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Image compression using SOFM using Wavelet

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Image compression using SOFM using Wavelet

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18 Oct 2005 (Updated )

SOFM algorithm is one of the Method for Image compression ...

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Description

The main objective of this project is to implement the concept of wavelet based compression to gray scale images using SOFM.Wavelet Transform is a superior approach to other time frequency analysis tools because its time scale width of the window can be stretched to match the original signal especially for image analysis.By using SOFM technique,we have made an attempt in employing lossy technique i.e., Vector Quantisation to encode the sub bands formed by the application of wavelet Transform.We have also used a clustering property of self organizing Feature Map of Kohonen,an unsupervised training algorithm formulated by Kohonen.Sofm serves as a tool for selecting the best vectors as they are being trained and the codebooks are formed using the trained vectors.Instead of storing the grayscale image,we store only the codebook and their corresponding index values.This reduces the space required to store the image,hence the compression of the image is achieved.

Required Products Wavelet Toolbox
MATLAB release MATLAB 6.0 (R12)
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Comments and Ratings (13)
03 Apr 2014 Mayuri

I have gone through your code. Its good.I will be thankful to you if you send me the code for SOFM algorithm based gray-scale image compression using Wavelets. My email id:mayuri29kalita@gmail.com

16 Nov 2010 win kong

hello. Can i have the function of the SOFM and the concept of it?
Tq..

20 Apr 2009 hbu 

I also have a very little knowledge on SOFM ,but i will study it hard.

21 Mar 2008 tarik piere

hello

25 Dec 2007 sai ram krishna

i studied all the concept its excellent.....
i hav a very little knowledge on SOFM soo can i know where the concept of SOFM is used and what r the functions of the SOFM used..??

21 Mar 2007 CHANDRA SEKHAR

GOOD

05 Oct 2006 jay johnson

excuse me.can i ask what are the codebook and block size?the value...
tq

28 Mar 2006 nishul ben  
28 Mar 2006 Kareen nasar  
27 Mar 2006 shenus n  
27 Mar 2006 jeorge paul  
27 Mar 2006 mathi k  
26 Mar 2006 vidhya k  

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