Enhancement Sushisen algorithms in Images analysis Technologies to increase computerized tomography images
| Autor: | Ishwar Baidari, M. Suganya, S. P. Sajjan, P. Senthil |
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| Rok vydání: | 2020 |
| Předmět: |
Logarithm
Computer Networks and Communications Computer science Applied Mathematics media_common.quotation_subject 020206 networking & telecommunications 02 engineering and technology Image enhancement Field (computer science) Computer Science Applications Image (mathematics) Computational Theory and Mathematics Artificial Intelligence Histogram 0202 electrical engineering electronic engineering information engineering Contrast (vision) 020201 artificial intelligence & image processing Tomography Noise (video) Electrical and Electronic Engineering Algorithm Information Systems media_common |
| Zdroj: | International Journal of Information Technology. 14:375-387 |
| ISSN: | 2511-2112 2511-2104 |
| DOI: | 10.1007/s41870-020-00429-5 |
| Popis: | Contrary to one of the major problems in computer tomography image analysis, Image enhancement can be used to improve the clarity and quality of the picture or to provide better conversion presentation for further processing. Contrast growth of one of the acceptable methods for image enhancement in various applications in the medical field is increased. It will help to show and remove brain myocardial infarction, cancer and cancer related details from CT images. In contrast to CT images, a comparison learning of five contrasting techniques has been presented in this paper. Types of technology include electric law conversion, logarithmic change, histogram equations, contrast pulling and lap less changes, all of these techniques are compared to each other, so that it can be achieved that a better CT image is in contrast. To compare technical parameters, peak signals are used for noise ratio (PSNR) and mean class error. Logarithmic result provides an image with clear and Sushisen algorithms better quality than all other techniques and has the highest PSNR value. Comparative findings are a better way for future studies, especially for unusual images of CT images due to brain damage. |
| Databáze: | OpenAIRE |
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