Noise Removal and Contrast Enhancement for X-Ray Images

  • Ren-You Huang Institute of Electrical Control Engineering, National Chiao Tung University, Taiwan
  • Lan-Rong Dung Department of Electrical and Computer Engineering, National Chiao Tung University, Taiwan
  • Cheng-Fa Chu Department of Electrical and Computer Engineering, National Chiao Tung University, Taiwan
  • Yin-Yi Wu National Chung-Shan Institute of Science and Technology
Keywords: Medical Image Processing, Noise Reduction, Contrast Enhancement, X-ray images

Abstract

X-ray image plays a very important role in the medical diagnosis. To help the doctors for diagnosis of the disease, some algorithms for enhancing X-ray images were proposed in the past decades. However, the enhancement of images will also amplify the noise or produce distortion of image, which are unfavorable to the diagnosis. Therefore, appropriate techniques for noise suppression and contrast enhancement are necessary. This paper proposed an algorithm including two-stage filtering and contrast enhancement for X-ray images. By using adaptive median filter and bilateral filter, our method is able to suppress the mixed noise which contains Gaussian noise and impulsive noise, while preserving the important structures (e.g., edges) in the images. Afterwards, the contrast of image is enhanced by using gray-level morphology and contrast limited histogram equalization (CLAHE). In the experiments, we evaluate the performance of noise removal and contrast enhancement separately with quantitative indexes and visual results. For the mixed noise case, our method is able to achieve averaged PSNR 39.89 dB and averaged SSIM 0.9449; for the contrast enhancement, our method is able to enhance more detail structures (e.g., edges, textures) than CLAHE.

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Published
2016-03-03
How to Cite
Huang, R.-Y., Dung, L.-R., Chu, C.-F., & Wu, Y.-Y. (2016). Noise Removal and Contrast Enhancement for X-Ray Images. Journal of Biomedical Engineering and Medical Imaging, 3(1), 56. https://doi.org/10.14738/jbemi.31.1893