A Fast Directional Sigma Filter for Noise Reduction in Digital TV Signals

This paper proposes a structure-oriented multidirectional Sigma filter for additive white Gaussian noise in digital TV signals. Filtering is restricted to homogeneous directions to reduce blurring by analyzing local structure using directional second derivatives. The proposed filter improves the Sigma estimate of denoised pixels by imposing a homogeneity constraint on the noise-adaptive selection of estimation pixels by the Sigma filter. It achieves noise-reduction gains of up to 4.8 dB Peak-Signal-to-Noise Ratio (PSNR) in real-time. The block size, shape and coefficients of the filter are adapted to both structure and noise level. The goal is to optimize the filter with regard to noise-reduction gain and structure preservation. A possible hardware-oriented design of the proposed filter is also presented. To show the effectiveness of the proposed method, comparisons between the proposed Sigma filter and referenced Sigma filters in terms of the PSNR gain and the modulation transfer function (MTF) are shown. Results show that the proposed method achieves a higher PSNR gain and contrast transfer ratio than referenced Sigma filters.