Sonali
(Department of CSE & IT, Jaypee University of Information Technology Waknaghat, Solan, Himachal Pradesh, India)
,
Sahu, Sima
(Dr. A. P. J. Abdul Kalam Technical University, Lucknow, Uttar Pradesh, India)
,
Singh, Amit Kumar
(Department of CSE & IT, Jaypee University of Information Technology Waknaghat, Solan, Himachal Pradesh, India)
,
Ghrera, S.P.
(Department of CSE & IT, Jaypee University of Information Technology Waknaghat, Solan, Himachal Pradesh, India)
,
Elhoseny, Mohamed
(Department of Information Systems, Faculty of Computer and Information, Mansoura University, Egypt)
Abstract Now-a-days medical fundus images are widely used in clinical diagnosis for the detection of retinal disorders. Fundus images are generally degraded by noise and suffer from low contrast issues. These issues make it difficult for ophthalmologist to detect and interpret diseases in fundus im...
Abstract Now-a-days medical fundus images are widely used in clinical diagnosis for the detection of retinal disorders. Fundus images are generally degraded by noise and suffer from low contrast issues. These issues make it difficult for ophthalmologist to detect and interpret diseases in fundus images. This paper presents a noise removal and contrast enhancement algorithm for fundus image. Integration of filters and contrast limited adaptive histogram equalization (CLAHE) technique is applied for solving the issues of de-noising and enhancement of color fundus image. The efficacy of the proposed method is evaluated through different performance parameters like Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), Correlation coefficient (CoC) and Edge preservation index (EPI). The proposed method achieved 7.85% improvement in PSNR, 1.19% improvement in SSIM, 0.12% improvement in CoC and 1.28% improvement in EPI when compared to the state of the art method. Highlights Proposed a noise removal and contrast enhancement algorithm for color fundus image. Our method uses integration of filters and contrast limited adaptive histogram equalization (CLAHE) technique. Efficacy of the method is evaluated through different performance parameters. The performance of our method is better than other state-of-the-art technique.
Abstract Now-a-days medical fundus images are widely used in clinical diagnosis for the detection of retinal disorders. Fundus images are generally degraded by noise and suffer from low contrast issues. These issues make it difficult for ophthalmologist to detect and interpret diseases in fundus images. This paper presents a noise removal and contrast enhancement algorithm for fundus image. Integration of filters and contrast limited adaptive histogram equalization (CLAHE) technique is applied for solving the issues of de-noising and enhancement of color fundus image. The efficacy of the proposed method is evaluated through different performance parameters like Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM), Correlation coefficient (CoC) and Edge preservation index (EPI). The proposed method achieved 7.85% improvement in PSNR, 1.19% improvement in SSIM, 0.12% improvement in CoC and 1.28% improvement in EPI when compared to the state of the art method. Highlights Proposed a noise removal and contrast enhancement algorithm for color fundus image. Our method uses integration of filters and contrast limited adaptive histogram equalization (CLAHE) technique. Efficacy of the method is evaluated through different performance parameters. The performance of our method is better than other state-of-the-art technique.
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