per
دانشگاه صنعتی نوشیروانی بابل
مجله علمی رایانش نرم و فناوری اطلاعات
2383-1006
2588-4913
2012-12-21
1
4
29
40
80868
English Original Article
A Hybrid Statistical IHS Image Fusion Method
A Hybrid Statistical IHS Image Fusion Method
Ali Reza Afary
afary@nit.ac.ir
1
Mohammad Javad Valdan Zoej
valadanzouj@kntu.ac.ir
2
Hassan Emami
h_emami@tabrizu.ac.ir
3
Babol Noshirvani University of Technology
K.N. Toosi University of Technology, Tehran, Iran
University of Tabriz, Tabriz, Iran
IHS method for image fusion is one of the conventional methods with a simple theory. Implementation of thismethod is simple and effective from computational point of view. But this method causes the spectral content ofthe fused image to get disturbed in comparison with the spectral criteria of the main multispectral image. In thisarticle a statistical image fusion method is combined with the conventional IHS method to improve its spectralquality and overcome its deficiency. Some spectral indices were used for evaluation of this combined method andcompared with the conventional IHS and the used statistical fusion methods. This combined method improves thespectral quality of the fused image and eliminates the existing shortcomings of the spectral disturbing in fusedimage produced by IHS method.
IHS method for image fusion is one of the conventional methods with a simple theory. Implementation of thismethod is simple and effective from computational point of view. But this method causes the spectral content ofthe fused image to get disturbed in comparison with the spectral criteria of the main multispectral image. In thisarticle a statistical image fusion method is combined with the conventional IHS method to improve its spectralquality and overcome its deficiency. Some spectral indices were used for evaluation of this combined method andcompared with the conventional IHS and the used statistical fusion methods. This combined method improves thespectral quality of the fused image and eliminates the existing shortcomings of the spectral disturbing in fusedimage produced by IHS method.
https://jscit.nit.ac.ir/article_80868_c24c0ef92e8ff96d58d1a58c2bebedba.pdf
Image fusion
IHS
Statistical method
Spectral quality
Image fusion
IHS
Statistical method
Spectral quality
per
دانشگاه صنعتی نوشیروانی بابل
مجله علمی رایانش نرم و فناوری اطلاعات
2383-1006
2588-4913
2012-12-21
1
4
49
54
84484
English Original Article
A New Upper Bound for the Capacity of Free Space Optical Intensity Channel by Using a Simple Mathematical Inequality
A New Upper Bound for the Capacity of Free Space Optical Intensity Channel by Using a Simple Mathematical Inequality
کبری اکبری
kobra_akbari20@yahoo.com
1
قوشه عابدهدتنی
hodtani@um.ac.ir
2
Department of Electrical Engineering, Sadjad Institute for Higher Education
Department of Electrical Engineering, Ferdowsi University of Mashhad,
Farid-Hranilovic (FH), in an interesting way, found a capacity-achieving discrete input distribution for free space optical (FSO) channel by numerically maximizing the input-parameter (β) dependent mutual information between channel input and the scaled output. In this paper, first, by using a simple mathematical inequality, we find an upper bound for FH input-scaled output mutual information and then maximize the obtained upper bound to reach to a third order equation for the optimum β as β*. Our equation (i) determines β* exactly in contrary to the FH work where β* is found numerically through an exhaustive search and also, (ii) is consistent with the estimated equation for β* in the FH work. Our upper bound is shown to be tighter than the proposed upper bound in the FH work that is found through sphere packing argument at very high SNRs. Using numerical illustrations at different SNRs, we compare our β*s, mass point spacing as *, and upper bound with previous works.
Farid-Hranilovic (FH), in an interesting way, found a capacity-achieving discrete input distribution for free space optical (FSO) channel by numerically maximizing the input-parameter (β) dependent mutual information between channel input and the scaled output. In this paper, first, by using a simple mathematical inequality, we find an upper bound for FH input-scaled output mutual information and then maximize the obtained upper bound to reach to a third order equation for the optimum β as β*. Our equation (i) determines β* exactly in contrary to the FH work where β* is found numerically through an exhaustive search and also, (ii) is consistent with the estimated equation for β* in the FH work. Our upper bound is shown to be tighter than the proposed upper bound in the FH work that is found through sphere packing argument at very high SNRs. Using numerical illustrations at different SNRs, we compare our β*s, mass point spacing as *, and upper bound with previous works.
https://jscit.nit.ac.ir/article_84484_c7809eb20ccad3fa5f2247f99c2e185f.pdf
FSO channels
equally spaced mass points
maximization of the mutual information
FSO channels
equally spaced mass points
maximization of the mutual information