Transform-based image enhancement algorithms with performance measure

Authors:
S. S. Agaian;K. Panetta;A. M. Grigoryan
Affiliations:
Div. of Eng., Texas Univ., San Antonio, TX;-;-
Venue:
IEEE Transactions on Image Processing
Year:
2001

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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