التفاصيل البيبلوغرافية
| العنوان: |
Image Dehazing and Enhancement Using Principal Component Analysis and Modified Haze Features. |
| المؤلفون: |
Kim, Minseo, Yu, Soohwan, Park, Seonhee, Lee, Sangkeun, Paik, Joonki |
| المصدر: |
Applied Sciences (2076-3417); Aug2018, Vol. 8 Issue 8, p1321, 16p |
| مصطلحات موضوعية: |
IMAGE enhancement (Imaging systems), PRINCIPAL components analysis, SUPERVISED learning |
| مستخلص: |
This paper presents a computationally efficient haze removal and image enhancement methods. The major contribution of the proposed research is two-fold: (i) an accurate atmospheric light estimation using principal component analysis, and (ii) learning-based transmission estimation. To reduce the computational cost, we impose a constraint on the candidate pixels to estimate the haze components in the sub-image. In addition, the proposed method extracts modified haze-relevant features to estimate an accurate transmission using random forest. Experimental results show that the proposed method can provide high-quality results with a significantly reduced computational load compared with existing methods. In addition, we demonstrate that the proposed method can significantly enhance the contrast of low-light images according to the assumption on the visual similarity between the inverted low-light and haze images. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
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