Skip to content

Two lossy algorithms, Discrete Wavelet Transform (DWT) and Vector Quantization (VQ) are added together to compress medical images and see their performance.

Notifications You must be signed in to change notification settings

mahajananshul/Image_Compression_using_Wavelet_Transform_and_Vector_Quantization

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Image_Compression_using_Wavelet_Transform_and_Vector_Quantization

Image compression using various techniques is always evolving concept. Modifying various techniques to best fit different needs is what derives innovation in the field. One such modification is combining two lossy algorithms, Discrete Wavelet Transform and Vector-Quantization to process medicinal images. The question is to see how this algorithm performs universally for image compression. The effect of both Discrete Wavelet Transform (DWT) and Vector-Quantization (VQ) are discussed and how they merge into one algorithm is shown. Different preprocessing techniques can be added as per the applications of the algorithm.

About

Two lossy algorithms, Discrete Wavelet Transform (DWT) and Vector Quantization (VQ) are added together to compress medical images and see their performance.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages