Image optimization

Image optimization is the process of altering an image to improve its quality and visual appearance.^[1] It can be used to highlight significant details within an image, to enhance the relative losslessness of compressed images, or in systems that provide digital image correlation.^[2] One such technique is image segmentation.^[3] There are a variety of mathematical algorithms that can provide a variety of enhancements. Software that may incorporate one or more of these algorithms are called "digital image optimizers" (DIO).^[4]

As pointed out by Professor Hemanth, "Optimization has become part and parcel of all computational vision applications, and since the amount of data used in these applications is vast, the need for optimization techniques has increased exponentially."^[5] He went on to point out that it is important to document the nature of the changes being made in the images to ensure the accuracy of the results.^[5]

Notes and references

^ Jebril, Noor A.; Al-Haija, Qasem Abu (2018). "Cuckoo Optimization Algorithm (COA) for Image Processing". In Hemanth, Jude; Balas, Valentina Emilia (eds.). Nature Inspired Optimization Techniques for Image Processing Applications. Cham, Switzerland: Springer Verlag. p. 189. ISBN 978-3-319-96002-9.
^ Schreier, Hubert W.; Orteu, Jean-José; Sutton, Michael A. (2009). Image Correlation for Shape, Motion and Deformation Measurements. Boston, Massachusetts: Springer Verlag. ISBN 978-0-387-78746-6..
^ Oliva, Diego; Elaziz, Mohamed Abd; Hinojosa, Salvador. Metaheuristic Algorithms for Image Segmentation: Theory and applications. Cham, Switzerland: Springer Verlag. ISBN 978-3-03-012931-6.
^ Kollmann, Christian (2011). List of technical and medical ultrasonic abbreviations (PDF) (2nd ed.). Vienna, Austria: Center for Medical Physics & Biomedical Engineering, University of Vienna. p. 4.
^ ^a ^b Hemanth, Jude; Balas, Valentina Emilia, eds. (2018). "Preface". Nature Inspired Optimization Techniques for Image Processing Applications. Cham, Switzerland: Springer Verlag. ISBN 978-3-319-96002-9.

[1] Jebril, Noor A.; Al-Haija, Qasem Abu (2018). "Cuckoo Optimization Algorithm (COA) for Image Processing". In Hemanth, Jude; Balas, Valentina Emilia (eds.). Nature Inspired Optimization Techniques for Image Processing Applications. Cham, Switzerland: Springer Verlag. p. 189. ISBN 978-3-319-96002-9.

[2] Schreier, Hubert W.; Orteu, Jean-José; Sutton, Michael A. (2009). Image Correlation for Shape, Motion and Deformation Measurements. Boston, Massachusetts: Springer Verlag. ISBN 978-0-387-78746-6..

[3] Oliva, Diego; Elaziz, Mohamed Abd; Hinojosa, Salvador. Metaheuristic Algorithms for Image Segmentation: Theory and applications. Cham, Switzerland: Springer Verlag. ISBN 978-3-03-012931-6.

[4] Kollmann, Christian (2011). List of technical and medical ultrasonic abbreviations (PDF) (2nd ed.). Vienna, Austria: Center for Medical Physics & Biomedical Engineering, University of Vienna. p. 4.

[Hemanth1-5] Hemanth, Jude; Balas, Valentina Emilia, eds. (2018). "Preface". Nature Inspired Optimization Techniques for Image Processing Applications. Cham, Switzerland: Springer Verlag. ISBN 978-3-319-96002-9.

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