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Dept     : ECE
Sem      : 5
Regul    : 2019
Faculty : S.V.Lakshmi
phone  : NIL
E-mail  : lakshmi.s.v.ece@snsct.org
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Announcements

  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:</br>Digital image processing system-Fundamental steps in digital image processing, </br>Digital image processing system-Fundamental steps in digital image processing, </br>Structure of human eye, Image formation, </br>Components of an image processing system, </br>Brightness adaption and discrimination, </br>Basic concepts in sampling and quantization, Representing digital images, </br>Neighbours of a pixel, Adjacency, Connectivity, Regions and Boundaries, </br>Distance measures, A simple image formation mode, </br>Image transforms- Properties of 2D DFT,DCT, </br>SVD transform , Wavelet transform, </br>Image Enhancement: Histogram processing-Histogram equalization

  • Question Bank

    Dear Students the Question Bank has been uploaded for the following topics:</br>DIGITAL IMAGE BPROCESSING FUNDAMENTALS, </br>IMAGE ENHANCEMENT AND HISTOGRAM PROCESSING

  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:</br>Matching, Local histogram processing, </br>Noise models- Inverse filtering, </br>Geometric transformation, </br>Image Restoration: A model of image degradation/Restoration process, </br>Histogram statistics for image enhancement

  • Youtube Video

    Dear Students the Youtube Video has been uploaded for the following topics:</br>Digital image processing Introduction</br>Human Visual Systenm

  • Question Bank

    Dear Students the Question Bank has been uploaded for the following topics:</br>IMAGE COMPRESSION, </br>IMAGE COMPRESSION

  • Lecture Notes

    Dear Students the Lecture Notes has been uploaded for the following topics:</br>Wiener Filtering, </br>8 Constrained least mean square filtering, </br>Geometric transformation, </br>Matching, Local histogram processing, </br>Smoothing linear filters, Sharpening spatial filters, </br>Image compression: Need for compression, </br>Huffman Coding, Arithmetic coding, </br>Run length coding, </br>Lossy compression – Transform coding , </br>Wavelet coding, </br>Line detection, Edge models, Basic edge detection, </br>Region based segmentation- region growing