@conference {12447,
	title = {Component-based restoration of speckled images},
	booktitle = {2011 18th IEEE International Conference on Image Processing (ICIP)},
	year = {2011},
	month = {2011/09/11/14},
	pages = {2797 - 2800},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Many coherent imaging modalities are often characterized by a multiplicative noise, known as speckle which often makes the interpretation of data difficult. In this paper, we present a speckle reduction algorithm based on separating the structure and texture components of SAR images. An iterative algorithm based on surrogate functionals is presented that solves the component optimization formulation. Experiments indicate this proposed method performs favorably compared to state-of-the-art speckle reduction methods.},
	keywords = {coherent imaging modalities, component optimization formulation, component-based restoration, Dictionaries, image restoration, iterative algorithm, iterative methods, multiplicative noise, NOISE, optimisation, radar imaging, SAR images, Speckle, speckle reduction algorithm, speckled images, structure components, surrogate functionals, synthetic aperture radar, texture components, transforms, TV},
	isbn = {978-1-4577-1304-0},
	doi = {10.1109/ICIP.2011.6116252},
	author = {Patel, Vishal M. and Easley,G. R and Chellapa, Rama}
}
@conference {15916,
	title = {A new multiresolution generalized directional filter bank design and application in image enhancement},
	booktitle = {15th IEEE International Conference on Image Processing, 2008. ICIP 2008},
	year = {2008},
	month = {2008/10//},
	pages = {2816 - 2819},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {In this paper, we present an image enhancement technique based on a new multiscale generalized directional filter bank design. The design presented is a shift-invariant overcomplete representation, which is well suited to extracting geometric features such as edges. Special cases of this design method can be made to reduce to different and improved implementations of the shearlet and the contourlet transforms, which are known to represent certain classes of images optimally. Use of this new filter bank design has proven itself competitive in image restoration for noisy images and is well suited for distinguishing noise from weak edges. Experimental results show that our unique image enhancement technique out-performs wavelet and contourlet based enhancement methods.},
	keywords = {Algorithm design and analysis, Approximation error, Channel bank filters, contourlet transform, Design methodology, Discrete transforms, Feature extraction, Filter bank, Frequency, geometric feature extraction, Image Enhancement, IMAGE PROCESSING, image resolution, image restoration, Multidimensional digital filters, Multidimensional systems, multiresolution generalized directional filter bank design, shearlet transform, shift-invariant overcomplete representation, transforms, Wavelet transforms},
	isbn = {978-1-4244-1765-0},
	doi = {10.1109/ICIP.2008.4712380},
	author = {Patel, Vishal M. and Easley,G. R and Healy,D. M}
}
