightness distribution information of these regions. Our iTMO uses a hybrid approach to achieve an optimal balance between the overall contrast and brightness of the output HDR frame by maximizing a weighted sum of contrast and brightness difference between input SDR and generated HDR frame. The proposed iTMO works equally well for all levels of brightness, eliminating any visual artifacts by dynamically maintaining changes at non-perceivable levels. Subjective and objective evaluations validated the superior visual performance of our proposed iTMO over state-of-the-art methods.
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