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In this work, we employ a pair wise Markov Random Field (MRF) and a Conditional Random Field (CRF) for bi-level image segmentation and denoising. For both tasks, the Ising pair wise model and the Iterative Conditional Mode (ICM) inference method are implemented, assuming the parameters of the unary and pair wise potentials are known. Experimental results demonstrate the effectiveness of the proposed...
In this paper, under the non-local means framework, we propose a non-local bilateral filter algorithm for image denoising based on the neighborhoods' gray value and the corresponding neighborhoods' Gaussian curvature. We also adopt a new method to provide the optimum denoising parameter h based on the discrete wavelet transform and the smoothing spline estimation. Meanwhile the generalized cross-validation...
Image denoising usually needs to estimate noise variance. In order to avoid estimating the noise variance and remove the white Gaussian noise from image, a denoising method based on adaptive sparse representation was proposed. It trains the initialized dictionary based on training samples constructed from noised image. The training process is finished by an iteration algorithm which alternates between...
Electrocardiogram (ECG) signal's noise reduction is critical for ECG automatic diagnosis and analysis, and the de-noising result directly affects the accuracy of ECG parameter extraction even the patients' illness diagnosis and analysis. ECG signals are often seriously distorted by noises with the characteristics of low signal-noise ratio and non-stationary stochastic property, especially for P wave...
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