The document discusses image compression techniques. It introduces compression goals of minimizing file size while maintaining quality. It then covers compressing grayscale images using global thresholding and Huffman encoding. The document demonstrates this method on a "mask" image, outputting the compression ratio and bits per pixel. It also covers compressing color images using wavelet-based methods like SPIHT. The quality of the compressed "wpeppers" image is assessed using MSE and PSNR metrics.

2. • Starting from a given image, the goal of the
true compression is to minimize the length of
the sequence of bits needed to represent it,
while preserving information of acceptable
quality. Wavelets contribute to effective
solutions for this problem.

3. • In this section, you'll learn to
• Compress using global thresholding and
Huffman encoding
• Uncompress
• Compress using progressive methods
• Handle truecolor images

4. • Compression by Global Thresholding and
Huffman Encoding
• First load and display the grayscale image mask.
• load mask;
• image(X) axis square;
• colormap(pink(255))
• title('Original Image: mask')

5. wcompress
• %--------------------------------------------------------------
• % Compression and uncompression of a truecolor image
• % and computed MSE and PSNR error values.
• % Compression parameters are the same as those used for example 3,
• % but using the 'spiht_3d' method give better performance yet.
• %--------------------------------------------------------------
• X = imread('wpeppers.jpg');
• [cr,bpp] = wcompress('c',X,'wpeppers.wtc','spiht','maxloop',12)
• Xc = wcompress('u','wpeppers.wtc');
• delete('wpeppers.wtc')
• D = abs(double(X)-double(Xc)).^2;
• mse = sum(D(:))/numel(X)
• psnr = 10*log10(255*255/mse)
• % Display the original and the compressed image
• subplot(1,2,1); image(X); title('Original image'); axis square
• subplot(1,2,2); image(Xc); title('Compressed image'); axis square

6. Output of the program

7. Output of the program
• cr =
• 1.6527
• bpp =
• 0.3966
• mse =
• 26.7808
• psnr =
• 33.8526

8. Mask wcompress

9. • The achieved Bit-Per-Pixel ratio is actually
about 0.53 (closed to the desired one) for a
compression ratio of 6.7%.

10. Compression code
• load mask;
• image(X)
• axis square;
• colormap(pink(255))
• title('Original Image: mask')
• meth = 'gbl_mmc_h'; % Method name
• option = 'c'; % 'c' stands for compression
• [CR,BPP] =
wcompress(option,X,'mask.wtc',meth,'bpp',0.5)

11. Uncompression code
• %%%%here is the uncompression part
•
•
• option = 'u'; % 'u' stands for uncompression
• Xc = wcompress(option,'mask.wtc');
• colormap(pink(255))
• subplot(1,2,1); image(X);
• axis square;
• title('Original Image')
• subplot(1,2,2); image(Xc);
• axis square;
• title('Compressed Image')
• xlabel({['Compression Ratio: ' num2str(CR,'%1.2f %%')],
...
• ['BPP: ' num2str(BPP,'%3.2f')]})

12. Result quality not bad

13. Nebula compression results
CR =
1.5144
BPP =
0.3635