Study On Multiscale Image Analysis: Theory And Applications

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-22 Number-1
Year of Publication : 2015
Authors : SuryaNath R S, Anilkumar A
  10.14445/22312803/IJCTT-V22P102

MLA

SuryaNath R S, Anilkumar A "Study On Multiscale Image Analysis: Theory And Applications". International Journal of Computer Trends and Technology (IJCTT) V22(1):5-10, April 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Wavelet has application in the field of denoising and compression but they are inefficient for computing geometrical features. To accommodate missing features multiscale methods can be used. Multiscale image analysis methods are deeply related to the field of pattern recognition, computer vision, Remote sensing. Multiscale representation of image are more desirable and ridgelet, curvelet, contourlet are such representations. Ridgelet transform is the anisotropic geometric wavelet transform which is good in representing lines. Most images has curves rather than straight lines so more efficient method called curvelet transform can be used. Contourlet transform is good in representing smooth contours and has high directional selectivity.

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Keywords
Character Recognition, Contourlet Transform, Curvelet Transform, Fingerprint Identification, Image Compression, Image Denoising, Image Fusion, Ridgelet Transform, Radon Transform, Wavelet Transform.