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In this paper, we introduce a new SAR despeckling method based on directionlet transform using Bayesian MAP estimator.
A new denoising algorithm based on directionlet transform using a Cauchy probability density function (PDF) is proposed to remove speckle noise.
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The article provides an infrared and visible image fusion algorithm based on directionlets transform.
Figure 2a,b shows, respectively, represent the infrared and visible images of the airfield, and the two images contain much detail and texture information; Figure 2c represents the fusion result based on the Laplacian pyramid transform; Figure 2d represents the fusion result based on the fusion of the wavelet transform; Figure 2e represents the fusion results based on directionlets transform.
The article puts forward an infrared and visible fusion algorithm based on the directionlets transform.
The study demonstrates that the compressive sensing image fusion algorithm based on directionlets has a number of perceived advantages.
The localization techniques are, respectively, based on adapted Fourier transform and frequency-wavenumber transform.
The proposed scheme is based on the differential transform method (DTM), Laplace transform and Padé approximants.
Nonsubsampled contourlet transform is proposed based on contourlet transform.
De-noising based on wavelet transform footprints [26, 27].
Based on Arnold transform and discrete fractional angular transform, a double image encryption algorithm is designed.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com