A New Contourlet Transform With Adaptive Directional Partitioning

A new image sparse representation tool—adaptive contourlet transform (ACT) is introduced in this letter. Adaptive directional partitioning schemes in ACT can match the arbitrary orientation distribution of natural image, which brings sparser representation. The proposed ACT is based on pseudopolar Fourier transform that has similar geometrical structure to fan filter. This characteristic helps ACT out of the difficulty of designing traditional directional filter bank. Simulation results demonstrate that ACT can provide more efficient image sparse representation compared to contourlet transform.

[1]  Reza Kheradmand,et al.  Noise reduction in selective computational ghost imaging using genetic algorithm , 2017 .

[2]  Guangming Shi,et al.  Nonuniform Directional Filter Banks With Arbitrary Frequency Partitioning , 2011, IEEE Transactions on Image Processing.

[3]  Ma Yide,et al.  Image denoising via bivariate shrinkage function based on a new structure of dual contourlet transform , 2015 .

[4]  Dan Wu,et al.  Image enhancement based on contourlet transform , 2019, International Conference on Photonics and Optical Engineering and the Annual West China Photonics Conference.

[5]  D. Donoho,et al.  Fast and accurate Polar Fourier transform , 2006 .

[6]  Minh N. Do,et al.  Ieee Transactions on Image Processing the Contourlet Transform: an Efficient Directional Multiresolution Image Representation , 2022 .

[7]  Pengpeng Zhao,et al.  Blocking Contourlet Transform: An Improvement of Contourlet Transformand Its Application to Image Retrieval , 2012, J. Comput..

[8]  Minh N. Do,et al.  A New Contourlet Transform with Sharp Frequency Localization , 2006, 2006 International Conference on Image Processing.

[9]  Andrea Montanari,et al.  Accurate Prediction of Phase Transitions in Compressed Sensing via a Connection to Minimax Denoising , 2011, IEEE Transactions on Information Theory.

[10]  M. Omair Ahmad,et al.  A Study of Multiplicative Watermark Detection in the Contourlet Domain Using Alpha-Stable Distributions , 2014, IEEE Transactions on Image Processing.

[11]  Yide Ma,et al.  Image denoising via bivariate shrinkage function based on a new structure of dual contourlet transform , 2015, Signal Process..

[12]  Vikrant Bhateja,et al.  Multimodal Medical Image Sensor Fusion Framework Using Cascade of Wavelet and Contourlet Transform Domains , 2015, IEEE Sensors Journal.

[13]  Yu Zhang,et al.  Image compressed sensing based on wavelet transform in contourlet domain , 2011, Signal Process..