Journal ArticleDOI
Retinal vessel enhancement based on multi-scale top-hat transformation and histogram fitting stretching
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TLDR
Results on the DRIVE and STARE databases show that the proposed method improves the contrast and enhances the details of the retinal vessels effectively.Abstract:
Retinal vessels play an important role in the diagnostic procedure of retinopathy. A new retinal vessel enhancement method is proposed in this paper. Firstly, the optimal bright and dim image features of an original retinal image are extracted by a multi-scale top-hat transformation. Then, the retinal image is enhanced preliminarily by adding the optimal bright image features and removing the optimal dim image features. Finally, the preliminarily enhanced image is further processed by linear stretching with histogram Gaussian curve fitting. The experiments results on the DRIVE and STARE databases show that the proposed method improves the contrast and enhances the details of the retinal vessels effectively.read more
Citations
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Color Retinal Image Enhancement Based on Luminosity and Contrast Adjustment
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Retinal Fundus Image Enhancement Using the Normalized Convolution and Noise Removing
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Modeling and Enhancing Low-Quality Retinal Fundus Images
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Entropy and Contrast Enhancement of Infrared Thermal Images Using the Multiscale Top-Hat Transform
Julio César Mello Román,José Luis Vázquez Noguera,Horacio Legal-Ayala,Diego P. Pinto-Roa,Santiago Gómez-Guerrero,Miguel García Torres +5 more
TL;DR: Evaluation of the experimental results shows that the proposed method improves the details of the image by increasing entropy, also preserving natural appearance and enhancing the contrast of infrared thermal images.
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Optimum wavelet based masking for the contrast enhancement of medical images using enhanced cuckoo search algorithm
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TL;DR: An Optimum Wavelet Based Masking (OWBM) using Enhanced Cuckoo Search Algorithm (ECSA) for the contrast improvement of medical images is proposed and shows improved results as compared with other reported literature.
References
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Journal ArticleDOI
Ridge-based vessel segmentation in color images of the retina
TL;DR: A method is presented for automated segmentation of vessels in two-dimensional color images of the retina based on extraction of image ridges, which coincide approximately with vessel centerlines, which is compared with two recently published rule-based methods.
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Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response
TL;DR: An automated method to locate and outline blood vessels in images of the ocular fundus that uses local and global vessel features cooperatively to segment the vessel network is described.
Journal ArticleDOI
Realization of the Contrast Limited Adaptive Histogram Equalization (CLAHE) for Real-Time Image Enhancement
TL;DR: A system level realization of CLAHE is proposed, which is suitable for VLSI or FPGA implementation and the goal for this realization is to minimize the latency without sacrificing precision.
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A New Supervised Method for Blood Vessel Segmentation in Retinal Images by Using Gray-Level and Moment Invariants-Based Features
TL;DR: A neural network scheme for pixel classification and computes a 7-D vector composed of gray-level and moment invariants-based features for pixel representation that is suitable for retinal image computer analyses such as automated screening for early diabetic retinopathy detection.
Journal ArticleDOI
An Ensemble Classification-Based Approach Applied to Retinal Blood Vessel Segmentation
Muhammad Moazam Fraz,Paolo Remagnino,Andreas Hoppe,Bunyarit Uyyanonvara,Alicja R. Rudnicka,Christopher G. Owen,Sarah Barman +6 more
TL;DR: This method uses an ensemble system of bagged and boosted decision trees and utilizes a feature vector based on the orientation analysis of gradient vector field, morphological transformation, line strength measures, and Gabor filter responses to segmentation of blood vessels in retinal photographs.