ENG  Vol.3 No.10 , October 2011
Industrial X-Ray Image Enhancement Algorithm based on AH and MSR
Abstract: An X-ray image enhancement algorithm based on AH(adaptive histogram) and MSR( Multi-scale Retinex )algorithm is proposed in this paper for the industrial X-ray image, which contrast is low, and the detail features is poor. Firstly, the contrast limited adaptive histogram equalization and neighborhood algorithm is used for the image. Then the mapping is built between the image and the detail scales by the enhance function ratio rules, which is adjusted by the local contracting information. Finally, according the enhance function radios, the reconstructed image is rebuild. Compared with other image enhancement algorithms, experimental results show that our algorithm can improve the global image effectively, moreover it overcomes the visible artifacts of X-ray image. Therefore, the x-ray image becomes clearer, and a better perceptual image is acquired for the image feature recognizing and matching.
Cite this paper: nullW. Jie, W. Dada, Y. Wang, J. Li, W. Lei and H. Liang, "Industrial X-Ray Image Enhancement Algorithm based on AH and MSR," Engineering, Vol. 3 No. 10, 2011, pp. 1040-1044. doi: 10.4236/eng.2011.310129.

[1]   S. Yang, C. Wang and L. G. Deng, “A New Approach of Image Enhancement Based on Multi-Scale Morphological Reconstruction,” 9th International Conference on Hybrid Intelligent Systems, Shenyang, 12-14 August 2009, pp. 113-116. doi:10.1109/HIS.2009.30

[2]   S. G. Mallat, “A Theory for Multiresolution Signal Decomposition: The Wavelet Representation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 2, No. 7, 1989, pp. 674-693. doi:10.1109/34.192463

[3]   S. M. Pizer and E. P. Ambtrrn, “Adaptive Histogram Equalization and Its Variations,” Computer Vision Gra- phics & Image Processing, Vol. 39, No. 3, 1987, pp. 355-368. doi:10.1016/S0734-189X(87)80186-X

[4]   J. S. Tang, X. M. Liu and Q, L. Sun, “A Direct Image Contrast Enhancement Algorithm in the Wavelet Domain for Screening Mammograms,” IEEE Journal of Selected Topics in Signal Processing, Vol. 3, No. 1, 2009, p. 1.

[5]   X.-B. Wang, “Image Enhancement Based on Lifting Wavelet Transform,” 4th International Conference on Computer Science & Education, Xiamen, 25-28 July 2009, pp. 739-741.

[6]   J. S. Tang, Q. L. Sun and K. Agyepong, “An Image Enhancement Algorithm Based on a Contrast Measure in the Wavelet Domain for Screening Mammograms,” IEEE International Conference on Image Processing, San Antonio, 16-19 September 2007, pp. 74-80. doi:10.1109/ICIP.2007.4379757

[7]   J. M. Morel, A. B. Petro and C. A. Sbert, “PDE Formalization of Retinex Theory,” IEEE Transactions on Image Processing, Vol. 19, No. 11, 2010, pp. 2825-2837. doi:10.1109/TIP.2010.2049239