Log Transform Based Optimal Image Enhancement Using Firefly Algorithm for Autonomous Mini Unmanned Aerial Vehicle: An Application of Aerial Photography

• Autor(a) principal: Sourav Samanta
• Data de Publicação: 2018
• Outros Autores: Amartya Mukherjee, Amira S. Ashour, Nilanjan Dey, João Manuel R. S. Tavares, Wahiba Ben Abdessalemkaraa, Redha Taiar, Ahmad Taher Azar, Aboul Ella Hassanien
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://hdl.handle.net/10216/116845
• topic: Ciências Tecnológicas, Ciências da engenharia e tecnologias; Technological sciences, Engineering and technology

The Unmanned Aerial Vehicles (UAV) are widely used for capturing images in border area surveillance, disaster intensity monitoring, etc. An aerial photograph offers a permanent recording solution as well. But rapid weather change, low quality image capturing equipments results in low/poor contrast images during image acquisition by Autonomous UAV. In this current study, a well-known meta-heuristic technique, namely, Firefly Algorithm (FA) is reported to enhance aerial images taken by a Mini Unmanned Aerial Vehicle (MUAV) via optimizing the value of certain parameters. These parameters have a wide range as used in the Log Transformation for image enhancement. The entropy and edge information of the images is used as an objective criterion for evaluating the image enhancement of the proposed system. Inconsistent with the objective criterion, the FA is used to optimize the parameters employed in the objective function that accomplishes the superlative enhanced image. A low-light imaging has been performed at evening time to prove the effectiveness of the proposed algorithm. The results illustrate that the proposed method has better convergence and fitness values compared to Particle Swarm Optimization. Therefore, FA is superior to PSO, as it converges after a less number of iterations.