Additive noise is one among the prominent types of noises which degrades the quality of images. A very large number of algorithms, in spatial, frequency and wavelet domain have been proposed to enhance images corrupted with additive noise. All the methods suggested have their own advantages as well as disadvantages. With the availability of parallel processing capability, in low end workstations and systems, fusion of two or more de-noising methods has become a topic of interest. In this paper, we have implemented one of the recent contributions to mean filter - a fuzzy filter. Also, as a complementary filter, the basic Non Local Means filter is implemented. Experiments were carried out by fusing the results obtained through the two filters. The results obtained establish the merit of the fusion approach.
CITATION STYLE
Raju, G., Wahid, F. F., & Sugandhi, K. (2017). Additive noise removal by combining non local means filtering and a local fuzzy filter – A fusion approach. In Communications in Computer and Information Science (Vol. 721, pp. 30–39). Springer Verlag. https://doi.org/10.1007/978-981-10-5427-3_4
Mendeley helps you to discover research relevant for your work.