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

被引:15
作者
Samanta, Sourav [1 ]
Mukherjee, Amartya [2 ]
Ashour, Amira S. [3 ,4 ]
Dey, Nilanjan [5 ]
Tavares, Joao Manuel R. S. [6 ]
Karaa, Wahiba Ben Abdessalem [4 ,7 ]
Taiar, Redha [8 ]
Azar, Ahmad Taher [9 ,10 ]
Hassanien, Aboul Ella [11 ]
机构
[1] Univ Inst Technol, Dept Comp Sci & Engn, Burdwan, W Bengal, India
[2] Inst Engn & Management, Dept CSE & BSH, Kolkata, India
[3] Tanta Univ, Fac Engn, Dept Elect & Elect Commun Engn, Tanta, Egypt
[4] Taif Univ, Coll Comp & IT, At Taif, Saudi Arabia
[5] Techno India Coll Technol, Dept Informat Technol, Kolkata, India
[6] Univ Porto, Fac Engn, Dept Engn Mecan, Inst Ciencia & Inovacao Engn Mecan & Engn Ind, Rua Dr Roberto Frias S-N, P-4200465 Porto, Portugal
[7] RIADI GDL Lab, Manouba, Tunisia
[8] Univ Reims Champagne Ardennes, Reims, France
[9] Benha Univ, Fac Comp & Informat, Banha, Egypt
[10] Nile Univ, 6th Of October City, Egypt
[11] Cairo Univ, Fac Comp & Informat, Sci Res Grp Egypt, Cairo, Egypt
关键词
Mini unmanned aerial vehicle; meta-heuristic approaches; particle swarm optimization; firefly algorithm; log transformation; aerial photography;
D O I
10.1142/S0219467818500195
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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.
引用
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页数:25
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