Enhancement of low light image based on Gaussian Mixture Modeling
| Autor: | Kamini Kanta Mohanty, Mahesh Kumar Gellaboina |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Brightness
Dynamic range business.industry Gaussian ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Transfer function Image (mathematics) symbols.namesake Computer Science::Computer Vision and Pattern Recognition Histogram Lookup table symbols Computer vision Artificial intelligence business Gaussian process Mathematics |
| Zdroj: | EUVIP |
| DOI: | 10.1109/euvip.2010.5699120 |
| Popis: | This paper presents a method for global image enhancement based on Gaussian Mixture Modeling (GMM)1. The philosophy behind GMM based enhancement is to enable a more efficient packing of individual Gaussian components in the histogram of the enhanced image, which gets rid off unutilized brightness zones in the image. This enhancement technique falls under the category of global image enhancement and is applied to the image using a transfer function. This method has been tested on diverse set of images under low light conditions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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