Abstract
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
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CITATION STYLE
Klaiber, M., & Klopfer, J. (2022). A Systematic Literature Review on SOTA Machine learning-supported Computer Vision Approaches to Image Enhancement. Jurnal Ilmu Komputer Dan Informasi, 15(1), 21–31. https://doi.org/10.21609/jiki.v15i1.1017
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