Images Enhancement with Brightness Preserving using MRHRBFN
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10.5120/4976-7231 |
Narendra Singh Bagri, Sanjeev Sharma and Santosh Sahu. Article: Images Enhancement with Brightness Preserving using MRHRBFN. International Journal of Computer Applications 40(7):22-26, February 2012. Full text available. BibTeX
@article{key:article,
author = {Narendra Singh Bagri and Sanjeev Sharma and Santosh Sahu},
title = {Article: Images Enhancement with Brightness Preserving using MRHRBFN},
journal = {International Journal of Computer Applications},
year = {2012},
volume = {40},
number = {7},
pages = {22-26},
month = {February},
note = {Full text available}
}
Abstract
In the image processing, Images Enhancement with Brightness Preserving has many methods likes HE(Histogram Equalization), MHE(Multi-Histogram Equalization), IDBPHE(Image Dependent Brightness Preserving Histogram Equalization). We are proposed a novel methodology for the enhancement of images MRHRBFN (Multi-Resolution Histogram with Radial Bias Function Network). Enhancement process using pixel independent multi histogram method and Radial Bias Function Network. In process of our methodology image are decompose in terms of subbands. The sub band division perform by Curvelet transform. The Curvelet Transform divides two types of bands as higher band and lower band. The separation band of frequency generates a multiple matrix for input of radial bias Function Network. We have radial Bias function network work in low band data, because higher band data preserve brightness of image. The lower frequency matrix calculates bias and proceed weight factor when The lower value of frequency matrix regret reaches the mean value of given image. Finally we get better enhance image in comparison of multi histogram equalization.
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