International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 12, No. 2, 8 Apr. 2020
Cover page and Table of Contents: PDF (size: 1199KB)
Improving Retinal Image Quality Using the Contrast Stretching, Histogram Equalization, and CLAHE Methods with Median Filters
Full Text (PDF, 1199KB), PP.30-41
Views: 0 Downloads: 0
Author(s)
Erwin
1,*
Dwi Ratna Ningsih
1
Index Terms
Median filter, STARE, contrast stretching, CLAHE, HE, PSNR, SSIM.
Abstract
This paper performs three different contrast testing methods, namely contrast stretching, histogram equalization, and CLAHE using a median filter. Poor quality images will be corrected and performed with a median filter removal filter. STARE dataset images that use images with different contrast values for each image. For this reason, evaluating the results of the three parameters tested are; MSE, PSNR, and SSIM. With the gray level scale image and contrast stretching which stretches the pixel value by stretching the stretchlim technique with the MSE result are 9.15, PSNR is 42.14 dB, and SSIM is 0.88. And the HE method and median filter with the results of the average value of MSE is 18.67, PSNR is 41.33 dB, and SSIM is 0.77. Whereas for CLAHE and median filters the average yield of MSE is 28.42, PSNR is 35.30 dB, and SSIM is 0.86. From the test results, it can be seen that the proposed method has MSE and PSNR values as well as SSIM values.
Cite This Paper
Erwin, Dwi Ratna Ningsih, " Improving Retinal Image Quality Using the Contrast Stretching, Histogram Equalization, and CLAHE Methods with Median Filters", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.12, No.2, pp. 30-41, 2020. DOI: 10.5815/ijigsp.2020.02.04
Reference
[1]M. Rajaram, “A novel approach for contrast enhancement based on histogram equalization followed by median filter,” ARPN J. Eng. Appl. Sci., no. September 2009, 2014.
[2]V. M. Saffarzadeh, A. Osareh, and B. Shadgar, “Vessel Segmentation in Retinal Images Using Multi ‑ scale Line Operator and K ‑ Means Clustering,” Dep. Comput. Eng. Shahid Chamran Univ. Ahvaz, Khuzestan, Iran,jmss., vol. 4, no. 2, 2017.
[3]H. Aguirre-ramos, J. G. Avina-cervantes, I. Cruz-aceves, J. Ruiz-pinales, and S. Ledesma, “Blood vessel segmentation in retinal fundus images using Gabor filters , fractional derivatives , and Expectation Maximization,” Appl. Math. Comput., vol. 339, pp. 568–587, 2018.
[4]F. Farokhian and H. Demirel, “Blood Vessels Detection and Segmentation in Retina using Gabor Filters,” Electr. Electron. Eng. Dep. IEEE, pp. 104–108, 2013.
[5]K. Firdausy, T. Sutikno, and E. Prasetyo, “Image Enhancement Using Contrast Stretching On Rgb And Ihs Digital Image,” Cent. Electr. Eng. Res. Solut. (CEERS), ISSN, vol. 5, No.1, no. 1, pp. 45–50, 2007.
[6]Y. Zhu and C. Huang, “An Improved Median Filtering Algorithm for Image Noise,” Phys. Procedia, vol. 25, pp. 609–616, 2012.
[7]F. A. Jassim and F. H. Altaani, “Hybridization of Otsu Method and Median Filter for Color Image Segmentation,” Int. J. Soft Comput. Eng. ISSN 2231-2307, vol. Volume-3, no. 2, pp. 69–74, 2013.
[8]P. Garhwal and P. Garhwal, “A Hybrid Approach to Image Enhancement using Contrast Stretching on Image Sharpening and the analysis of various cases arising using Histogram,” IEEE Int. Conf. Recent Adv. Innov. Eng., no. 3, 2014.
[9]B. Xu, Y. Zhuang, H. Tang, and L. Zhang, “Object-Based Multilevel Contrast Stretching Method for Image Enhancement,” IEEE Trans. Consum. Electron., vol. 56, no. 3, pp. 1746–1754, 2010.
[10]R. K. B, H. Kabir, and S. Salekin, “Contrast Enhancement by Top-Hat and Bottom-Hat Transform with Optimal Structuring Element : Application to Retinal,” Dep. Comput. Sci. Eng., pp. 533–540, 2017.
[11]M. Liao, Y. Zhao, X. Wang, and P. Dai, “Retinal vessel enhancement based on multi-scale top-hat transformation and histogram fitting stretching,” Opt. Laser Technol., vol. 58, pp. 56–62, 2014.
[12]P. P. Acharjya and S. Mukherjee, “Digital Image Segmentation Using Median Filtering and Morphological Approach,” Int. J. Adv. Res. Comput. Sci. Softw. Eng., vol. 4, no. 1, pp. 552–557, 2014.
[13]K. B. Khan, A. A. Khaliq, A. Jalil, and M. Shahid, “A robust technique based on VLM and Frangi filter for retinal vessel extraction and denoising,” PLoS One, vol. 13, no. 2, pp. 1–22, 2018.
[14]A. M. Reza, “Realization of the contrast limited adaptive histogram equalization (CLAHE) for real-time image enhancement,” J. VLSI Signal Process. Syst. Signal Image. Video Technol., vol. 38, no. 1, pp. 35–44, 2004.
[15]H. A. Rahim, A. S. Ibrahim, W. M. D. W. Zaki, and A. Hussain, “Methods to Enhance Digital Fundus Image for Diabetic Retinopathy Detection,” IEEE Int. Colloq. Signal Process. its Appl., no. Md, pp. 7–9, 2014.
[16]S. Anitha and V. Radha, “Contrast Stretching and Non Linear Median Filters for Fabric Inspection,” Int. J. Comput. Sci. Inf. Technol., vol. 2, no. 2, pp. 836–839, 2011.
[17]S. S. Al-amri, N. V Kalyankar, and S. D. Khamitkar, “Linear and Non-linear Contrast Enhancement Image,” IJCSNS Int. J. Comput. Sci. Netw. Secur. VOL.10, vol. 10, no. 2, pp. 139–143, 2010.
[18]G. B. Iwasokun and O. C. Akinyokun, “Enhancement Methods : A Review,” Sci. Int., vol. 4, pp. 2251–2277, 2016.
[19]J. Dash, “Retinal Blood Vessel Segmentation Using Otsu Thresholding With Principal Component Analysis,” 2018 2nd Int. Conf. Inven. Syst. Control, no. Icisc, pp. 933–937, 2018.
[20]S. Shrestha, “I MAGE D ENOISING U SING N EW A DAPTIVE,” Signal Image Process. An Int. J., vol. 5, no. 4, pp. 1–13, 2014.
[21]B. Gupta and M. Tiwari, “Color retinal image enhancement using luminosity and quantile based contrast enhancement,” PDPM Indian Inst. Inf. Technol., 2018.
[22]S. Sahu, A. Kumar, S. P. Ghrera, and M. Elhoseny, “An approach for de-noising and contrast enhancement of retinal fundus image using CLAHE,” Opt. Laser Technol., 2018.
[23]Erwin, R. Zulfahmi, G. Utami, A. Harison, D. Noviyanti, and P. Agung, “Improved Image Quality Retinal Fundus with Contrast Limited Adaptive Histogram Equalization and Filter Variation,” 2019 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS), vol. 2019, Jakarta, Indonesia, pp. 156–161, 2019.