Paper Title:
Image Enhancement Based on Fractional Differential and Image Entropy
  Abstract

In this paper, a new image enhancement method is proposed based on fractional differential, which can select the differential order automatically by the difference of mutual information (DMI). DMI describes the increase of mutual information in original and enhancement image. Being a measure of ascertaining the ehancement effect, it is considered getting the information balance in the images processed by different differential order. According to it, a criterion of selection differential order is put forward. Image convolutions are implemented with fractional operator in different scales, and then DMI of adjacent scales are calculated. The differential order can be selected in which the DMI is the mininum. The experimental results indicate that the proposed method is effective, and has better result compared with other methods.

  Info
Periodical
Edited by
Dehuai Zeng
Pages
232-235
DOI
10.4028/www.scientific.net/AMR.159.232
Citation
Y. W. Liu, J. W. Li, "Image Enhancement Based on Fractional Differential and Image Entropy", Advanced Materials Research, Vol. 159, pp. 232-235, 2011
Online since
December 2010
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Shang Bo Zhou, Yong Li
Abstract:For the existing methods of image registration based on feature, a new method of image registration based on plural differential is proposed...
2172
Authors: Wei Jiang, Zheng Xia Wang
Chapter 5: Information Processing and Computational Science
Abstract:Current total variation method excels at denoising and keeping the characteristics of image edges. However, its ability to retain texture...
797
Authors: Shuang Shuang He, Yuan Yuan Jiang, Jin Yan Zheng
Chapter 4: Practice of Data Processing for Intelligent Systems
Abstract:To improve image quality and a higher level of follow-up image process needed, it's of great importance to do the image denoising process...
586