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AuthorSaleem A.
AuthorBeghdadi A.
AuthorBoashash B.
Available date2022-05-31T19:01:39Z
Publication Date2012
Publication NameEurasip Journal on Image and Video Processing
ResourceScopus
Identifierhttp://dx.doi.org/10.1186/1687-5281-2012-10
URIhttp://hdl.handle.net/10576/31937
AbstractThe goal of contrast enhancement is to improve visibility of image details without introducing unrealistic visual appearances and/or unwanted artefacts. While global contrast-enhancement techniques enhance the overal contrast, their dependences on the global content of the image limit their ability to enhance local details. They also result in significant change in image brightness and introduce saturation artefacts. Local enhancement methods, on the other hand, improve image details but can produce block discontinuities, noise amplification and unnatural image modifications. To remedy these shortcomings, this article presents a fusion-based contrast-enhancement technique which integrates information to overcome the limitations of different contrast-enhancement algorithms. The proposed method balances the requirement of local and global contrast enhancements and a faithful representation of the original image appearance, an objective that is difficult to achieve using traditional enhancement methods. Fusion is performed in a multi-resolution fashion using Laplacian pyramid decomposition to account for the multi-channel properties of the human visual system. For this purpose, metrics are defined for contrast, image brightness and saturation. The performance of the proposed method is evaluated using visual assessment and quantitative measures for contrast, luminance and saturation. The results show the efficiency of the method in enhancing details without affecting the colour balance or introducing saturation artefacts and illustrate the usefulness of fusion techniques for image enhancement applications.
Languageen
SubjectContrast Enhancement
Fusion techniques
Gaussian pyramids
Human Visual System
Image blending
Image brightness
Image decomposition
Image modification
Laplacian pyramid decomposition
Multi-channel
Multi-resolutions
Noise amplification
Original images
Quantitative measures
Visual appearance
Visual assessments
Luminance
Image fusion
TitleImage fusion-based contrast enhancement
TypeArticle
Issue Number1
Volume Number2012


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