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Derivation of Optimal Global Equalization Function with Variable Size Block Based Local Contrast Enhancement
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作者 Ralph Oyini Mbouna Young-joon HAN 《Journal of Measurement Science and Instrumentation》 CAS 2010年第4期334-337,共4页
A conventional global contrast enhancement is difficult to apply in various images because image quality and contrast enhancement are dependent on image characteristics largely. And a local contrast enhancement not on... A conventional global contrast enhancement is difficult to apply in various images because image quality and contrast enhancement are dependent on image characteristics largely. And a local contrast enhancement not only causes a washed-out effect, but also blocks. To solve these drawbacks, this paper derives an optimal global equalization function with variable size block based local contrast enhancement. The optimal equalization function makes it possible to get a good quality image through the global contrast enhancement. The variable size block segmentation is firstly exeoated using intensity differences as a measure of similarity. In the second step, the optimal global equalization function is obtained from the enhanced contrast image having variable size blocks. Conformed experiments have showed that the proposed algorithm produces a visually comfortable result image. 展开更多
关键词 global oontrast enhancement local contrast enhancement optimal equalization function block segmentation variable size block
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Parametric Duality Models for Semi-infinite Discrete Minmax Fractional Programming Problems Involving Generalized (η,ρ)-Invex Functions 被引量:4
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作者 G.J.Zalmai 《Acta Mathematicae Applicatae Sinica》 SCIE CSCD 2007年第3期353-376,共24页
A semi-infinite programming problem is a mathematical programming problem with a finite number of variables and infinitely many constraints. Duality theories and generalized convexity concepts are important research t... A semi-infinite programming problem is a mathematical programming problem with a finite number of variables and infinitely many constraints. Duality theories and generalized convexity concepts are important research topics in mathematical programming. In this paper, we discuss a fairly large number of paramet- ric duality results under various generalized (η,ρ)-invexity assumptions for a semi-infinite minmax fractional programming problem. 展开更多
关键词 Semi-infinite programming discrete minmax fractional programming generalized invex functions infinitely many equality and inequality constraints parametric duality models duality theorems
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Global Parametric Sufficient Optimality Conditions for Semi-infinite Discrete Minmax Fractional Programming Problems Involving Generalized (η,ρ)-invex Functions 被引量:1
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作者 G.J.Zalmai 《Acta Mathematicae Applicatae Sinica》 SCIE CSCD 2007年第2期217-234,共18页
In this paper, we discuss a large number of sets of global parametric sufficient optimality conditions under various generalized (η,ρ)-invexity assumptions for a semi-infinite minmax fractional programming problem.
关键词 Semi-infinite programming discrete minmax fractional programming generalized invex functions infinitely many equality and inequality constraints sufficient optimality conditions
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Global Parametric Sufficient Efficiency Conditions for Semiinfinite Multiobjective Fractional Programming Problems Containing Generalized (α, η, ρ)-V-Invex Functions
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作者 G.J. Zalmai Qing-hong Zhang 《Acta Mathematicae Applicatae Sinica》 SCIE CSCD 2013年第1期63-78,共16页
Abstract In this paper, we discuss numerous sets of global parametric sufficient efficiency conditions under various generalized (a,n, p)-V-invexity assumptions for a semiinfinite multiobjective fractional programmi... Abstract In this paper, we discuss numerous sets of global parametric sufficient efficiency conditions under various generalized (a,n, p)-V-invexity assumptions for a semiinfinite multiobjective fractional programming problem. 展开更多
关键词 Semiinfinite programming multiobjective fractional programming generalized invex functions infinitely many equality and inequality constraints parametric sufficient efficiency conditions.
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