2018 25th IEEE International Conference on Image Processing (ICIP) 2018
DOI: 10.1109/icip.2018.8451715
|View full text |Cite
|
Sign up to set email alerts
|

On Minimum Spanning Tree Streaming for Image Analysis

Abstract: This work addresses minimum spanning tree (MST) construction in streaming for images. We study the problem of computation a MST on streaming in which image columns from a continuous stream are processed in blocks of a given size. The correctness of proposed algorithm is proved and confirmed in the case of morphological segmentation of remote sensing images.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
3
0

Year Published

2020
2020
2020
2020

Publication Types

Select...
2

Relationship

1
1

Authors

Journals

citations
Cited by 2 publications
(3 citation statements)
references
References 15 publications
(15 reference statements)
0
3
0
Order By: Relevance
“…We only prove that the second method returns a MST. For a proof of the first method please refer to our previous work (Gigli et al, 2018). We show that the graph…”
mentioning
confidence: 84%
See 1 more Smart Citation
“…We only prove that the second method returns a MST. For a proof of the first method please refer to our previous work (Gigli et al, 2018). We show that the graph…”
mentioning
confidence: 84%
“…e-mail: name.surname@mines-paristech.fr (Leonardo Gigli) This paper is an extended version of the work published by Gigli et al (2018). The original paper addresses the problem of computing a MST on image streaming .…”
Section: Introductionmentioning
confidence: 99%
“…In the literature, this problem of trees changing over time is known as the dynamic tree problem (Sleator and Tarjan, 1983). Our image streaming algorithms rely on temporal based streaming while there are other perspectives such as spatial image streaming (Gigli et al, 2018). As a related work, authors proposed streaming graph for video segmentation in (de Souza et al, 2015).…”
Section: Introductionmentioning
confidence: 99%