A novel decision fusion approach to improving classification accuracy of hyperspectral images

Görmüş, Esra Tunç; Canagarajah, N.; Achim, Alin

doi:10.1109/igarss.2012.6351696

Cited by 1 publication

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Liu et al, [38] discussed an approach to identify minimum NDVI ( less vegetation cover) in MODIS data, approach is based on BVI-method (Brown Vegetation Index) which is a refined masking of cloud and snow matrix. The mean difference and contaminated percentage of Green band and SWIR band is less hence is useful in identifying evergreen forests, monsoon forests, and double cropping.…”

Section: Transformationmentioning

confidence: 99%

Remote Sensing Satellite Image Processing Techniques for Image Classification: A Comprehensive Survey

Sowmya¹,

Shenoy²,

Venugopal³

2017

IJCA

View full text Add to dashboard Cite

This paper is a brief survey of advance technological aspects of Digital Image Processing which are applied to remote sensing images obtained from various satellite sensors. In remote sensing, the image processing techniques can be categories in to four main processing stages: Image preprocessing, Enhancement, Transformation and Classification. Image pre-processing is the initial processing which deals with correcting radiometric distortions, atmospheric distortion and geometric distortions present in the raw image data. Enhancement techniques are applied to preprocessed data in order to effectively display the image for visual interpretation. It includes techniques to effectively distinguish surface features for visual interpretation. Transformation aims to identify particular feature of earth's surface and classification is a process of grouping the pixels, that produces effective thematic map of particular land use and land cover.

show abstract

Section: Transformationmentioning

confidence: 99%