Small Target Recognition in Low-Contrast Images Using Top-Hat Transformation

In low-contrast images, we can employ the morphological top-hat transformation to detect small targets. This technique effectively enhances subtle features by subtracting the morphological opening from the original image, making it particularly suitable for identifying faint targets against noisy backgrounds. For maritime applications, the algorithm can be implemented using structural elements that match target characteristics - disk-shaped elements for ship detection and linear elements for fluorescence trajectory identification. The implementation typically involves these key steps: 1) Apply morphological opening with an appropriately sized structuring element 2) Subtract the opened image from the original 3) Apply thresholding to isolate targets. This approach effectively handles challenging scenarios where targets have minimal contrast difference from the background, such as ship detection in hazy conditions or fluorescence tracking in oceanographic research.