Since ultra-high-definition (UHD) display has larger resolution and various display size, it is necessary to measure image sharpness considering variation in visual resolution caused by diverse viewing geometry. In this paper, we propose a no-reference perceptual sharpness assessment model of UHD images. The proposed model analyzes viewing geometry in terms of display resolution and viewing environment. Then, we measure the local adaptive sharpness score in accordance with the textural motion blur, texture, and edge. In addition, we propose a spatial pooling method associated with foveal regions, which is caused by nonuniform distribution of the photoreceptors on a human retina. Through the rigorous experiments, we demonstrate that the proposed model can measure the sharpness of UHD images more accurately than other image sharpness assessment methods.
|Title of host publication||2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings|
|Publisher||IEEE Computer Society|
|Number of pages||5|
|Publication status||Published - 2016 Aug 3|
|Event||23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States|
Duration: 2016 Sep 25 → 2016 Sep 28
|Name||Proceedings - International Conference on Image Processing, ICIP|
|Other||23rd IEEE International Conference on Image Processing, ICIP 2016|
|Period||16/9/25 → 16/9/28|
Bibliographical notePublisher Copyright:
© 2016 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
- Signal Processing