Dehazing is important in remote sensing image restorations to enhance the acquired low quality image for interpretation. However, traditional methods have some limitations for dehazing of remote sensing images due to its color distortion and noise. In this paper, we propose an improved method combining superpixel segmentation with luminance information of a haze image to estimate the atmospheric light instead of dark channel prior. Using this method with the haze imaging model, we can directly estimate the thickness of the haze and restore a high quality haze-free image. Experimental results on a variety of remote sensing haze images demonstrate our approach can achieve better image quality when compared with well-known He's [1] method for remote sensing images. Index Terms- Haze removal; superpixel segmentation; atmospheric scattering model;