Analysis on Image Enhancement Techniques

Analysis on Image Enhancement Techniques

Автор: Shekhar Karanwal

Журнал: International Journal of Engineering and Manufacturing @ijem

Статья в выпуске: 2 vol.13, 2023 года.

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Image Enhancement is crucial phase of particular application. These enhancement techniques become essential when there is every possibility of image degradation due to uncontrolled variations. These variations are categorized into light, emotion, noise, pose, blur and corruption. The enhanced images provide better images from which feature extraction is performed more effectively. Therefore the two major objectives of the proposed work are aligned in two phases. First phase of this paper discuss about Image Enhancement Techniques (IET) for improving image intensity. Second phase provide detailed elaboration of various Full Reference Based Image Quality Measures (FRBIQM). FRBIQM is further categorized into Pixel Difference Based Image Quality Measures (PDBIQM), Edge Based Image Quality Measures (EBIQM) and Corner Based Image Quality Measures (CBIQM). First image quality measure employs different techniques to evaluate performance between original and distorted image. Second image quality measure deploy edge detection techniques, which are essential for increasing the robustness (in feature extraction) and third image quality measure discuss corner based detection techniques, which are essential for enhancing robustness (in feature extraction). All these techniques are discussed with their examples. This paper provide brief survey of IET and FRBIQM. The significance and the value of the proposed work is to select the best image enhancement techniques and image quality measures among all (described ones) for features extraction. The one which gives the best results will be used for feature extraction.

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Image Enhancement Techniques (IET), Full Reference Based Image Quality Measures (FRBIQM), Pixel Difference Based Image Quality Measures (PDBIQM), Edge Based Image Quality Measures (EBIQM), Corner Based Image Quality Measures (CBIQM)

Короткий адрес: https://sciup.org/15018688

IDR: 15018688   |   DOI: 10.5815/ijem.2023.02.02

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