IHDCP: Single Image Dehazing Using Inverted Haze Density Correction Prior.

Area of Science:

• Computer Vision
• Image Processing

Background:

• Image dehazing is vital for applications like autonomous driving and surveillance.
• Existing methods often struggle with efficiency and diverse scene types.

Purpose of the Study:

• To propose a novel and efficient single image dehazing algorithm.
• To introduce the Inverted Haze Density Correction Prior (IHDCP) for improved transmission estimation.

Main Methods:

• Formulating transmission using a pixel-wise gamma correction coefficient based on inverted haze density.
• Incorporating IHDCP into the atmospheric scattering model (ASM) and simplifying the resulting equation.
• Estimating model parameters using boundary constraints and deriving the gamma correction coefficient map.

Main Results:

• The IHDCP algorithm achieves visually appealing dehazing with high computational efficiency.
• Experimental results demonstrate superior performance compared to state-of-the-art methods on synthetic and real-world datasets.
• The method shows good generalization across various degraded scenes.

Conclusions:

• IHDCP offers an effective and efficient solution for single image dehazing.
• The proposed prior enhances transmission estimation, leading to improved dehazing results.
• The algorithm's robustness makes it suitable for diverse real-world applications.