Dermoscopy Images Enhancement via Multi-Scale Morphological Operations
Source abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Image Enhancement Techniques · Optical Coherence Tomography Applications · Color Science and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Computer Engineer Department, Universidad Americana, Asunción 1206, Paraguay
Facultad Politécnica, Universidad Nacional de Asunción, San Lorenzo 111421, Paraguay
Data Science and Big Data Lab, Universidad Pablo de Olavide, 41013 Seville, Spain
Department of Computer and Electronics, Universidade Federal do Espírito Santo, São Mateus 29932-540, ES, Brazil
Sígnal Theory and communications Department, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain
Hospital de Clínicas, Facultad de Ciencias Médicas, Universidad Nacional de Asunción, San Lorenzo 111421, Paraguay
Facultad de Ciencias Exactas y Tecnológicas, Universidad Nacional de Conepción, Concepción 010123, Paraguay
Funding
Consejo Nacional de Ciencia y Tecnología
References (40)
Show source-provided references
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