Results 1 to 10 of about 32,536 (135)
Deep HDR Hallucination for Inverse Tone Mapping [PDF]
Sensors, 2021 Inverse Tone Mapping (ITM) methods attempt to reconstruct High Dynamic Range (HDR) information from Low Dynamic Range (LDR) image content. The dynamic range of well-exposed areas must be expanded and any missing information due to over/under-exposure ...
Demetris Marnerides +2 more
doaj +10 more sources
iTM-Net: Deep Inverse Tone Mapping Using Novel Loss Function Considering Tone Mapping Operator [PDF]
IEEE Access, 2019 In this paper, we propose a novel inverse tone mapping network, called “iTM-Net.” For training iTM-Net, we also propose a novel loss function that considers the non-linear relation between low dynamic range (LDR) and high dynamic range (HDR)
Yuma Kinoshita, Hitoshi Kiya
doaj +5 more sources
Inverse Tone Mapping Based upon Retina Response [PDF]
The Scientific World Journal, 2014 The development of high dynamic range (HDR) display arouses the research of inverse tone mapping methods, which expand dynamic range of the low dynamic range (LDR) image to match that of HDR monitor.
Yongqing Huo, Fan Yang, Vincent Brost
doaj +5 more sources
Fast and flexible stack‐based inverse tone mapping
CAAI Transactions on Intelligence Technology, 2023 Inverse tone mapping technique is widely used to restore the lost textures from a single low dynamic range image. Recently, many stack‐based deep inverse tone mapping networks have achieved impressive results by estimating a set of multi‐exposure images ...
Ning Zhang +4 more
doaj +3 more sources
Deep Inverse Tone Mapping for Compressed Images [PDF]
IEEE Access, 2019 Converting a single low dynamic range (LDR) image into a high dynamic range (HDR) image, which is the so-called inverse tone mapping (ITM), is a challenging ill-posed problem since a lot of information is lost during compression and storage.
Chao Wang, Yang Zhao, Ronggang Wang
doaj +3 more sources
Lightweight improved residual network for efficient inverse tone mapping [PDF]
Multimedia Tools and Applications, 2023 The display devices like HDR10 televisions are increasingly prevalent in our daily life for visualizing high dynamic range (HDR) images. But the majority of media images on the internet remain in 8-bit standard dynamic range (SDR) format.
Liqi Xue +6 more
semanticscholar +3 more sources
Semantic Aware Diffusion Inverse Tone Mapping [PDF]
Journal of Physics: Conference SeriesCapturing the full luminance range of real-world scenes exceeds the capabilities of most digital cameras, often resulting in detail loss, particularly in bright regions.
Abhishek Goswami +4 more
semanticscholar +4 more sources
HDR-LFNet: Inverse tone mapping using fusion network
Computers & Graphics, 2023 To capture the real-world luminance values, High Dynamic Range (HDR) image processing has been developed. HDR images have a richer content than the widely-used Standard Dynamic Range (SDR) images, and are used in a number of situations, e.g.
Mathieu Chambe +5 more
semanticscholar +2 more sources
Cyclic Learning-Based Lightweight Network for Inverse Tone Mapping
Electronics (Switzerland), 2022 Recent studies on inverse tone mapping (iTM) have moved toward indirect mapping, which generates a stack of low dynamic range (LDR) images with multiple exposure values (multi-EV stack) and then merges them.
Byung Cheol Song, Song Byung Cheol
exaly +2 more sources
A Mixed Quantization Network for Efficient Mobile Inverse Tone Mapping [PDF]
CoRR, 2022 Recovering a high dynamic range (HDR) image from a single low dynamic range (LDR) image, namely inverse tone mapping (ITM), is challenging due to the lack of information in over- and under-exposed regions.
Juan Borrego-Carazo +3 more
semanticscholar +3 more sources