Editor/Reviewer loginFrequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
IJCATR Volume 12 Issue 4
Visibility Detection Based on Object Region Selection
Tao Xu, Jie Zhang, Rong Fu
10.7753/IJCATR1204.1002
keywords : dark channel prior; visibility detection; superpixel segmentation; object region
In response to the shortcomings of the dark channel prior and optimization methods in window selection and object depth variation, this paper proposes a visibility detection algorithm based on object region selection. The algorithm introduces superpixel segmentation to divide the image into superpixel blocks and extracts the superpixel blocks containing the target object for visibility calculation. In the visibility calculation, the dark channel and transmission rate extraction can be obtained only from the target object region, without the need to process the entire image region. This improves the accuracy of the target object parameter calculation and speeds up the computation.
@artical{t1242023ijcatr12041002,
Title = " Visibility Detection Based on Object Region Selection ",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "12",
Issue ="4",
Pages ="5 - 7",
Year = "2023",
Authors ="Tao Xu, Jie Zhang, Rong Fu"}
Reduce the amount of data and then save running memory.
Strict boundary constraints.
High speed.
It is widely applicable because no window selection is required.