Feature Extraction On AN Image

DWT is an algorithm used to reduce dimensionality of an image, feature extraction process. DWT algorithm decomposes the image into 4 sub-band (sub-image) ie,LL,LH,HL,HH.

I Have an Image I am practicing on (cameraman.tif) , and I decomposed it 3 times on the LL subband (I have LL1, LL2 and LL3). Apprently you can extract features from an decomposed image. But I dont know what features i could extract from an image and also and more importantly HOW TO EXTRAXT the features from the image....Can anyone explain?

Answer 1

[Prabhan Purwar]

Hi,

The purpose of feature extraction technique in image processing is to represent the image in its compact and unique form of single values or matrix vector. Low level feature extraction involves the automatic extraction of features from an image without doing any processing method.

DWT is used for high level feature extraction to investigate the characteristic of narrow and broad band. You may apply further processing to the coefficient values to extract the image feature vectors (refer to literature for various methods) or retain coefficients itself as a feature vector.

Kindly have a look at the following link:

• https://www.mathworks.com/help/wavelet/ref/dwt2.html#description

Thanks