Name
Abstract | ||
|---|---|---|
Various power saving and contrast enhancement (PSCE) techniques have been applied to an organic light emitting diode (OLED) display for reducing the power demands of the display while preserving the image quality. In this paper, we propose a new deep learning-based PSCE scheme that can save power consumed by the OLED display while enhancing the contrast of the displayed image. In the proposed method, the power consumption is saved by simply reducing the brightness a certain ratio, whereas the perceived visual quality is preserved as much as possible by enhancing the contrast of the image using a convolutional neural network (CNN). Furthermore, our CNN can learn the PSCE technique without a reference image by unsupervised learning. Experimental results show that the proposed method is superior to conventional ones in terms of image quality assessment metrics such as a visual saliency-induced index (VSI) and a measure of enhancement (EME). |
Year | Venue | DocType |
|---|---|---|
2019 | arXiv: Image and Video Processing | Journal |
Volume | Citations | PageRank |
abs/1905.05916 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| yonggoo shin | 1 | 15 | 6.00 |
| seung park | 2 | 3 | 2.78 |
| Min-Jae Yoo | 3 | 0 | 0.34 |
| Sung-Jea Ko | 4 | 14 | 1.95 |