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<p>Satellite images commonly exhibit constrained brightness values, facilitating the enhancement of contrast to preserve pertinent details before conducting further image analysis. Enhancing the brightness of the images serves as an first phase in the analysis of image, given that image quality significantly influences human perception. Metaheuristics have proven to be effective in addressing intricate image processing challenges. This paper presents an effort to present the versatility and effectiveness of a method in searching best solutions to enhance the brightness of the images. The image’s intensity is improved through a transformation term (TT) and the AVA (African Vulture Algorithm). The intensity transformation integrates information from optimal information of the satellite images. The AVA method is utilized to determine the optimal pixel values capable of enhancing the maximization in low contrast satellite images. Simultaneously, the AVA considers the objective function which enhances the image quality by considering the factors which includes entropy and edge details. The experimentation is demonstrated on the dataset and achieved better contrast and entropy values of 21.036 and 0.806 respectively.</p>

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Optimizing satellite image brightness and entropy with the african vulture algorithm for enhanced visual quality

  • 期刊论文

  • 发表日期：

    2025年3月1日

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  • V. Rajesh,
  • P. Sivakumar

摘要

Satellite images commonly exhibit constrained brightness values, facilitating the enhancement of contrast to preserve pertinent details before conducting further image analysis. Enhancing the brightness of the images serves as an first phase in the analysis of image, given that image quality significantly influences human perception. Metaheuristics have proven to be effective in addressing intricate image processing challenges. This paper presents an effort to present the versatility and effectiveness of a method in searching best solutions to enhance the brightness of the images. The image’s intensity is improved through a transformation term (TT) and the AVA (African Vulture Algorithm). The intensity transformation integrates information from optimal information of the satellite images. The AVA method is utilized to determine the optimal pixel values capable of enhancing the maximization in low contrast satellite images. Simultaneously, the AVA considers the objective function which enhances the image quality by considering the factors which includes entropy and edge details. The experimentation is demonstrated on the dataset and achieved better contrast and entropy values of 21.036 and 0.806 respectively.