ICTACT Journal on Image and Video Processing

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A Review on Comparative Analysis of Dehazing of Remote Sensing Images using Different Filters


Affiliations
1 Department of Electronics and Communication Engineering, Government College of Technology, India
     

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Haze is an atmospheric phenomenon caused by scattering of atmospheric particles in air and these factor causes deterioration of images, captured by the sensors. Haze detection, removal and enhancement of dehazed images are extremely important for the analysis and interpretation of Remote sensing images. This work presents the comparison of haze removal methodologies and analysis of dehazed images in terms of its image quality metrics. Consequently various imaging filters are employed to enhance fine details in the dehazed images and comparative analysis is presented. Simulation results reveal that the filter enhancement technique produces images with better quality and visible improvements in Quality metrics.

Keywords

Remote Sensing, Haze Removal, Adaptive Dehazing, Deformed Haze Imaging Model, Dark Channel Prior, Dark Channel Saturation Prior, Image Filters.
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  • A Review on Comparative Analysis of Dehazing of Remote Sensing Images using Different Filters

Abstract Views: 263  |  PDF Views: 0

Authors

M. Kamalam
Department of Electronics and Communication Engineering, Government College of Technology, India
N. Ameena Bibi
Department of Electronics and Communication Engineering, Government College of Technology, India

Abstract


Haze is an atmospheric phenomenon caused by scattering of atmospheric particles in air and these factor causes deterioration of images, captured by the sensors. Haze detection, removal and enhancement of dehazed images are extremely important for the analysis and interpretation of Remote sensing images. This work presents the comparison of haze removal methodologies and analysis of dehazed images in terms of its image quality metrics. Consequently various imaging filters are employed to enhance fine details in the dehazed images and comparative analysis is presented. Simulation results reveal that the filter enhancement technique produces images with better quality and visible improvements in Quality metrics.

Keywords


Remote Sensing, Haze Removal, Adaptive Dehazing, Deformed Haze Imaging Model, Dark Channel Prior, Dark Channel Saturation Prior, Image Filters.

References