A Robust Detection Algorithm for Infrared Maritime Small and Dim Targets.

Area of Science:

• Computer Vision
• Remote Sensing
• Signal Processing

Background:

• Infrared maritime target detection is crucial for search systems but faces challenges like low signal-to-noise ratio, low resolution, and complex environmental interference.
• Small dim targets in infrared maritime images are difficult to distinguish due to low contrast, minimal pixel representation, and lack of edge information, obscured by background elements like islands and waves.

Purpose of the Study:

• To develop an effective algorithm for detecting small, dim targets in infrared maritime images amidst complex and dynamic sea conditions.
• To address the limitations of traditional algorithms in handling low-quality infrared imagery and environmental disturbances.

Main Methods:

• A novel maritime background filter using a sensitive region-based median filter to accurately extract and eliminate background.
• Development of a small dim target extraction operator analyzing gradient features and incorporating adaptive threshold segmentation.
• Deep analysis of target-background differences in infrared maritime imagery.

Main Results:

• The proposed algorithm, SRGM, demonstrates superior performance in detecting small dim targets compared to existing popular algorithms.
• Effective suppression of maritime background interferences like islands and waves.
• Accurate extraction of small dim targets even with low contrast and minimal pixel presence.

Conclusions:

• The developed SRGM algorithm offers a robust solution for infrared small dim target detection in diverse maritime environments.
• The method successfully overcomes the challenges posed by low image quality and complex backgrounds.
• This work contributes to enhancing the capabilities of maritime target search systems.