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Titolo:
Transform-based image enhancement algorithms with performance measure
Autore:
Agaian, SS; Panetta, K; Grigoryan, AM;
Indirizzi:
Univ Texas, Div Engn, San Antonio, TX 78249 USA Univ Texas San Antonio TXUSA 78249 , Div Engn, San Antonio, TX 78249 USA Tufts Univ, Dept Elect Engn & Comp Sci, Medford, MA 02155 USA Tufts Univ Medford MA USA 02155 ct Engn & Comp Sci, Medford, MA 02155 USA Texas A&M Univ, Dept Elect Engn, CAMDI Lab, College Stn, TX 77843 USA Texas A&M Univ College Stn TX USA 77843 DI Lab, College Stn, TX 77843 USA
Titolo Testata:
IEEE TRANSACTIONS ON IMAGE PROCESSING
fascicolo: 3, volume: 10, anno: 2001,
pagine: 367 - 382
SICI:
1057-7149(200103)10:3<367:TIEAWP>2.0.ZU;2-9
Fonte:
ISI
Lingua:
ENG
Soggetto:
CONTRAST ENHANCEMENT;
Keywords:
alpha-rooting; detection; frequency domain enhancement; magnitude-reduction; sequency ordered transforms; visualization;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
34
Recensione:
Indirizzi per estratti:
Indirizzo: Agaian, SS Univ Texas, Div Engn, San Antonio, TX 78249 USA Univ Texas SanAntonio TX USA 78249 San Antonio, TX 78249 USA
Citazione:
S.S. Agaian et al., "Transform-based image enhancement algorithms with performance measure", IEEE IM PR, 10(3), 2001, pp. 367-382

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 asingle 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. Anumber of experimental results are presented to illustrate the performanceof the proposed algorithms.

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Documento generato il 29/01/20 alle ore 19:14:30