Single image highlight removal for real-time image processing pipelines

This paper presents a fully automatic method for the separation of diffuse and specular reflection components from a single image. Overall, the mechanisms in which the available methods operate on are computationally costly and do not translate well to modern hardware-implemented image processing pi...

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Detalles Bibliográficos
Autores: Ramos, Vítor S., Silveira Júnior, Luiz Gonzaga de Q., Silveira, Luiz Felipe de Q.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:Brasil
Institución:Universidade Federal do Rio Grande do Norte (UFRN)
Repositorio:Repositório Institucional da UFRN
Idioma:inglés
OAI Identifier:oai:repositorio.ufrn.br:123456789/31477
Acceso en línea:https://repositorio.ufrn.br/handle/123456789/31477
Access Level:acceso abierto
Palabra clave:Blind source separation
Feature extraction
Image color analysis
Image enhancement
Image processing
Image texture analysis
Descripción
Sumario:This paper presents a fully automatic method for the separation of diffuse and specular reflection components from a single image. Overall, the mechanisms in which the available methods operate on are computationally costly and do not translate well to modern hardware-implemented image processing pipelines, such as the ones present in consumer electronics. Consequently, the objective of this article is to introduce a simple yet effective method for specular highlight removal. It is based on the dichromatic reflection model and operates through histogram matching in the YCbCr color space. The proposed method performs in real-time. It only uses global image statistics and point-wise intensity transformations. Experimental evaluation shows that the proposed approach has competitive results in comparison to state-of-the-art methods. Limitations of the proposed approach are seldom and are common to most methods available. The proposed method, however, achieves better quality results with much less computational cost, thus enabling feasibility in systems with limited processing power