Actually i am working on medical image classification. can we use the stockwell-transform (s-transform) for feature extraction purpose.
S transform is used widely in classification of signals, I don't think it is applicable for image classification
Yosra Mohammed, image is a two-dimensional signal.
S-transform can be applied in image classification. However, this classification should be performed on images with large amount of texture [1], but I don't know if medical image has this property. I recommend to read this paper and take your own conclusions.
1. Drabycz, S., Stockwell, R.G., & Mitchell, J.R. (2008). Image Texture Characterization Using the Discrete Orthonormal S-Transform. Journal of Digital Imaging.
why don't try it . there are features useful for classification because it give us a pattern .
- Power system disturbance recognition
- S transform has been proven to be able to identify a few types of disturbances, like voltage sag, voltage swell, momentary interruption, and oscillatory transients.[11]
- S transform also be applied for other types of disturbances such as notches, harmonics with sag and swells etc.
- S transform generates contours which are suitable for simple visual inspection. However, wavelet transform requires specific tools like standard multiresolution analysis.
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