Blind image quality evaluation metrics design for UAV photographic application
Title | Blind image quality evaluation metrics design for UAV photographic application |
Publication Type | Conference Paper |
Year of Publication | 2015 |
Authors | Liu, H., Wang, W., He, Z., Tong, Q., Wang, X., Yu, W., Lv, M. |
Conference Name | 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER) |
Keywords | autonomous aerial vehicles, blind image quality evaluation metrics design, blind IQEM, calamity resuce, Cameras, human visual system, HVS based IQEM, image brightness level, image contrast level, image edge blur level, Image edge detection, image enhancement, image flicker level, image jitter level, image noise level, image processing, Image quality, image quality metric, image texture, image texture intensity level, imaging quality, Measurement, mobile robots, outdoor application, photography, pubcrawl170111, robot vision, telerobotics, UAV, UAV photographic application, unmanned aerial vehicle |
Abstract | A number of blind Image Quality Evaluation Metrics (IQEMs) for Unmanned Aerial Vehicle (UAV) photograph application are presented. Nowadays, the visible light camera is widely used for UAV photograph application because of its vivid imaging effect; however, the outdoor environment light will produce great negative influences on its imaging output unfortunately. In this paper, to conquer this problem above, we design and reuse a series of blind IQEMs to analyze the imaging quality of UAV application. The Human Visual System (HVS) based IQEMs, including the image brightness level, the image contrast level, the image noise level, the image edge blur level, the image texture intensity level, the image jitter level, and the image flicker level, are all considered in our application. Once these IQEMs are calculated, they can be utilized to provide a computational reference for the following image processing application, such as image understanding and recognition. Some preliminary experiments for image enhancement have proved the correctness and validity of our proposed technique. |
DOI | 10.1109/CYBER.2015.7287951 |
Citation Key | liu_blind_2015 |
- Image Processing
- unmanned aerial vehicle
- UAV photographic application
- uav
- telerobotics
- robot vision
- pubcrawl170111
- photography
- outdoor application
- mobile robots
- Measurement
- imaging quality
- image texture intensity level
- image texture
- image quality metric
- Image quality
- autonomous aerial vehicles
- image noise level
- image jitter level
- image flicker level
- image enhancement
- Image edge detection
- image edge blur level
- image contrast level
- image brightness level
- HVS based IQEM
- human visual system
- Cameras
- calamity resuce
- blind IQEM
- blind image quality evaluation metrics design