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Adaptive enhancement of underwater images using multi-objective PSO

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Abstract

Underwater images have poor clarity and bad contrast due to low illumination in deep water. Moreover, underwater images are bluish-green in appearance due to inherent wavelength absorption property of water. Therefore, the study of underwater images is a difficult task. Being computationally simple, histogram-based enhancement techniques are obvious choice for improvement of contrast and color of underwater images. However, due to lack of any guidance mechanism, these techniques can overstretch the histogram leading to artifacts in the image. Hence, an adaptive method named ‘Contrast and Information Enhancement of Underwater Images’ (CIEUI) is proposed, which enhances underwater images by improving their contrast and information content using Multi-Objective Particle Swarm Optimization (MOPSO). Objective functions of MOPSO are chosen to act as guiding mechanism to ensure color & contrast correction and information enhancement respectively without introducing artifacts. Computed results not only have good contrast and color performance but also have better information content. The proposed CIEUI technique performs quantitatively and qualitatively better as compared to state-of-the-art algorithms.

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Authors and Affiliations

  1. Department of Information Technology, Delhi Technological University, Delhi, India

    Rajni Sethi

  2. Department of Electronics and Communication Engineering, Delhi Technological University, Delhi, India

    Indu Sreedevi

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  1. Rajni Sethi
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Correspondence to Rajni Sethi.

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Sethi, R., Sreedevi, I. Adaptive enhancement of underwater images using multi-objective PSO. Multimed Tools Appl 78, 31823–31845 (2019). https://doi.org/10.1007/s11042-019-07938-x

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