Adaptive impulse detection based selective window median filter for removal of random-valued impulse noise in digital images
| Autor: | K. Ashok, V. R. Vijaykumar, A. Kalaiselvi |
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| Rok vydání: | 2016 |
| Předmět: |
business.industry
Applied Mathematics 020206 networking & telecommunications Salt-and-pepper noise 02 engineering and technology Impulse noise Computer Science Applications Gradient noise Noise symbols.namesake Computational Theory and Mathematics Gaussian noise 0202 electrical engineering electronic engineering information engineering Median filter symbols Image noise 020201 artificial intelligence & image processing Computer vision Value noise Artificial intelligence Electrical and Electronic Engineering business Mathematics |
| Zdroj: | COMPEL - The international journal for computation and mathematics in electrical and electronic engineering. 35:1604-1616 |
| ISSN: | 0332-1649 |
| Popis: | Purpose One of the fundamental tasks in the field of image processing is image denoising. Images are often corrupted by different types of noise and the restoration of images degraded with random-valued impulse noise is still a challenging task. The paper aims to discuss these issues. Design/methodology/approach This paper presents an adaptive threshold-based impulse noise detection following by a novel selective window median filter for restoration of RVIN pixels. Findings The proposed method emphasis a local image statistics using an exponential nonlinear function with an adaptive threshold is derived from the rank-ordered trimmed median absolute difference (ROTMAD) are deliberated to detect the noisy pixels. In the filtering stage, a selective 3×3 moving window median filter is applied to restore the detected noisy pixel. Originality/value Experimental result shows that the proposed algorithm outperforms the existing state-of-art techniques in terms of noise removal and quantitative metrics such as peak signal to noise ratio (PSNR), mean absolute error (MAE), structural similarity index metric (SSIM) and miss and false detection rate. |
| Databáze: | OpenAIRE |
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