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Medical imaging is widely used in detection of tumors and other diseases. In medicine, the enormous use of digital imaging, the quality of images becomes an important issue. The basic problem found in it is the introduction various kinds of noises whose removal becomes difficult. The technologies are working on civilizing the excellence and resolution of images but these forms as one of the major face to de-noise the image and recover its perception. This paper represents the complete review of various filters and their comparative analysis which can be used with statistical parameters in digital image processing. We can simulate the various statistical parameters and view their results using plots. We can have their relative study with the aid of MATLAB simulation to relieve the selection of best filter for a particular noise introduced in MRI and USG image.
Manasi Rana. 2015. \u201cA Review on Statistical Analysis of Filters on Various Noises in MRI and USG Images\u201d. Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 15 (GJCST Volume 15 Issue G1): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Total Score: 101
Country: India
Subject: Global Journal of Computer Science and Technology - G: Interdisciplinary
Authors: Manasi Rana (PhD/Dr. count: 0)
View Count (all-time): 261
Total Views (Real + Logic): 8330
Total Downloads (simulated): 2082
Publish Date: 2015 06, Thu
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Medical imaging is widely used in detection of tumors and other diseases. In medicine, the enormous use of digital imaging, the quality of images becomes an important issue. The basic problem found in it is the introduction various kinds of noises whose removal becomes difficult. The technologies are working on civilizing the excellence and resolution of images but these forms as one of the major face to de-noise the image and recover its perception. This paper represents the complete review of various filters and their comparative analysis which can be used with statistical parameters in digital image processing. We can simulate the various statistical parameters and view their results using plots. We can have their relative study with the aid of MATLAB simulation to relieve the selection of best filter for a particular noise introduced in MRI and USG image.
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