Dermoscopy Images Enhancement via Multi-Scale Morphological Operations

Author:

Mello-Román Julio CésarORCID,Vázquez Noguera José LuisORCID,Legal-Ayala HoracioORCID,García-Torres MiguelORCID,Facon JacquesORCID,Pinto-Roa Diego P.ORCID,Grillo Sebastian A.ORCID,Salgueiro Romero LuisORCID,Salgueiro Toledo Lizza A.,Bareiro Paniagua Laura RaquelORCID,Leguizamon Correa Deysi NataliaORCID,Mello-Román Jorge DanielORCID

Abstract

Skin dermoscopy images frequently lack contrast caused by varying light conditions. Indeed, often low contrast is seen in dermoscopy images of melanoma, causing the lesion to blend in with the surrounding skin. In addition, the low contrast prevents certain details from being seen in the image. Therefore, it is necessary to design an approach that can enhance the contrast and details of dermoscopic images. In this work, we propose a multi-scale morphological approach to reduce the impacts of lack of contrast and to enhance the quality of the images. By top-hat reconstruction, the local bright and dark features are extracted from the image. The local bright features are added and the dark features are subtracted from the image. In this way, images with higher contrast and detail are obtained. The proposed approach was applied to a database of 236 color images of benign and malignant melanocytic lesions. The results show that the multi-scale morphological approach by reconstruction is a competitive algorithm since it achieved a very satisfactory level of contrast enhancement and detail enhancement in dermoscopy images.

Funder

Consejo Nacional de Ciencia y Tecnología

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference40 articles.

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Advanced enhancement technique for infrared images of wind turbine blades utilizing adaptive difference multi-scale top-hat transformation;Scientific Reports;2024-07-06

2. Mung Bean Variety Classification Using KNN and Image Processing Technique;2024 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS);2024-06-29

3. Enhanced medical images through multi-scale mathematical morphology by reconstruction;2023 18th Iberian Conference on Information Systems and Technologies (CISTI);2023-06-20

4. Image Fusion based Removal of Color Artifacts for the Enhancement of Dermoscopy Images;2022 International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN);2022-03-25

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