Image De-Hazing based on Krill Herd Optimization Algorithm

Authors

  • Sunkavalli Jaya Prakash Research Scholar, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India.
  • Manna Sheela Rani Chetty Professor, Department of Computer Science and Engineering,Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India.
  • A Jayalakshmi Professor& Head, Department of CSE,Prasad V. Potluri Siddhartha Institute of Technology, Kanuru, Vijayawada, AP, India

Keywords:

De-Hazing, Krill Herd Optimization algorithm, Noise filtering

Abstract

In digital images, haze damages the image quality which are taken in outdoor environment. This causes the degradation of image quality in terms of colour distortion and there exists a huge loss in the contrast. Because of the difficulty and importance of the problem, a lot of study has been done on picture de-hazing. A significant number of approaches were done based on dark channel prior shows successful results among picture haze removal approaches. Furthermore, the addition of a guided filter has greatly improved its efficiency. To address this issue, an optimization approach-based Image-Dehazing technique is applied in this research paper. It generates pixel-wised transmission without additional refining. Furthermore, image de-hazing procedures based on noise filtering perspective are used to achieve the goal of saturation enhancement while adhering to the minimum hue change constraint. The usefulness and efficiency of the suggested algorithm were evaluated by qualitative and quantitative analysis of the results.

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Flow Chart of Krill Herd Algorithm for Image De-Hazing

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Published

16.01.2023

How to Cite

Jaya Prakash, S., Rani Chetty, M. S. ., & Jayalakshmi, A. . (2023). Image De-Hazing based on Krill Herd Optimization Algorithm. International Journal of Intelligent Systems and Applications in Engineering, 11(1), 310–315. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2540

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Section

Research Article