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This paper presents a new method based on curvelet transform to assess damage location in plate structures.
To reduce bandwidth requirement and power consumption, a compression technique is proposed based on curvelet transform before image encryption, with special technique of coefficient elimination by which a higher compression ratio can be obtained without much loss in image information.
In order to overcome this issue, first, we propose to find the most robust area of the image against rotation based on curvelet transform and mark that point as principle orientation; then perform an alignment by cycle-shifting the feature vector with reference to principle orientation.
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The algorithms in the top three rows are based on curvelet transformation, which are shown to outperform earlier multiscale-based texture classification methods.
It is observed that, fusion methodology based on the Curvelet transform has given curved visual details better than those given by the Wavelet fusion algorithm.
After this, certain watermarking schemes based on curvelet domain have been proposed[12, 13].
In [11], image Hash was generated and embedded into a host image based on multi-scale curvelet transform.
The localization techniques are, respectively, based on adapted Fourier transform and frequency-wavenumber transform.
Based on Arnold transform and discrete fractional angular transform, a double image encryption algorithm is designed.
Nonsubsampled contourlet transform is proposed based on contourlet transform.
De-noising based on wavelet transform footprints [26, 27].
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