|
|
|
| Image De-noising Method Based on Nonparametric Adaptive Density
Estimation in Ridgelet Domain |
| Li Li①; Peng Yu-hua①; Yang Ming-qiang①; Xue Pei-jun② |
| ①School of Information Science and Engineering, Shandong University, Jinan 250100, China;②School of Mathematics, Shandong University, Jinan 250100, China |
|
|
|
|
Abstract Ridgelet is a new signal analysis method; it 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 is presented, named Finite Ridgelet Transform (FRIT). In this paper, a new image de-noising method is proposed by using the threshold method based on nonparametric adaptive estimation which is presented by Birge-Massart in Ridgelet domain. Experiments show that this de-noising method represents better characteristic than traditional de-noising method in wavelet domain and the de-noising method based on Donoho strategy.
|
|
Received: 16 May 2005
|
|
|
|
|
|
|
|
|
2006, Vol. 28 
