Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Two-dimensional signal and image processing
Two-dimensional signal and image processing
Estimation of noise in images: an evaluation
CVGIP: Graphical Models and Image Processing
Image Processing, Analysis, and Machine Vision
Image Processing, Analysis, and Machine Vision
A modified sigma filter for noise reduction in images
ICCOM'05 Proceedings of the 9th WSEAS International Conference on Communications
Noise reduction by fuzzy image filtering
IEEE Transactions on Fuzzy Systems
Block-based noise estimation using adaptive Gaussian filtering
IEEE Transactions on Consumer Electronics
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This paper is a study on image noise reduction of modified sigma filter using image decomposition. Conventional sigma filter has been shown to be a good solution both in terms of filtering accuracy and computational complexity. However, the sigma filter does not preserve well small edges especially for high level of additive noise. In this paper, we propose here a new method using a modified sigma filter. In our proposed method the input image is first decomposed in two components that have features of horizontal, vertical and diagonal direction. Then, two components are applied HPF and LPF. By applying a conventional sigma filter separately on each of them, the output image is reconstructed from the filtered components. Added noise is removed and our proposed method preserves the edges from the image. Comparative results from experiments show that the proposed algorithm achieves higher gains, on average, 2.6 dB PSNR than the sigma filter and 0.5 dB PSNR than the modified sigma filter. When relatively high levels of noise added, the proposed algorithm shows better performance than two conventional filters.