By Jin Li (auth.), Song Lin, Xiong Huang (eds.)
This two-volume set (CCIS one hundred seventy five and CCIS 176) constitutes the refereed court cases of the overseas convention on desktop schooling, Simulation and Modeling, CSEM 2011, held in Wuhan, China, in June 2011. The 148 revised complete papers provided in either volumes have been rigorously reviewed and chosen from a lot of submissions. The papers hide concerns similar to multimedia and its software, robotization and automation, mechatronics, machine schooling, sleek schooling examine, keep an eye on structures, info mining, wisdom administration, snapshot processing, communique software program, database know-how, man made intelligence, computational intelligence, simulation and modeling, agent dependent simulation, biomedical visualization, machine simulation & modeling, object-oriented simulation, net and protection visualization, imaginative and prescient and visualization, coupling dynamic modeling idea, discretization technique , and modeling process research.
Read or Download Advanced Research on Computer Education, Simulation and Modeling: International Conference, CESM 2011, Wuhan, China, June 18-19, 2011. Proceedings, Part I PDF
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Extra info for Advanced Research on Computer Education, Simulation and Modeling: International Conference, CESM 2011, Wuhan, China, June 18-19, 2011. Proceedings, Part I
Meanwhile, make a convolution between a 3 × 3 template and the each frequency domain to acquire the diagonal edge information. Then the low- frequency coefficients’ edge information EA1 , EA2 , EA3 An Image Fusion Algorithm Based on Discrete Wavelet Transform and Canny Operator of the three directions and the high- frequency coefficients’ 35 ED1 , ED2 , ED3 are all gained. The energy of low-frequency coefficient’s each pixel is defined as follows: EA( x, y ) = EA12 ( x, y ) + EA22 ( x, y ) + EA32 ( x, y) (10) The energy of high-frequency coefficient’s each pixel is defined as follows: ED( x, y ) = ED12 ( x, y ) + ED22 ( x, y ) + ED32 ( x, y ) (11) Calculate each point’s energy E1( x, y ) , E 2( x, y ) of the frequency domain coefficients of original images and make a comparison to determine the fused low-frequency coefficient FA and fused high-frequency coefficient FD (three directions): A1( x, y ) FA( x, y ) = ， EA1( x, y) ≥ EA2( x, y) (12) A2( x, y ) , EA1( x, y ) < EA2( x, y ) D1( x , y ) , ED1( x, y ) ≥ ED 2( x, y ) FD ( x, y ) = (13) D 2( x, y ) , ED1( x, y ) < ED 2( x, y ) Then, implement a consistency verification towards the frequency domain coefficient by a 3 × 3 template, which is an essential part.
On Info-tech and Info-net, pp. 291–295. : Multifrequency channel decompositions of images and wavelet models. IEEE Trans. : Digital image processing, pp. 55–67. : Image Fusion: Theory and Applications, pp. 70–86. : Wavelwt based image fusion techniques——An introduction, review and comparision. : A wavelet-decomposition-based image fusion scheme and its performance evaluation.
What is more, they need to smoothly and gradually transform their thinking pattern from structural programming to object-oriented programming pattern. To achieve these three goals, it is necessary to appeal to the meticulous design of various stages in the whole teaching process. In inculcating the object-orientation thoughts, obstacles caused by complex grammar should be cleared away as clean as possible; on the other hand, in teaching the C++ grammar, the object-orientation thinking pattern should be considered and integrated.