explaination of these duties in remote sensing

[adnan0001]

Hi friends

 

Can anyone explain me

 

Euclidean geometry transformations such as enlargement, reduction, and rotation.

 

Interpolation, demosaicing, and recovery of a full image from a raw image format using a Bayer filter pattern.

 

Image differencing and morphing.

 

High dynamic range imaging by combining multiple images.

 

Image segmentation.

 

Geometric hashing for 2-D object recognition with affine invariance.

 

Thanks

[Lurker]

Euclidean geometry transformations such as enlargement, reduction, and rotation ;

 

this is kind of geometric transformation, changing the geometry of the data,

http://www.cs.mtu.edu/~shene/COURSES/cs3621/NOTES/geometry/geo-tran.html

Interpolation, demosaicing, and recovery of a full image from a raw image format using a Bayer filter pattern ;

 

never use this method, but here some interesting links :

http://www.kenrockwell.com/tech/bayer.htm

http://www.thedailynathan.com/demosaic/

http://www.peter-cockerell.net/Bayer/bayer.html

Image differencing and morphing.

 

this maybe like detection of the differences of two images, and applied on land use change detector tool from ENVI, or land change modeller by IDRISI

http://www.exelisvis.com/docs/ChangeDetectionAnalysis.html

simple explanation would be compare pixel from two different images with same area to see the change value between them

 

image morphing related to geometric transformation I guess :

http://www.comp.nus.edu.sg/~cs4340/lecture/imorph.pdf

High dynamic range imaging by combining multiple images.

 

hem I dont know implementation in remote sensing, but for more general image processing, this could be interersting resource :

http://ij3c.ncuteecs.org/volume/paperfile/3-2/IJ3C_6.pdf

Image segmentation.

 

implementation in remote sensing is to separate and extract object from image, basically for image classification

 

more general explanation :

http://en.wikipedia.org/wiki/Image_segmentation

and some tools with reference :

http://www.exelisvis.com/docs/BackgroundSegmentationAlgorithm.html

http://faculty.wwu.edu/wallin/envr442/envi/442_segmentation_envi.htm

Geometric hashing for 2-D object recognition with affine invariance.

 

general explanation :

http://en.wikipedia.org/wiki/Geometric_hashing

basically for object recognition so in remote sensing this would be suited for image classification

http://www.cse.unr.edu/~bebis/CS773C/ObjectRecognition/Lectures/GeometricHashing.ppt

but never try this before,

 

IMHO