Title :
The general application of the spherical mean value method for image noise reduction
Author_Institution :
Dept. of Radiol., Pennsylvania Univ., Philadelphia, PA, USA
Abstract :
A spherical mean value (SMV) method was shown to reduce image noise significantly for magnetic field and temperature mapping. Here the SMV method is proposed as a general image-processing tool, applicable to a wide variety of scalar or vector physical quantities including static electromagnetic, current density, flow velocity, gravity, and temperature fields
Keywords :
Laplace equations; filtering theory; harmonic analysis; image processing; interference suppression; Laplace equation; averaging; current density; data noise; flow velocity; general image-processing tool; gravity fields; harmonic functions; image noise reduction; magnetic field gradient tensor; magnetic field mapping; multiple-order spatial derivatives; scalar physical quantities; spatial resolution; spherical mean value method; static electromagnetic fields; temperature mapping; vector physical quantities; Current density; Electromagnetic fields; Gravity; Laplace equations; Magnetic fields; Magnetic noise; Magnetic resonance; Magnetic susceptibility; Noise reduction; Temperature;
Conference_Titel :
Bioengineering Conference, 2002. Proceedings of the IEEE 28th Annual Northeast
Conference_Location :
Philadelphia, PA
Print_ISBN :
0-7803-7419-3
DOI :
10.1109/NEBC.2002.999527
