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Matlab image processing projects

An image is considered to contain sub-images referred as regions-of-interest Roles. Images contain lot of objects each can be essentials for a region. Matlab image processing projects are very easy to use. It has many tools in boxes which can be used directly. In Matlab image processing projects , a image we use many filter operations where in the main is convolution with matrix which is called kernel. They are generally 3×3 square matrix. The size of matrix can vary sometime. The values of matlab image processing projects are stored in the kernel which directly relate the results of applying the filter.



Noise addition.
Frequency domain filtering.
Intensity transformation.
Spatial domain filtering.

Noise addition:

This method transforms private aspect by adding noise to provide familiarity. It works by multiplying or adding a random number to the private quantitative attributes.

Frequency domain filtering:

Here the reaction of applying a filter to a signal is to multiply the signal spectrum to that of filter spectrum. The resultant is the combination of both input signals and filter.

Intensity transformation:

This process increases the contrast of the image quality and also enables to simulate intensity distortion.

Spatial domain filtering:

This filtering is a design of FIR filtering. Here the weights of the masks are in rectangular pattern. It is sliding the mask along the image and gives more operation on the pixels which are fully mask covered.

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