how to find euclidean distance

I have calculated 1080 features for the image using 2d-dual tree discrete wavelet transform(the features include energy, entropy,standard deviation,mean).How to use all these features and calculate euclidean distance. I have 1000 images in my database please give some idea or suggestion about it.

Answer 1

[Jan]

The Euclidean distance can be calculated between two vectors. Do you want to treat the 1080 features as elements of a vector? This would work, but treating all elements equally might be a bad idea: Is the mean and the entropy really equivalent for the wanted distance?

x1 = rand(1, 1080);
x2 = rand(1, 1080);
dist = sqrt(sum((x1-x2).^2));