Hi,
I need to know the computational complexities to extract the texture feature from an image using the Wavelet Transform . Also, I should know the limitations of Wavelet while it captures texture features from an image. Besides, I need to know the advantages of Gradient Local Auto-correlation texture descriptor over the Wavelet texture descriptor. I expect your invaluable feedback regarding the issue. Thanks in advance!!!!
Dear Farhad Bulbul
The computational complexity of a feature-based texture segmentation algorithm is limited by the dimensional of the feature space[] . In advance, the Wavelet Transform has an overall computational complexity of O(N logN). the state-of-the-art researches declared that the wavelet texture feature has lower accuracy segmentation (negative effect) and lower computational complexity (positive effect) compared to direct texture features. the following reference can help you in this way:
[1] Ng, B.W., 2003. Wavelet based image texture segmentation using a modified K-means algorithm/by Brian W. Ng (Doctoral dissertation).
[2] Bhalerao, Abhir H., and Nasir M. Rajpoot. "Discriminant feature selection for texture classification." (2003).
I hope it can be useful.
Regards
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