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Image Processing using Matlab projects

Image processing is nothing but computer imaging, where its benefits are to the human visuals. Image processing using Matlab projects are used to evaluate and employ Image enhancement and data compression of the image.DIP is not continued on a particular area but has a vast knowledge when analyzed. Image processing using matlab projects include three portions. They are as follows

  1. Image Restoration.
  2. Image compression.
  3. Image enhancement.

Image Restoration:

This method is taking some image with a familiar decline value and again storing  it in its original plane.

Image compression:

In compression technique we extract features like segmentation, image morphology and pattern recognition from the image.

Image enhancement:

To highlight certain characteristics of an image we need to bring out specific features from the image. This technique links taking an image and developing it optically by considering the benefits of man’s visual responses.

2015 IEEE Image Processing using Matlab projects

Image Registration in Image processing matlab projects is very important in fields like medical imaging and remote sensing. Pixels in a image has many dots representing grayscale or color value which are given to it. The processing toolbox guides image registration based on intensity.

Masking of image is given with a example like a image of road in remote sensor where the area of road without 50m wide from the centre is masked.

In image processing the input taken is always a form of image may be photograph but the output can be of any form may be an image or characteristics or any parameter related to the image.

Benefits of algebric operation of digital signals are

  • Digital signals achieved from physical signals through transducers.
  • Represented signals are digital sequence of samples.

Compression based technique includes Discrete cosine transformation (DCT) and wavelet based compression technique. But now wavelet based technique is widely used for higher compression ratios by just least loss of data.

he innovations in medical imaging are

  • Approximate diagnosis.
  • Proportion in computer science and micro electronics.
  • Advancement in technology of tissue imaging.

Projects on medical images are done by using matlab. Matlab has many functions and they are widely used for clarifying testing process.

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