Lung Lesion Enhancement Using Adaptive Median Filter with Curvelet Transform

  • Authors

    • Lim J Seelan
    • Dr Padma Suresh
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.18130
  • Histogram equalization, Adaptive median filter, Curvelet transform

  • Lung cancer is one of the major troubles of cancer in the worldwide among people. Initial identification of lung cancer will highly decreases the mortality rate to save the patient lifetime. To detect the lung nodule, the lung image must be enhanced, thus a novel method is proposed for improving image quality, which is the combination of adaptive median filter and Curvelet transform. During image acquisition, the noise content also include in the image. In order to eliminate the noise, the following steps are carried out; first the input image is changed into grayscale image for reduce the processing delay. Then adaptive median filter is performed along the image to remove the noise and histogram equalization is used to improve the image contrast. Finally, the curvelet transform is applied for sharpening the image edge. Performances are analyzed based on the PSNR, MSE, SNR and SSIM values.

     

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  • How to Cite

    J Seelan, L., & Padma Suresh, D. (2018). Lung Lesion Enhancement Using Adaptive Median Filter with Curvelet Transform. International Journal of Engineering & Technology, 7(2.33), 1323-1328. https://doi.org/10.14419/ijet.v7i2.33.18130