Scattering Medium Removal Using Adaptive Masks for Scatter in the Spatial Frequency Domain

Abstract

To address this issue, this paper presents an adaptive method for removing scattering media using a mask based on wireless communication fading models. We hypothesize a similarity between light propagation and wireless communication systems, which incorporates scattering estimates through models such as the Rayleigh and Rician fading models, which are applied to process the captured images and mitigate scattering effects. Our proposed method incorporates two systems: the Scattered Image Model and the Scattering Media Model. The conventional dehazing method requires processing sequences’ approximated depth map or specific background. However, the proposed method functions regardless of the image’s depth and specific background colors. To validate the proposed method, we conducted optical experiments and tested outdoor images. The results were compared with conventional haze-removal methods, such as dark channel prior and Peplography, using various image quality metrics, e.g., the Peak Signal-to-Noise ratio, Structural Similarity Index Measurement, Tone Mapped Image Quality, and Feature Similarity Index Measurement extended to color imagery. The experimental results demonstrated significant improvements over the conventional methods across all metrics.