计算机科学
图像分辨率
计算机视觉
人工智能
迭代重建
过程(计算)
分辨率(逻辑)
亚像素分辨率
信号处理
图像(数学)
数字图像处理
图像处理
数字信号处理
计算机硬件
操作系统
作者
Sung Cheol Park,Min‐Gyu Park,Moon Gi Kang
出处
期刊:IEEE Signal Processing Magazine
[Institute of Electrical and Electronics Engineers]
日期:2003-05-01
卷期号:20 (3): 21-36
被引量:3133
标识
DOI:10.1109/msp.2003.1203207
摘要
A new approach toward increasing spatial resolution is required to overcome the limitations of the sensors and optics manufacturing technology. One promising approach is to use signal processing techniques to obtain an high-resolution (HR) image (or sequence) from observed multiple low-resolution (LR) images. Such a resolution enhancement approach has been one of the most active research areas, and it is called super resolution (SR) (or HR) image reconstruction or simply resolution enhancement. In this article, we use the term "SR image reconstruction" to refer to a signal processing approach toward resolution enhancement because the term "super" in "super resolution" represents very well the characteristics of the technique overcoming the inherent resolution limitation of LR imaging systems. The major advantage of the signal processing approach is that it may cost less and the existing LR imaging systems can be still utilized. The SR image reconstruction is proved to be useful in many practical cases where multiple frames of the same scene can be obtained, including medical imaging, satellite imaging, and video applications. The goal of this article is to introduce the concept of SR algorithms to readers who are unfamiliar with this area and to provide a review for experts. To this purpose, we present the technical review of various existing SR methodologies which are often employed. Before presenting the review of existing SR algorithms, we first model the LR image acquisition process.
科研通智能强力驱动
Strongly Powered by AbleSci AI