The importance of native panel contrast and local dimming density on perceived image quality of high dynamic range displays

2016 ◽  
Vol 24 (4) ◽  
pp. 216-228 ◽  
Author(s):  
David M. Hoffman ◽  
Natalie N. Stepien ◽  
Wei Xiong
Keyword(s):  
Image Quality ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
High Dynamic ◽  
Local Dimming

scholarly journals An experimental study on the perceived quality of natively graded versus inverse tone mapped high dynamic range video content on television

2020 ◽  
Author(s):  
Gonzalo Luzardo ◽  
Tine Vyvey ◽  
Jan Aelterman ◽  
Tom Paridaens ◽  
Glenn Van Wallendael ◽  
...  
Keyword(s):  
Experimental Study ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Perceived Quality ◽  
Video Content ◽  
High Dynamic ◽  
High Dynamic Range Video

Image quality evaluation for high dynamic range and wide color gamut applications using visual spatial processing of color differences

2020 ◽  
Vol 46 (1) ◽  
pp. 46-64
Author(s):  
Anustup Choudhury ◽  
Robert Wanat ◽  
Jaclyn Pytlarz ◽  
Scott Daly
Keyword(s):  
Image Quality ◽  
Quality Evaluation ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Spatial Processing ◽  
Color Gamut ◽  
Visual Spatial ◽  
Color Differences ◽  
Wide Color Gamut ◽  
High Dynamic

scholarly journals Consolidated Dataset and Metrics for High-Dynamic-Range Image Quality

2021 ◽  
pp. 1-1
Author(s):  
Aliaksei Mikhailiuk ◽  
Maria Perez-Ortiz ◽  
Dingcheng Yue ◽  
Wilson Samuel Suen ◽  
Rafa Mantiuk
Keyword(s):  
Image Quality ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Range Image ◽  
High Dynamic Range Image ◽  
High Dynamic

High Dynamic Range (HDR) Image Quality Assessment: A Survey

2019 ◽  
Author(s):  
Irwan Prasetya Gunawan ◽  
Ocarina Cloramidina ◽  
Salmaa Badriatu Syafa'ah ◽  
Guson Prasamuarso Kuntarto ◽  
Berkah I Santoso
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
High Dynamic ◽  
Hdr Image

P-108: Contrast Enhancement based on Advanced Local Dimming System for High Dynamic Range LCDs

2017 ◽  
Vol 48 (1) ◽  
pp. 1667-1669 ◽  
Author(s):  
Ooksang Yoo ◽  
Sangjin Nam ◽  
JoungMi Choi ◽  
Seungjin Yoo ◽  
Kyu-Jin Kim ◽  
...  
Keyword(s):  
Contrast Enhancement ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
High Dynamic ◽  
Local Dimming

scholarly journals Evaluation of hemispherical photos extracted from smartphone spherical panorama images to estimate canopy structure and forest light environment

2020 ◽  
Author(s):  
A. Z. Andis Arietta
Keyword(s):  
Image Quality ◽  
Forest Canopy ◽  
Dynamic Range ◽  
Canopy Structure ◽  
High Dynamic Range ◽  
Canopy Openness ◽  
Traditional Methods ◽  
Area Index ◽  
Site Factor ◽  
High Dynamic

AbstractHemispherical photography (HP) is one of the most commonly employed methods to estimate forest canopy structure and understory light environments. Traditional methods require expensive, specialized equipment, are tedious to deploy, and are sensitive to exposure settings. In contrast, modern smartphone cameras are readily available and make use of ever-improving software to produce images with high dynamic range and clarity, but lack suitable hemispherical lenses. Thus, despite the fact that almost all ecologists and foresters carry a high-powered, image processing device in our pockets, we have yet to fully employ it for the purpose of data collection. As an alternative, hemispherical images can be extracted from spherical panoramas produced by many smartphone camera applications. I compared hemispherical photos captured with a digital single lens reflex camera and 180° lens to those extracted from smartphone spherical panoramas (SSP) for 72 sites representing a range of canopy types and densities. I estimated common canopy and light measures (canopy openness, leaf area index, and global site factor) as well as image quality measures (total gap area, number of gaps, and relative gap size) to compare methods. The SSP HP method leverages built-in features of current generation smartphones including exposure metering over restricted field-of-view, high dynamic range tonal correction, computational sharpening, high pixel density, and automatic leveling via the phone’s built-in gyroscope to yield an accurate alternative to traditional HP in canopy estimation. Although the process of stitching together multiple photos occasionally produces artifacts in the SSP HP images, estimates of canopy openness and global site factor are highly correlated with those of traditional methods (R2> 0.9) and are comparable to under- or over-exposing traditional HP by 1-1.5 stops. In addition to superior image quality, SSP HP requires no additional equipment or exposure settings and is likely to prove more robust to uneven lighting conditions by avoiding wide-angles lenses and exploiting HDR images.

Evaluation of High Dynamic Range Reduced-Reference Image Quality Assessment based on Spatial Features

2019 ◽  
Author(s):  
Irwan Prasetya Gunawan ◽  
Ocarina Cloramidina ◽  
Salmaa Badriatu Syafa'ah ◽  
Guson Prasamuarso Kuntarto ◽  
Berkah Iman Santoso
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Dynamic Range ◽  
High Dynamic Range ◽  
Reference Image ◽  
Spatial Features ◽  
High Dynamic
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