التفاصيل البيبلوغرافية
| العنوان: |
Gaussian mixture modeling of histograms for contrast enhancement |
| المؤلفون: |
Lai, Yu-Ren1, Chung, Kuo-Liang k.l.chung@mail.ntust.edu.tw, Lin, Guei-Yin1, Chen, Chyou-Hwa1 |
| المصدر: |
Expert Systems with Applications. Jun2012, Vol. 39 Issue 8, p6720-6728. 9p. |
| مصطلحات موضوعية: |
*GAUSSIAN processes, *CONTRAST effect, *EQUALIZERS (Electronics), *MATHEMATICAL models, *LITERATURE reviews, *COST analysis |
| مستخلص: |
Abstract: The current major theme in contrast enhancement is to partition the input histogram into multiple sub-histograms before final equalization of each sub-histogram is performed. This paper presents a novel contrast enhancement method based on Gaussian mixture modeling of image histograms, which provides a sound theoretical underpinning of the partitioning process. Our method comprises five major steps. First, the number of Gaussian functions to be used in the model is determined using a cost function of input histogram partitioning. Then the parameters of a Gaussian mixture model are estimated to find the best fit to the input histogram under a threshold. A binary search strategy is then applied to find the intersection points between the Gaussian functions. The intersection points thus found are used to partition the input histogram into a new set of sub-histograms, on which the classical histogram equalization (HE) is performed. Finally, a brightness preservation operation is performed to adjust the histogram produced in the previous step into a final one. Based on three representative test images, the experimental results demonstrate the contrast enhancement advantage of the proposed method when compared to twelve state-of-the-art methods in the literature. [Copyright &y& Elsevier] |
| قاعدة البيانات: |
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