5/1/2023 0 Comments Matlab denoise![]() It is also efficient in representing curve-like edges. The 2nd generation Curvelet transform is an efficient tool in numerous applications including image processing, seismic data exploration, fluid mechanics, and solving partial differential equations. In 2000, they introduced 1st and 2nd generation Curvelet transform, called Ridgelet transform-based Curvelet transform. It was regarded as an anisotropic geometric wavelet transform. Ridgelet transform was proposed by Candes and Donoho in 1999. However, it is difficult to design complex wavelets with perfect reconstruction properties and filter characteristics. ![]() The complex transform is one way to improve directional selectivity. Wavelets are effective in capturing coefficients along the horizontal, vertical, and diagonal axes but poor in determining coefficients along the curvature. A huge disadvantage of wavelets is that they are not directional. ![]() Theoretical background of Curvelet transformĬurvelet transform is a geometric scale transform, used to represent edges and curves more efficiently than traditional wavelets.
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