Shortwave Infrared Image Dehazing Based on Dark Channel Prior

To solve the problems of blurred image quality and low-resolution weather haze in shortwave infrared imaging systems, a shortwave infrared image-defogging algorithm based on a dark channel prior is proposed. First, the algorithm obtains the dark-channel image data using an improved dark-channel prior. Then, the atmospheric light is estimated based on the dark channel data. To avoid local highlights or blurred details of the target, the transmittance map is refined and enhanced using guided filtering and multi-scale retinex (MSR). Finally, the defogged image is inverted using the atmospheric scattering model. The shortwave infrared image processed by this algorithm was verified in terms of subjective vision and objective indicators, displaying a remarkable defogging effect, rich details, and appropriate brightness.