P‐13.14: Two Inspection Methods of Image Quality & Appearance Based on Edge Crack of OLED Display Module

2021 ◽  
Vol 52 (S2) ◽  
pp. 1048-1049
Author(s):  
Wenyu Bao ◽  
Zhang Chao ◽  
Yang Zhihui ◽  
Xu Yuewei ◽  
Wenyu Bao
2019 ◽  
Vol 2019 (1) ◽  
pp. 104-107
Author(s):  
Ye Seul Baek ◽  
Youngshin Kwak ◽  
Sehyeok Park

The image quality is affected by the black luminance level of the image. This research aimed to investigate how low luminance levels are required to maintain image quality. The psychophysical experiment was carried out in a dark room using OLED display. Total of 6 different black luminance levels (0.003, 0.05, 0.1, 0.2, 0.3, and 1 cd/m2) were used in the experiment. Total of 20 participants was invited to evaluate the image quality. For the experiment, twelve test images are used and these test images categorized into three groups as dark, medium bright and bright image group by image histogram distribution. Each image is rendered by adjusting six different black luminance levels. Result found that the black level is higher than 0.1 cd/m2, the preference for the image is decreased. The best performance is achieved when the black level is 0.003 cd/m2, but there is no big difference from 0.1 cd/m2. The final result shows that a change in black level between about 0.003 cd/m2 and 0.1 cd/m2 does not significantly affect image quality.


2021 ◽  
Vol 52 (S1) ◽  
pp. 643-646
Author(s):  
Yang Guobo ◽  
Qiu Haijun ◽  
Huang Weiyun ◽  
Yang Yuqing ◽  
Long Yue ◽  
...  

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Di Wu ◽  
Fei Yuan ◽  
En Cheng

The optical images collected by remotely operated vehicles (ROV) contain a lot of information about underwater (such as distributions of underwater creatures and minerals), which plays an important role in ocean exploration. However, due to the absorption and scattering characteristics of the water medium, some of the images suffer from serious color distortion. These distorted color images usually need to be enhanced so that we can analyze them further. However, at present, no image enhancement algorithm performs well in any scene. Therefore, in order to monitor image quality in the display module of ROV, a no-reference image quality predictor (NIPQ) is proposed in this paper. A unique property that differentiates the proposed NIPQ metric from existing works is the consideration of the viewing behavior of the human visual system and imaging characteristics of the underwater image in different water types. The experimental results based on the underwater optical image quality database (UOQ) show that the proposed metric can provide an accurate prediction for the quality of the enhanced image.


2020 ◽  
Vol 51 (1) ◽  
pp. 1131-1134
Author(s):  
Hong-Jae Shin ◽  
Soo-Hong Choi ◽  
Sung-Joong Kim ◽  
Jae-Kyu Park ◽  
Seong-Ho Yun ◽  
...  

2017 ◽  
Vol 48 (1) ◽  
pp. 1134-1137 ◽  
Author(s):  
Hong-Jae Shin ◽  
Kwang-Mo Park ◽  
Shinji Takasugi ◽  
Yun-Sik Jeong ◽  
Jin-Mok Kim ◽  
...  

2020 ◽  
Vol 51 (S1) ◽  
pp. 176-179
Author(s):  
Yang Guobo ◽  
Qiu Haijun ◽  
Huang Weiyun ◽  
Yang Yuqing ◽  
Long Yue ◽  
...  

2019 ◽  
Vol 50 (1) ◽  
pp. 1533-1536
Author(s):  
Chi Jui Cheng ◽  
Tzu Chin Huang ◽  
Wen Tsan Lin ◽  
Cheng Chih Hsieh ◽  
Peng Yu Chen ◽  
...  

2019 ◽  
Vol 2019 (10) ◽  
pp. 309-1-309-5
Author(s):  
Dalin Tian ◽  
Lihao Xu ◽  
Ming Ronnier Luo

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