scholarly journals Human Perceptuality-Aware Tone-Mapping-Based Dynamic Voltage Scaling for an AMOLED Display Smartphone

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1015
Author(s):  
Simon Suh ◽  
Seok Min Hong ◽  
Young-Jin Kim ◽  
Jong Sung Park
Keyword(s):  
Dynamic Range ◽  
Power Saving ◽  
High Dynamic Range ◽  
Voltage Scaling ◽  
Dynamic Voltage Scaling ◽  
Tone Mapping ◽  
Local Contrast ◽  
Image Brightness ◽  
Dynamic Voltage ◽  
High Dynamic

In recent years, people have wanted to watch high dynamic range imagery which can give high human visual satisfaction on smartphones and demand longer smartphone battery time. However, compression of dynamic range using tone-mapping operators is required in smartphones because most smartphone displays currently have a low dynamic range, and this causes loss of local contrast and details to compress dynamic range. Thus, in this paper we propose a novel dynamic voltage scaling scheme tightly coupled with a modified tone-mapping operator to achieve high power saving as well as good human perceptuality on an AMOLED display smartphone. In order to perform a human perceptuality-aware voltage control, we control display panel voltage to save power consumption and use a well-adjusted global tone-mapping operator to convert image brightness and unsharp masking to enhance local contrast and details and control. We implement the proposed scheme on the AMOLED display Android smartphone and experiment with various high dynamic range image databases. Experimental results show that not only tone-mapped images but also general images are improved in terms of human visual satisfaction and power saving, compared to conventional techniques.

scholarly journals A Weighted Histogram-Based Tone Mapping Algorithm for CT Images

Algorithms ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 111 ◽  
Author(s):  
David Völgyes ◽  
Anne Martinsen ◽  
Arne Stray-Pedersen ◽  
Dag Waaler ◽  
Marius Pedersen
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Histogram Equalization ◽  
Ct Images ◽  
Tone Mapping ◽  
Local Contrast ◽  
Kernel Size ◽  
Mapping Algorithm ◽  
High Dynamic ◽  
Weighted Histogram

Computed Tomography (CT) images have a high dynamic range, which makes visualization challenging. Histogram equalization methods either use spatially invariant weights or limited kernel size due to the complexity of pairwise contribution calculation. We present a weighted histogram equalization-based tone mapping algorithm which utilizes Fast Fourier Transform for distance-dependent contribution calculation and distance-based weights. The weights follow power-law without distance-based cut-off. The resulting images have good local contrast without noticeable artefacts. The results are compared to eight popular tone mapping operators.

scholarly journals JSI-GAN: GAN-Based Joint Super-Resolution and Inverse Tone-Mapping with Pixel-Wise Task-Specific Filters for UHD HDR Video

2020 ◽  
Vol 34 (07) ◽  
pp. 11287-11295
Author(s):  
Soo Ye Kim ◽  
Jihyong Oh ◽  
Munchurl Kim
Keyword(s):  
Contrast Enhancement ◽  
Dynamic Range ◽  
Super Resolution ◽  
High Dynamic Range ◽  
Divide And Conquer ◽  
Tone Mapping ◽  
Local Contrast ◽  
Joint Learning ◽  
High Dynamic ◽  
Inverse Tone Mapping

Joint learning of super-resolution (SR) and inverse tone-mapping (ITM) has been explored recently, to convert legacy low resolution (LR) standard dynamic range (SDR) videos to high resolution (HR) high dynamic range (HDR) videos for the growing need of UHD HDR TV/broadcasting applications. However, previous CNN-based methods directly reconstruct the HR HDR frames from LR SDR frames, and are only trained with a simple L2 loss. In this paper, we take a divide-and-conquer approach in designing a novel GAN-based joint SR-ITM network, called JSI-GAN, which is composed of three task-specific subnets: an image reconstruction subnet, a detail restoration (DR) subnet and a local contrast enhancement (LCE) subnet. We delicately design these subnets so that they are appropriately trained for the intended purpose, learning a pair of pixel-wise 1D separable filters via the DR subnet for detail restoration and a pixel-wise 2D local filter by the LCE subnet for contrast enhancement. Moreover, to train the JSI-GAN effectively, we propose a novel detail GAN loss alongside the conventional GAN loss, which helps enhancing both local details and contrasts to reconstruct high quality HR HDR results. When all subnets are jointly trained well, the predicted HR HDR results of higher quality are obtained with at least 0.41 dB gain in PSNR over those generated by the previous methods. The official Tensorflow code is available at https://github.com/JihyongOh/JSI-GAN.

High Dynamic Range Images and Tone Mapping Operator

2009 ◽  
Vol 35 (2) ◽  
pp. 113-122 ◽  
Author(s):  
Ke-Hu YANG ◽  
Jing JI ◽  
Jian-Jun GUO ◽  
Wen-Sheng YU
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Tone Mapping ◽  
Range Images ◽  
High Dynamic

Evaluation of tone mapping operators using a High Dynamic Range display

2005 ◽  
Vol 24 (3) ◽  
pp. 640-648 ◽  
Author(s):  
Patrick Ledda ◽  
Alan Chalmers ◽  
Tom Troscianko ◽  
Helge Seetzen
Keyword(s):  
Dynamic Range ◽  
High Dynamic Range ◽  
Tone Mapping ◽  
High Dynamic

scholarly journals Optimal Tone-Mapping for HDR Images

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3078-3080
Keyword(s):  
Dynamic Range ◽  
Optimization Problems ◽  
High Dynamic Range ◽  
Mapping Technique ◽  
Tone Mapping ◽  
Local Restriction ◽  
High Dynamic ◽  
M Estimation ◽  
Performance Gains ◽  
Smooth Transitions

This research paper proposes a unique optimal tone-mapping technique for high dynamic range (HDR) images, performing local adjustments with overlapping windows covering complete image. A local linear adjustment is applied on each window to preserve the radiance values. This problem may be treated as global optimization problems to satisfy the local restriction for every overlapping window. These Local constraints may be considered as a guidance map to suppress high contrast without losing its details. M-estimation technique may be used for solving this optimization problem. This technique may be applied to HDR images with sudden radiance changes or comparatively smooth transitions. Further, this technique may be applied to differentiate and analyzes HDR images from LDR images. Simulation results are included to support the performance gains achieved by the proposed technique.

High Dynamic Range Image Watermarking Robust Against Tone-Mapping Operators

2011 ◽  
Vol 6 (2) ◽  
pp. 283-295 ◽  
Author(s):  
Fabrizio Guerrini ◽  
Masahiro Okuda ◽  
Nicola Adami ◽  
Riccardo Leonardi
Keyword(s):  
Dynamic Range ◽  
Image Watermarking ◽  
High Dynamic Range ◽  
Tone Mapping ◽  
Range Image ◽  
High Dynamic Range Image ◽  
High Dynamic
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