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Images captured under foggy conditions often have poor contrast and color. This is primarily due to air-light which degrades image quality exponentially with fog depth between the scene and the camera. In this paper, we restore fog-degraded images by first estimating depth using the physical model characterizing the RGB channels in a single monocular image. The fog effects are then removed by subtracting the estimated irradiance, which is empirically related to the scene depth information obtained, from the total irradiance received by the sensor. Effective restoration of color and contrast of images taken under foggy conditions are demonstrated. In the experiments, we validate the effectiveness of our method via representative performance measurements.