Image compression using SOFM using Wavelet
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.
Cite As
Aarathy M (2024). Image compression using SOFM using Wavelet (https://www.mathworks.com/matlabcentral/fileexchange/8746-image-compression-using-sofm-using-wavelet), MATLAB Central File Exchange. Retrieved .
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Version | Published | Release Notes | |
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1.0.0.0 |