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Artificial bee Colony optimized image enhancement framework for invisible images

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Abstract

Image enhancement plays an important role in image processing to obtain an image with more perceptual details. In this paper, an artificial bee colony optimization based weighted gamma correction method is proposed to improve the visual quality of the contrast distorted images. The proposed method improves the perceived contrast by expanding and compressing the pixel values. First, Image Expansion and Compression are employed to expose and confine the intensity level present in the image, respectively. Then, an optimally weighted sum approach is used to increase the essential details in the dark regions. Finally, an artificial bee colony optimization algorithm is employed to compute the optimal weighting parameter for brightness preservation. Experimental results demonstrate that the proposed method yields better visual quality images and highlights fine details by enhancing contrast and brightness. The proposed method’s quantitative results are competitive compared to the other well-known methods.

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This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, PSNA College of Engineering and Technology, Dindigul, Tamilnadu, 624622, India

    Magudeeswaran Veluchamy & Bharath Subramani

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  1. Magudeeswaran Veluchamy
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  2. Bharath Subramani
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Correspondence to Bharath Subramani.

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Veluchamy, M., Subramani, B. Artificial bee Colony optimized image enhancement framework for invisible images. Multimed Tools Appl 82, 3627–3646 (2023). https://doi.org/10.1007/s11042-022-13409-7

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  • DOI: https://doi.org/10.1007/s11042-022-13409-7

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