what values of an image should I use to produce a haar wavelet?

Question

I currently have a Java program that will get the rgb values for each of the pixels in an image. I also have a method to calculate a Haar wavelet on a 2d matrix of values. However I don't know which values I should give to my method that calculates the Haar wavelet. Should I average each pixels rgb value and computer a haar wavelet on that? or maybe just use 1 of r, g,b. I am trying to create a unique fingerprint for an image. I read elsewhere that this was a good method as I can take the dot product of 2 wavelets to see how similar the images are to each other.

Please let me know of what values I should be computing a Haar wavelet on. Thanks Jess

Answer 1

You should regard the R/G/B components as different images: Create one matrix for R, G and B each, then apply the wavelet to parts of those independently.

You then reconstruct the R/G/B-images from the 3 wavelet-compressed channels and finally combine those to a 3-channel bitmap.

Answer 2

Since eznme didn't answer your question (You want fingerprints, he explains compression and reconstruction), here's a method you'll often come across:

You separate color and brightness information (chrominance and luma), and weigh them differently. Sometimes you'll even throw away the chrominance and just use the luma part. This reduces the size of your fingerprint significantly (~factor three) and takes into account how we perceive an image - mainly by local brightness, not by absolute color. As a bonus you gain some robustness concerning color manipulation of the image.

The separation can be done in different ways, eg transforming your RGB image to YUV or YIQ color space. If you only want to keep the luma component, these two color spaces are equivalent. However, they encode the chrominance differently. Here's the linear transformation for the luma Y from RGB: Y = 0.299*R + 0.587*G + 0.114*B

When you take a look at the mathematics, you notice that we're doing nothing else than creating a grayscale image – taking into account that we perceive green brighter than red and red brighther than blue when they all are numerically equal.

Incase you want to keep a bit of chrominance information, in order to keep your fingerprint as concise as possible, you could reduce the resolution of the two U,V components (each actually 8 bit). So you could join them both into one 8 bit value by reducing their information to 4 bit and combining them with the shift operator (don't know how that works in java). The chrominance should weigh less in comparison to the luma, in the final fingerprint-distance calculation (the dot product you mentioned).