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Thermal imagesdenoisingusing multi-algorithms | ||
| Journal of College of Education | ||
| Article 1, Volume 0, Issue 5, 2017, Pages 255-266 | ||
| Author | ||
| Ameen A. Noor | ||
| Abstract | ||
| The measuring of digital image quality was important for many image processing applications. In this study, the conversion wavelet on the thermal images application for the purpose of improvement and the study of preference thermal images by evaluating the quality of these images through the application of a set of quality metrics’ objectivity known, such as image Fidelity (IF), the similarity synthetic coefficient (SSIM), square error rate (MSE), synthetic content (SC), the peak signal to noise ratio (PSNR), average difference (AD), etc.. In order to reach the goal of the study, the study came to three steps:First step: Add noise to the original image of the types (speckle -localvar -gaussian–poisson).Second step: remove noise from images added by applying wavelet conversionby applying sevenfamilieswavelet conversion techniques (haar, db, sym, bior, coif, rbio, dmey)and used algorithms to remove noise by the use of the technique (SOMA) and technique (threshold). Third step: through the comparison between the wavelet way and algorithms and show through the image quality and techniques of quality algorithms to remove noise (SOMA-Threshold) better quality than using wavelet according as showing in results out on the search. | ||
| Keywords | ||
| noise and denoise; wavelet; SOMA; images quality; Threshold | ||
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