In this paper, we analyze and compare the performance of fusion methods based on four different transforms: i) wavelet transform, ii) curvelet transform, iii) contourlet transform and iv) nonsubsampled contourlet transform. Fusion framework and scheme are explained in detail, and two different sets of images are used in our experiments. Furthermore, eight different performancemetrics are adopte...

Breast cancer is one of the most important causes of increased women death rate in the world. Mammography is the most efficient approach for the early identification of breast diseases. The major objective of mammography is to identify small, non-palpable cancers during its premature stage. On the other hand, mammograms are extremely complicated to interpret being the fact that the pathological...

In seismic data processing, the reconstruction and interpolation of missing traces are essential tasks. To overcome limitations irregularly sampled data, this paper proposes a method combining smoothing fast iterative soft threshold algorithm (SFISTA) curvelet transform; uses domain as sparse domain. For comparison, contourlet transform is used for different domains, shrinkage-thresholding (FIS...

Many of the geophysical data analysis problems, such as signal-noise separation and data regularization, are conveniently formulated in a transform domain, where the signal appears sparse. Classic transforms such as the Fourier transform or the digital wavelet transform, fail occasionally in processing complex seismic wavefields, because of the nonstationarity of seismic data in both time and s...

Designing a completely automatic and efficient face recognition system is a grand challenge for biometrics, computer vision and pattern recognition researchers. Generally, such a recognition system is able to perform three subtasks: face detection, feature extraction and classification. We’ll put our focus on feature extraction, the crucial step prior to classification. The key issue here is to...

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