.png){kind=icon}
返回
Phase-based fine-grained change detection
.png){kind=icon}
PRE
AI
DOI：10.1016/j.eswa.2023.120181.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Detecting fine-grained changes among a set of images taken at different times is a challenging problem, which is important for the applications such as high-value scene monitoring and structural inspection. Existing methods use a geometry registration and lighting compensation pipeline to alleviate the ingredients that affect change detection. However, lighting compensation may introduce a lot of artifacts, e.g., inaccurate local lighting conditions and fine-grained change disappearance. The distortion introduced by general registration methods also makes the process of lighting correction more challenging. To solve these problems, in this paper, we propose a new phase-based change detection method, called as pb-FGCD, which first aligns two observation of different times and then extract structure information to handle lighting difference. Benefiting from the proposed weighted amplitude filter and iterative alignment strategy, we could obtain a better registration performance. The structure information extracts the lighting irrelevant components of an image and is more sensitive to structure changes compared with the lighting compensation based method, which is vital for detecting the changes with low intensity difference. Furthermore, we contribute a new change detection dataset, which contains 100 groups of the real-world data of the ancient Mogao murals and the Terra-Cotta. It is the first fine-grained change detection dataset focusing on the ancient mural. Our approach significantly improves the accuracy by more than 190% higher F1-measure than the state-of-the-art methods.
Keyword:
Complex steerable pyramid
Change detection
Image registration
Structure information
期刊
IF:
7.5
论文数:
2.9W
被引数:
10.2W
机构
引用论文
Judgment Capacity, Fear of Falling, and the Risk of Falls in Community-Dwelling Older Adults: The Progetto Veneto Anziani Longitudinal Study社区居住的老年人的判断能力，对跌倒的恐惧和跌倒的风险: Progetto Veneto Anziani纵向研究
OAAI
OAAI分享收藏Alteration of Natural UO2 under Oxidizing Conditions from Shinkolobwe, Katanga, Zaire: A Natural Analogue for the Corrosion of Spent Fuel.png)
ract
ractIF0
PREAI
分享收藏分享收藏分享收藏Small towns shrinkage in the Jilin Province: A comparison between China and developed countriesPLOS ONEOAAI
PLOS ONEIF0
OAAI分享收藏
查看更多内容