Title
A flexible framework for local phase coherence computation
Abstract
Local phase coherence (LPC) is a recently discovered property that reveals the phase relationship in the vicinity of distinctive features between neighboring complex filter coefficients in the scale-space. It has demonstrated good potentials in a number of image processing and computer vision applications, including image registration, fusion and sharpness evaluation. Existing LPC computation method is restricted to be applied to three coefficients spread in three scales in dyadic scalespace. Here we propose a flexible framework that allows for LPC computation with arbitrary selections in the number of coefficients, scales, as well as the scale ratios between them. In particular, we formulate local phase prediction as an optimization problem, where the object function computes the closeness between true local phase and the predicted phase by LPC. The proposed method not only facilitates flexible and reliable computation of LPC, but also demonstrates strong robustness in the presence of noise. The groundwork laid here broadens the potentials of LPC in future applications.
Year
DOI
Venue
2011
10.1007/978-3-642-21593-3_5
ICIAR
Keywords
Field
DocType
true local phase,image registration,local phase prediction,local phase coherence computation,image processing,reliable computation,lpc computation method,flexible framework,phase relationship,local phase coherence,lpc computation,scale space,feature detection
Computer vision,Pattern recognition,Computer science,Scale space,Image processing,Robustness (computer science),Phase coherence,Artificial intelligence,Complex filter,Optimization problem,Image registration,Computation
Conference
Volume
ISSN
Citations 
6753
0302-9743
2
PageRank 
References 
Authors
0.42
11
3
Name
Order
Citations
PageRank
Rania Hassen1925.62
Z Wang213331630.91
Magdy M. A. Salama329514.63