Image Compression Using Modified Haar Wavelet Transform Matlab Project Source Code
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ABSTRACT
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Haar transform is one of the simplest and basic transformation from the multi-resolution spectrum. The attracting features obtained from Haar transform make it a potential candidate in modern applications, such as signal and image compression. The Haar wavelet transform provides mean values that compress the image so that it takes up much less storage space, and therefore transmits faster electronically and in progressive levels of detail. The main objective of this work is to modify the weighting factor in order to study their effects on image compression. This paper tries to implement different scale of weighting factor and study their performance on the overall system of compression. Scale of weighting factor is used in order to prevent the pixel value from exceeding their limits. Different values of weighting factor are applied, these values are spans into two range to evaluate the implemented system.
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Contact:
Mr. Roshan P. Helonde
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Email: roshanphelonde@rediffmail.com
Haar Wavelet Transform–based image compression is a simple yet efficient technique for reducing image size while preserving important visual information. A modified Haar wavelet transform improves the basic Haar method by enhancing energy compaction, reducing artifacts, and achieving better compression performance, especially for natural images.
ReplyDeleteImage compression using wavelets works by transforming the image into different frequency components. The modified Haar transform refines the traditional Haar approach (Image Denoising Projects ) by:
ReplyDeleteAdjusting scaling and wavelet coefficients
Improving representation of edges and textures
Reducing blocky artifacts
This makes it useful in Image Processing Projects For Final Year applications.