| Autor: |
Girija, M. G., Shanavaz, K. T., Ajith, G. S. |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2020, Vol. 2222 Issue 1, p030009-1-030009-9, 9p, 2 Charts, 3 Graphs |
| Abstrakt: |
Nowadays quality of outdoor as well as indoor images are very important. But outdoor images are deteriorated by haze, fog, rain etc. These atmosphere conditions adversely affect the visibility of the images and reduces the contrast. It is very much adverse in applications especially in military. Image de-hazing algorithm are commonly used to restore the original image which is affected by haze. Fine details in the images are lost due to haze. But if we are applying haze removal algorithms for non-hazy images then the image may get blurred. So haze detection algorithms are necessary before the application of haze removal algorithms. Herein, an algorithm for detection of haze using different classifiers has been implemented and the performance of classifiers are measured and tabulated. In this work initially a number of image features are estimated to train different classifiers such as support vector machine, logistic regression naïve Bayes Classifiers and Decision Tree. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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