Flood detection/monitoring using adjustable histogram equalization technique

Area of Science:

• Remote Sensing
• Image Processing
• Environmental Monitoring

Background:

• Existing flood monitoring techniques often suffer from overenhancement and artifacts.
• Accurate flood detection is crucial for disaster management and urban planning.
• Image contrast adjustment is key to improving the quality of flood maps.

Purpose of the Study:

• To propose an improved flood monitoring technique using adjustable histogram equalization.
• To overcome the limitations of existing methods in flood map generation.
• To provide a robust and automated solution for flood detection and monitoring.

Main Methods:

• Utilizes adjustable histogram equalization to enhance image contrast.
• Processes pre- and post-flood images through various processing steps.
• Generates flood maps automatically without user interaction.

Main Results:

• The proposed technique effectively adjusts image contrast, reducing artifacts and overenhancement.
• Generated flood maps exhibit superior quality compared to existing state-of-the-art methods.
• The technique provides reliable outputs for flood monitoring and detection.

Conclusions:

• Adjustable histogram equalization offers a significant improvement for flood monitoring.
• The automated technique enhances the accuracy and usability of flood maps.
• This method presents a valuable tool for real-time environmental monitoring and disaster response.