Please use this identifier to cite or link to this item:
Title: Multispectral image denoising by well-posed anisotropic diffusion scheme with channel coupling
Authors: Prasath, V.B.S .
Singh, A.
Keywords: Anisotropic Diffusion
Bounded variations
Channel coupling
Coupling terms
Diffusion process
Diffusion transfer
Edge preservations
Input image
Multi-dimensional images
Multi-spectral image data
Multispectral images
Piecewise smooth
Simulation result
Total variation
Aircraft engines
Image segmentation
Optical anisotropy
Partial differential equations
computer simulation
image analysis
image processing
numerical model
remote sensing
satellite data
spectral analysis
transfer function
Issue Date: 2010
Citation: International Journal of Remote Sensing, 31(8), 2091-2099
Abstract: A novel way to denoise multispectral images is proposed via an anisotropic diffusion based partial differential equation (PDE). A coupling term is added to the divergence term and it facilitates the modelling of interchannel relations in multidimensional image data. A total variation function is used to model the intrachannel smoothing and gives a piecewise smooth result with edge preservation. The coupling term uses weights computed from different bands of the input image and balances the interchannel information in the diffusion process. It aligns edges from different channels and stops the diffusion transfer using the weights. Well-posedness of the PDE is proved in the space of bounded variation functions. Comparison with the previous approaches is provided to demonstrate the advantages of the proposed scheme. The simulation results show that the proposed scheme effectively removes noise and preserves the main features of multispectral image data by taking channel coupling into consideration. � 2010 Taylor & Francis.
ISSN: 1431161
Appears in Collections:Articles

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.