A Systematic Literature Review on SOTA Machine learning-supported Computer Vision Approaches to Image Enhancement

Marco Klaiber, Jonas Klopfer


Image enhancement as a problem-oriented process of optimizing visual appearances to provide easier-toprocess input to automated image processing techniques is an area that will consistently be a companion to computer vision despite advances in image acquisition and its relevance continues to grow. For our systematic literature review, we consider the major peer-reviewed journals and conference papers on the state of the art in machine learning-based computer vision approaches for image enhancement. We describe the image enhancement methods relevant to our work and introduce the machine learning models used. We then provide a comprehensive overview of the different application areas and formulate research gaps for future scientific work on machine learning based computer vision approaches for image enhancement based on our results


Image enhancement, Machine learning, Computer vision, ML, CV

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DOI: https://doi.org/10.21609/jiki.v15i1.1017


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