title: Transform-based image enhancement algorithms with performance measure.
abstract: This paper presents a new class of the "frequency domain"-based signal/image enhancement algorithms including magnitude reduction, log-magnitude reduction, iterative magnitude and a log-reduction zonal magnitude technique. These algorithms are described and applied for detection and visualization of objects within an image. The new technique is based on the so-called sequency ordered orthogonal transforms, which include the well-known Fourier, Hartley, cosine, and Hadamard transforms, as well as new enhancement parametric operators. A wide range of image characteristics can be obtained from a single transform, by varying the parameters of the operators. We also introduce a quantifying method to measure signal/image enhancement called EME. This helps choose the best parameters and transform for each enhancement. A number of experimental results are presented to illustrate the performance of the proposed algorithms.
authors.affiliation: Division of Engineering, The University of Texas, San Antonio, TX 78249-0669, USA. sagaian@voyager1.eng.utsa.edu
authors.forename: S S
authors.initials: SS
authors.lastname: Agaian
authors.forename: K
authors.initials: K
authors.lastname: Panetta
authors.forename: A M
authors.initials: AM
authors.lastname: Grigoryan