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% SIO135/236 Lab 5, Spring 2009
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clear
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% Problem 1) Image contrast enhancement
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% read and display the thermal infrared band
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ir = fread( fopen( 'band6c.raw', 'r'), [1500 1500], '*uint8')';
figure(1),colormap('gray')
imshow(ir)
title( 'Original Data' );

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% linear contrast stretch (set display limits in imshow)
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min_pixel = min( min( ir ) );
max_pixel = max( max( ir ) );

figure(2),colormap('gray'),

title( 'Linear Stretch' );

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% histogram equallization using built-in matlab function histeq()
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figure(3),colormap('gray')

title( 'Histogram Equalization' );

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% look at the histogram for each
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figure(4),colormap('gray');
subplot(2,1,1), imhist(ir);

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% Problem 2)
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% read in 3 bands
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% look at the RGB image with contrast enhancement
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rgb = cat(3, rd, gr, bl );
figure(5), imshow(rgb), title( 'RGB Image' );

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% enhance the contrast in each band, and look at the histogram for each
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figure(6);
subplot(3,2,1), imhist(rd), title('Red');
rdeq = histeq(rd);
subplot(3,2,2), imhist(rdeq), title('Red Equalized');

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% combine the equalized bands and have a look
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figure(7);
rgbeq = cat( 3, rdeq, greq, bleq );
imshow(rgbeq), title( 'RGB Equalized' );


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% Problem 3) image enhancement through filtering
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% load & show the un-touched image
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bl = fread( fopen( 'band1c.raw', 'r'), [1500 1500], '*uint8')';
figure(8),colormap('gray'),
imagesc( bl ),
title('Original');

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% apply a smoothing filter
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smoothfilt=[1/9, 1/9, 1/9; 1/9, 1/9, 1/9; 1/9, 1/9, 1/9]

bl_smooth = filter2( smoothfilt, bl );
figure(9),colormap('gray'),
imagesc( bl_smooth ),
title('Smoothed');

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% apply a sharpening filter
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% illuminate from the northwest
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% Problem 4) compute the vegetation index
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% read in apropriate bands and convert them to doubles.
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red = double(fread( fopen( 'band3c.raw', 'r'), [1500 1500], '*uint8')');
ir = double(fread( fopen( 'band4c.raw', 'r'), [1500 1500], '*uint8')');

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% compute the vegetation index band transformation and display with imagesc
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