Literature DB >> 31897799

Enhancement of blurry retinal image based on non-uniform contrast stretching and intensity transfer.

Lvchen Cao1, Huiqi Li2.   

Abstract

Proper contrast and sufficient illuminance are important in clearly identifying the retinal structures, while the required quality cannot always be guaranteed due to major reasons like acquisition process and diseases. To ensure the effectiveness of enhancement, two solutions are developed for blurry retinal images with sufficient illuminance and insufficient illuminance, respectively. The proposed contrast stretching and intensity transfer are main steps in both of the two solutions. The contrast stretching is based on base-intensity removal and non-uniform addition. We assume that a base-intensity exists in an image, which mainly supports the basic illuminance but has less contribution to texture information. The base-intensity is estimated by the constrained Gaussian function and then removed. The non-uniform addition using compressed Gamma map is further developed to improve the contrast. Additionally, an effective intensity transfer strategy is introduced, which can provide required illuminance for a single channel after contrast stretching. The color correction can be achieved if the intensity transfer is performed on three channels. Results show that the proposed solutions can effectively improve the contrast and illuminance, and good visual perception for quality degraded retinal images is obtained. Illustration of contrast stretching based on a signal colour channel.

Entities:  

Keywords:  Contrast stretching; Enhancement; Intensity transfer; Retinal image

Year:  2020        PMID: 31897799     DOI: 10.1007/s11517-019-02106-7

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  18 in total

Review 1.  Retinal imaging and image analysis.

Authors:  Michael D Abràmoff; Mona K Garvin; Milan Sonka
Journal:  IEEE Rev Biomed Eng       Date:  2010

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Journal:  Comput Methods Programs Biomed       Date:  2017-03-07       Impact factor: 5.428

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4.  Color-difference evaluation for digital images using a categorical judgment method.

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Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2013-04-01       Impact factor: 2.129

5.  Enhancement and restoration of non-uniform illuminated Fundus Image of Retina obtained through thin layer of cataract.

Authors:  Anirban Mitra; Sudipta Roy; Somais Roy; Sanjit Kumar Setua
Journal:  Comput Methods Programs Biomed       Date:  2018-01-10       Impact factor: 5.428

6.  Naturalness Preserved Image Enhancement Using a priori Multi-Layer Lightness Statistics.

Authors: 
Journal:  IEEE Trans Image Process       Date:  2017-11-09       Impact factor: 10.856

7.  Glaucoma risk index: automated glaucoma detection from color fundus images.

Authors:  Rüdiger Bock; Jörg Meier; László G Nyúl; Joachim Hornegger; Georg Michelson
Journal:  Med Image Anal       Date:  2010-01-04       Impact factor: 8.545

Review 8.  Computer-aided diagnosis of diabetic retinopathy: a review.

Authors:  Muthu Rama Krishnan Mookiah; U Rajendra Acharya; Chua Kuang Chua; Choo Min Lim; E Y K Ng; Augustinus Laude
Journal:  Comput Biol Med       Date:  2013-10-14       Impact factor: 4.589

9.  Exploiting ensemble learning for automatic cataract detection and grading.

Authors:  Ji-Jiang Yang; Jianqiang Li; Ruifang Shen; Yang Zeng; Jian He; Jing Bi; Yong Li; Qinyan Zhang; Lihui Peng; Qing Wang
Journal:  Comput Methods Programs Biomed       Date:  2015-10-24       Impact factor: 5.428

10.  An Approach to Evaluate Blurriness in Retinal Images with Vitreous Opacity for Cataract Diagnosis.

Authors:  Li Xiong; Huiqi Li; Liang Xu
Journal:  J Healthc Eng       Date:  2017-04-26       Impact factor: 2.682

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  1 in total

1.  Image enhancement of color fundus photographs for age-related macular degeneration: the Shanghai Changfeng Study.

Authors:  Jing-Jing Shen; Rui Wang; Li-Long Wang; Chuan-Feng Lyu; Shuo Liu; Guo-Tong Xie; Hai-Luan Zeng; Ling-Yan Chen; Min-Qian Shen; Xin Gao; Huan-Dong Lin; Yuan-Zhi Yuan
Journal:  Int J Ophthalmol       Date:  2022-02-18       Impact factor: 1.779

  1 in total

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