<p>Due to scattering and absorption by suspended particles in hazy atmospheres, images captured suffer from visibility attenuation, low contrast and color cast issues. Handling a wide variety of hazy conditions with such degradations to reduce haze in images is a challenging task. In this regard, our paper proposes a novel image dehazing framework based on new hazy image priors, namely, the Haze Hue Prior and the Haze Saturation Prior. The Haze Hue Prior (HHP) presents distinguishing properties of hue in non-color-cast and color-cast hazy images, which is exploited to classify hazy images into these two categories. The Haze Saturation Prior (HSP) provides characteristic properties of saturation in hazy conditions, which is utilized to handle color distortion. The proposed framework also leverages a novel foreground-aware strategy to compute the atmospheric light and a depth-aware strategy to estimate the transmission map, which are then used in the standard atmospheric light scattering model to achieve dehazing. Extensive quantitative evaluations demonstrate that our proposed framework outperforms the state-of-the-art across a wide range of natural and synthetic hazy images. Subjective evaluations show that our proposed framework effectively removes color cast, significantly reduces haze, and preserves the natural image appearance without introducing noticeable distortion Project page: <a href="https://m14roy.github.io/HHHSPID-Image-Dehazing/">https://m14roy.github.io/HHHSPID-Image-Dehazing/</a></p>