Title :
Image De-noising Based on Nonparametric Adaptive Estimation in the Finite Ridgelet Domain
Author :
Li, Li ; Yuhua, Peng ; Mingqiang, Yang ; Peijun, Xue
Author_Institution :
Sch. of Inf. Sci. & Eng., Shandong Univ., Jinan
Abstract :
Ridgelet is a new signal analysis method which is especially suitable for describing the 2-D signals which have linear or super-plane singularities. Recently, an orthonormal version of ridgelet for discrete and finite-size images has been presented, named finite ridgelet transform (FRIT). In this paper, we propose a new image de-noising method by FRIT with the threshold based on nonparametric adaptive estimation. Experiments show that this method represents the better characteristic than the traditional de-noising methods in wavelet domain and the de-noising methods based on donoho strategy
Keywords :
adaptive estimation; image denoising; nonparametric statistics; wavelet transforms; FRIT; finite ridgelet transform; image denoising; nonparametric adaptive estimation; orthonormal version; super-plane singularities; wavelet domain; Adaptive estimation; Continuous wavelet transforms; Discrete transforms; Image denoising; Noise reduction; Parametric statistics; Signal analysis; Wavelet analysis; Wavelet domain; Wavelet transforms;
Conference_Titel :
Communications, Circuits and Systems Proceedings, 2006 International Conference on
Conference_Location :
Guilin
Print_ISBN :
0-7803-9584-0
Electronic_ISBN :
0-7803-9585-9
DOI :
10.1109/ICCCAS.2006.284626