Towards Automatic Image Enhancement with Genetic Programming and Machine Learning

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@Article{correia:2022:AS,

• author = "Joao Correia and Nereida Rodriguez-Fernandez and Leonardo Vieira and Juan Romero and Penousal Machado",
• title = "Towards Automatic Image Enhancement with Genetic Programming and Machine Learning",
• journal = "Applied Sciences",
• year = "2022",
• volume = "12",
• number = "4",
• keywords = "genetic algorithms, genetic programming",
• ISSN = "2076-3417",
• URL = "https://www.mdpi.com/2076-3417/12/4/2212",
• DOI = "doi:10.3390/app12042212",
• abstract = "Image Enhancement (IE) is an image processing procedure in which the images original information is improved, highlighting specific features to ease post-processing analyses by a human or machine. State-of-the-art image enhancement pipelines apply solutions to fixed and static constraints to solve specific issues in isolation. In this work, an IE system for image marketing is proposed, more precisely, real estate marketing, where the objective is to enhance the commercial appeal of the images, while maintaining a level of realism and similarity with the original image. This work proposes a generic image enhancement pipeline that combines state-of-the-art image processing filters, Machine Learning methods, and Evolutionary approaches, such as Genetic Programming (GP), to create a dynamic framework for Image Enhancement. The GP-based system is trained to optimise 4 metrics: Neural Image Assessment (NIMA) technical and BRISQUE, which evaluate the technical quality of the images; and NIMA aesthetics and PhotoILike, that evaluate the commercial attractiveness. It is shown that the GP model was able to find the best image quality enhancement (0.97 NIMA Aesthetics), while maintaining a high level of similarity with the original images (Structural Similarity Index Measure (SSIM) of 0.88). The framework has better performance according to the image quality metrics than the off-the-shelf image enhancement tool and the frameworks isolated parts.",
• notes = "also known as \cite{app12042212}",

}

Genetic Programming entries for Joao Nuno Goncalves Costa Cavaleiro Correia Nereida Rodriguez-Fernandez Leonardo Vieira Juan Jesus Romero Cardalda Penousal Machado

Citations