Linear feature extraction based on complex ridgelet transform

In our previous work, a new dual-tree complex wavelet transform (DT-CWT) model for surface analysis has been built, which solved the problem of the lack of shift-invariance that existed in the first and second generation wavelet models. Unfortunately, the DT-CWT model still has the same problem as the previous wavelet models in the lack of ability to detect line singularities or higher dimensional singularities, which causes the edges not to be smooth when extracting the directional features from engineering surfaces. In this paper, a complex finite ridgelet transform (CFRIT), which provides approximate shift invariance and analysis of line singularities, is proposed by taking the DT-CWT on the projections of the finite Radon transform (FRAT). The Numerical experiments show the remarkable potential of the methodology to analyse engineering and bioengineering surfaces with linear scratches in comparison to wavelet-based methods developed in our pervious work.