• Matlab
  • Simulink
  • NS3
  • OMNET++
  • NS2


Matlab is generally used to stimulate the processing technique. Matlab is very easy to use it does not require variables to be initialized before using.Matlab Based Projects has many variety of computations and built-in routines.It has lots of toolboxes and additional functions in it for modeling and simulating in efficient manner.DIP is executed by using matlab. It is considered as many dots which enhances brightness with it. These dots are nothing but pixels. A image is basically a two –dimensional function f(x,y)  where x and y are called plane coordinates, and the amplitude coordinates are called as the intensity of the image at any particular point.


Commonly used mathematical calculation in Matlab Based projects are as follows:

  • Curve filtering.
  • Transforms.
  • Various other special functions.
  • Integration.
  • Data analysis.
  • Numerical calculations.
  • Calculus and differential.
  • Statistics.
  • Algebraic equations.
  • Non-linear functions.
  • Linear algebra.
  • Dealing with matrices and arrays.
  • 2-D and 3-D plotting and graphics.

Image Enhancement are used in cases likes:

  • Enhancement of dark image.
  • Removing noise from image.
  • Highlighting the edges of objects in an image.


Image Enhancement is the method of improving the quality of digital image by means of undergoing some software techniques. Using parallel computing in image is the core objective in image enhancement. Stimulated annealing algorithm can be known easily from solid annealing principle, like, the solid is heated high , allow it to slowly cool and again heat then the solid internal particle with temperature rises to the disordered shape also the internal energy increase. Now the cooling particles slowly orders gradually, and in each temperature it is allowed to reach the equilibrium level, And at least when it reaches ground state the internal energy is lessen to minimum.

Genetic algorithm is an approach to learning and optimization established on concept of biological evolution. Matlab projects are easy to construct and their execution does not require a huge amount of cache. This is a sufficient choice for optimization problems.

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