Image Compression using Wavelet
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The following implementation steps have been made for the devised algorithm, which is based on 2D-wavelet.
1. Reading an image of either gray scale or RGB image.
2. Converting the image into grayscale if the image is RGB.
3. Decomposition of images using wavelets for the level N.
4. Selecting and assigning a wavelet for compression.
5. Generating threshold coefficients using Birge-Massart strategy.
6. Performing the image compression using wavelets.
7. Computing and displaying the results such as compressed image, retained energy and Zero coefficients.
8. Decompression the image based on the wavelet decomposition structure.
9. Plotting the reconstructed image.
10. Computing and displaying the size of original image, compressed image and decompressed image.
Cite As
Jebakumari Beulah (2024). Image Compression using Wavelet (https://www.mathworks.com/matlabcentral/fileexchange/20501-image-compression-using-wavelet), MATLAB Central File Exchange. Retrieved .
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- Image Processing and Computer Vision > Image Processing Toolbox > Image Segmentation and Analysis >
- Signal Processing > Wavelet Toolbox > Denoising and Compression >
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1.0.0.0 |