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Research Paper | Biomedical Sciences | Volume 9 Issue 1, January 2020 | Pages: 65 - 68 | Saudi Arabia
Improvement of Dental X-rays Images using Image Processing Techniques
Abstract: This thesis proposed a procedure for effective statistical noise analysis in dental rays. A Gaussian scale blend has been used to satisfy non-linearity dispersion to improve the quality of images after denoisation. Current methods are based on a filter based on insignificant details. The traditional theory of gaseous and poison diffusion seems only to overestimate noise variance in low-intensity areas (small photon counts).20 experiments from 20 panorama pictures test the retrospective method, and medical experts back the findings. Secondly, the general image has been maintained; secondly, the diagnostic data on the photo are preserved, and thirdly, the scene diagnostics section defines small details of low contrast. As illustrated above, state-of - the-art approaches have poor results. This new approach is followed by an attempt to see the problem from BSS ' perspective in order to see the panorama as a simple combination of (unwanted) background, observational and noise information.
Keywords: Dental Images, image, processing, MatLab
How to Cite?: Tariq Alqahtani, "Improvement of Dental X-rays Images using Image Processing Techniques", Volume 9 Issue 1, January 2020, International Journal of Science and Research (IJSR), Pages: 65-68, https://www.ijsr.net/getabstract.php?paperid=ART20203850, DOI: https://dx.doi.org/10.21275/ART20203850