2016 2nd International Conference on Advanced Technologies for Signal and Image Processing (ATSIP) 2016
DOI: 10.1109/atsip.2016.7523154
|View full text |Cite
|
Sign up to set email alerts
|

Super-resolution algorithm based on sub-pixels spatial Correlation for hyperspectral image classification

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
2
0

Year Published

2016
2016
2016
2016

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(2 citation statements)
references
References 25 publications
0
2
0
Order By: Relevance
“…In [61], an adaptive sub-pixel mapping algorithm is proposed. After finding the abundance maps, each pixel is divided along columns into smaller units and fractions are duplicated in the divided pixels.…”
Section: Spatial Optimization Based Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…In [61], an adaptive sub-pixel mapping algorithm is proposed. After finding the abundance maps, each pixel is divided along columns into smaller units and fractions are duplicated in the divided pixels.…”
Section: Spatial Optimization Based Methodsmentioning
confidence: 99%
“…In general, SRR methods using auxiliary data such as sub-pixel shifted LR images or HR RGB or MS image generates better results[58].However, single image SRR for HS images are taking considerable attention since sometimes supplementary data may not exist for the HS image. The output of single SRR can be either super-resolution maps (SRM)[59,60,61], a map to describe the most likely distribution of mixed pixels, or HR HS image[58,62,63].…”
mentioning
confidence: 99%