Image denoising using two-dimensional GARCH model

被引:0
作者
Amirmazlaghani, M. [1 ]
Amindavar, H. [1 ]
机构
[1] Amirkabir Univ Technol, Dept Elect Engn, Tehran, Iran
来源
2007 14TH INTERNATIONAL WORKSHOP ON SYSTEMS, SIGNALS, & IMAGE PROCESSING & EURASIP CONFERENCE FOCUSED ON SPEECH & IMAGE PROCESSING, MULTIMEDIA COMMUNICATIONS & SERVICES | 2007年
关键词
two-dimensional GARCH model; wavelet transform; image denoising; statistical modeling; MMSE estimation;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we introduce a new method for removing noise from digital images, based on statistical model of wavelet coefficients. We use two-dimensional Generalized Antoregressive Conditional Heteroscedasticity (GARCH) model for statistical modeling of wavelet coefficients. Using two-dimensional GARCH model yields a novel wavelet coefficients model, which is capable of taking into account important characteristics of wavelet coefficients, such as non-stationarity, heavy tailed marginal distribution, and the dependencies between the coefficients. We use Minimum Mean Square Error (MMSE) estimator for estimating the clean wavelet image coefficients. Here, to prove the performance of this method in image denoising, we have compared our proposed method with various image denoising methods.
引用
收藏
页码:149 / 152
页数:4
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