Journal of Multimedia Processing and Technologies

DLINE Journals portal

Home

New Journals

Browse Journals

Journal Prices

For Authors

Print ISSN: 0976-4127
Online ISSN: 0976-4135

About JMPT
	DLINE Portal Home Home Aims & Scope Editorial Board Current Issue Next Issue Previous Issue Sample Issue Upcoming Conferences Self-archiving policy Alert Services Be a Reviewer Publisher Paper Submission Subscription Contact us

How To Order
	Order Online Price Information Request for Complimentary Print Copy

For Authors
	Guidelines for Contributors Online Submission Call for Papers Author Rights

RELATED JOURNALS

Journal of Digital Information Management (JDIM)

International Journal of Computational Linguistics Research (IJCL)

International Journal of Web Application (IJWA)

Journal of Multimedia Processing and Technologies

Adaptive Noise Image Enhancement Method Based on Genetic Algorithm in Nonsubsampled Contourlet Domain

Yang Li, Shengyong Chen, Wei Huang
TianJin University of Technology TianJin, 300384 China

Abstract: In order to suppress the noise adaptively while enhancing the image details, an adaptive image enhancement method based on genetic algorithm in Nonsubsampled Contourlet (NSCT) domain is proposed. The optimal parameters of the image enhancement function are obtained adaptively through genetic algorithm (GA). The NSCT high frequency sub-bands coefficients are processed by the image enhancement function, the coefficients which are less than the low threshold are set to 0 and the coefficients between the low threshold and the high threshold are enhanced. Experimental results demonstrate that the proposed method can adaptively enhance the image details and suppress noise at the same time, the detail variance is significantly improved, and a better visual effect is obtained. The results processed by the proposed method are better than that by classical enhancement methods.

Keywords: Image Enhancement, NSCT, Noise, Adaptive, GA Adaptive Noise Image Enhancement Method Based on Genetic Algorithm in Nonsubsampled Contourlet Domain

DOI:https://doi.org/10.6025/jmpt/2019/10/4/138-151

Full_Text PDF 2.8 MB Download: 382 times

References:

[1] Gonzalez, R C., Woods, R E., Masters, B R. (2009). “Digital image processing, third edition,” Journal of Biomedical Optics, Vol.14, No.6, pp. 029901, 2009.
[2] Ling, Z., Liang, Y., Wang, Y., et al. (2015). “Adaptive extended piecewise histogram equalization for dark image enhancement,” IET Image Processing, Vol. 9, No. 11, pp. 1012-1019, 2015.
[3] Liu, N., Zhao, D. (2014). “Detail enhancement for high-dynamic-range infrared images based on guided image filter,” Infrared Physics & Technology, Vol. 67, pp. 138–147, 2014.
[4] Kanwal, N., Girdhar, A., Gupta, S. (2011). “Region Based Adaptive Contrast Enhancement of Medical X-Ray Images,”Bioinformatics and Biomedical Engineering, (iCBBE) 2011 5th International Conference on. IEEE, pp. 1-5, 2011.
[5] Singh, K., Kapoor, R. (2014). “Image enhancement using Exposure based Sub Image Histogram Equalization,” Pattern Recognition Letters, Vol1. 36, No. 1, pp. 10-14, 2014.
[6] Liu, N., Zhang, Y., Xie, J. (2015). “A Novel High Dynamic Range Image Enhancement Algorithm Based on Guided Image Filter,” Optik - International Journal for Light and Electron Optics, Vol. 126, No. 23, pp. 4581-4585, 2015.
[7] Di, H., Gao, D. (2014). “Gray-level transformation and Canny edge detection for 3D seismic discontinuity enhancement,” Computers & Geosciences, Vol. 72, pp. 192-200, 2014.
[8] Jin, L., Xiong, C., Liu, H. (2012). “Improved bilateral filter for suppressing mixed noise in color images,” Digital Signal Processing, Vol. 22, No. 6, pp.903-912, 2012.
[9] Cho, D., Bui, T D. (2014). “Fast image enhancement in compressed wavelet domain,” Signal Processing, pp. 295–307, 2014.
[10] Shi, J., Shan, Z. (2012). “Image resolution enhancement using statistical estimation in wavelet domain,” Biomedical Signal Processing & Control, Vol. 17, No.6, pp. 571–578, 2012.
[11] Metwalli, M R., Nasr, A H., Faragallah, O S. (2014). “Efficient pan-sharpening of satellite images with the contourlet transform,” International Journal of Remote Sensing, Vol. 35, No. 5, pp. 1979-2002, 2014.
[12] Xia, C., Jiao, L., Liu, F. (2015). “SAR Image Despeckling Using Scale Mixtures of Gaussians in the Nonsubsampled Contourlet Domain,” Chinese Journal of Electronics, Vol. 24, No. 1,pp: 205-211, 2015.
[13] Changdong, Wu., Zhigang, Liu., Hua Jiang. (2014). “Catenary image enhancement using wavelet-based contourlet transform with cycle translation,” Optik, Vol. 125, No. 15, pp. 3922-3925, 2014.
[14] Shen, Y., Ren, E., Dang, J W. (2013). “A Nonsubsampled Contourlet Transform Based Medical Image Fusion Method,” Information Technology Journal, Vol. 12, No. 4, 2013.
[15] Wu, C., Liu, Z., Jiang, H. (2014). “Catenary image enhancement using wavelet-based contourlet transform with cycle translation,” Optik - International Journal for Light and Electron Optics, Vol. 125, No. 15, pp. 3922-3925, 2014.
[16] Bamberger, R H., Smith, M J T. (1992). A filter bank for the directional decomposition of images: theory and design[J]. IEEE Transactions on Signal Processing, 1992, 40 (4), 882-893.
[17] Starck, J L., Murtagh, F., Candès, E J., et al. (2003). Gray and color image contrast enhancement by the curvelet transform, IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society, 2003, 12(6) 706-17. [18] Sezan, M I.,Tekalp, A M., Schaetzing, R. Automatic anatomically selective image enhancement in digital chest radiography, IEEE Transactions on Medical Imaging, 8 (2) 154-162, 1989.
[19] S karabot A., Ram poni G., T offoli D. (200). Image sequence processing for videowall visualization, In: Proceedings of SPIE, Vol. 3961, p. 138—147, 2000.
[20] Zhang, X., Wu, H., Ma, Y. (2015). A new auto-focus measure based on medium frequency discrete cosine transform filtering and discrete cosine transform, Applied & Computational Harmonic Analysis, 2015, 40 (2) 430-437.
[21] Wang, Z., Bovik, A C. (2009). Mean squared error: Love it or leave it? A new look at Signal Fidelity Measures, IEEE Signal Processing Magazine, 2009, 26 (1) 98-117.
[22] Elsayed, S M., Sarker, R A., Essam, D L. (2014). A new genetic algorithm for solving optimization problems," Engineering Applications of Artificial Intelligence, 27 (1) 57-69, 2014.

DLINE Journals portal