The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. The term image registration is most commonly used to denote the process of alignment of images , that is of transforming them to the common coordinate system. This is done by optimizing a similarity measure between the two images. A widely used measure is Mutual Information (MI). This method requires estimating joint histogram of the two images. Experiments are presented that demonstrate the approach. The technique is intensity-based rather than feature-based. As a comparative assessment the performance based on normalized mutual information and cross correlation as metric have also been presented.
-The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. Mutual Information is the similarity measure used in this case for optimizing the two images. This method requires estimating joint histogram of the two images. The fusion of images is the process of combining two or more images into a single image retaining important features from each. The Discrete Wavelet Transform (DWT) has become an attractive tool for fusing multimodal images. In this work it has been used to segment the features of the input images to produce a region map. Features of each region are calculated and a region based approach is used to fuse the images in the wavelet domain.
Wireless technology has been evolving at a breakneck speed. The total number of
cell-phones in use (as of 2011) was over 6 billion for a 7 billion world population [1]
constituting 87% of the world population. Additionally, with user convenience be-
coming paramount, more and more functions are being implemented wirelessly.
The first Third Generation Partnership Project (3GPP) Wideband Code Division
Multiple Access (WCDMA) networks were launched during 2002. By the end of 2005
there were 100 open WCDMA networks and a total of over 150 operators having
frequency licenses for WCDMA operation. Currently, the WCDMA networks are
deployedinUniversalMobileTelecommunicationsSystem(UMTS)bandaround2GHz
in Europe and Asia including Japan and Korea. WCDMA in America is deployed in the
existing 850 and 1900 spectrum allocations while the new 3G band at 1700/2100 is
expected to be available in the near future. 3GPP has defined the WCDMA operation
also for several additional bands, which are expected to be taken into use during the
coming years.
The information technology (IT) revolution is surely coming in this century, just
as did the agricultural and industrial revolutions that have already so enriched our
lives. As the IT revolution progresses, it is expected that almost all social struc-
tures and economic activities will be changed substantially
Recent decades have shown a tremendous expansion of the Internet. The number of
connected terminals has increased by orders of magnitude, traffic has grown exponen-
tially, coverage has become ubiquitous and worldwide, and today’s sophisticated Web
2.0 applications are increasingly providing services which hitherto have been the realm
of telecommunications, such as Skype and video conferencing. This has even led to the
thought that access to the Internet might one day be a universal right of every citizen.
This evolution will accelerate in the coming decades.
Under the Energy Independence and Security Act of 2007 (EISA), the National Institute of
Standards and Technology (NIST) was assigned “primary responsibility to coordinate
development of a framework that includes protocols and model standards for information
management to achieve interoperability of Smart Grid devices and systems…” [EISA Section
1305]. 35 This responsibility comes at a time when the electric power grid and electric power
industry are undergoing the most dramatic transformation in many decades. Very significant
investments are being made by industry and the federal government to modernize the power grid.
To realize the full benefits of these investments—and the continued investments forecast for the
coming decades—there is a continued need to establish effective smart grid 36 standards and
protocols for interoperability.
This example shows how you can use signal functions in the Visiondebugger to simulate a signal that is coming into one of the analog inputs of the LPC21xx.The Measure example is described in detail in the Getting StartedUser's Guide.The MEASURE example program is available for several targets:Simulator: uVision Simulator for LPC2129MCB2100: Keil MCB2100 evaluation board with ULINK debugger - Application is loaded to internal Flash. - Switch S2 (INT1) is used as GPIO and sampled (jumper positions: J1= off, J7= on) - potentiometer POT1 is sampled as AIN0 (jumper position: J2= on) - serial port COM1 parameters: 9600 baud, no parity, 8-bits, 1 stop bit, flow control noneMCB2130: Keil MCB2130 evaluation board with ULINK debugger - Application is loaded to internal Flash. - Switch S2 (INT1) is used as GPIO and sampled (jumper positions: J1= off, J7= on) - potentiometer POT1 is sampled as AIN1 (jumper position: J2= on) - serial port COM1 parameters: 9600 baud, no parity, 8-bits, 1 stop bit, flow control none
