Images of outdoor scenes are usually degraded under bad weather conditions and bad environment which results in a hazy image. The most of haze removal methods based on a single image have ignored the effects of sensor blur and noise. Therefore, in this paper we propose a simple but effective image priodark channel prior to remove haze from a single input image. We employ an extremum approximate method to extract the atmospheric light and propose a contour preserving estimation to obtain the transmission by using edge preserving and mean filters alternately. The dark channel prior is a kind of statistics of outdoor haze-free images. Using this prior with the haze imaging model we can directly estimate the thickness of the haze image and recover a high-quality dehaze image which is similar to natural image. Our method can efficiently avoid the halo artifact generated in the recovered image. This paper describes haze removation technique using Haze Removal algorithm. Software reference model for haze removal method has been modeled in MATLAB/ Simulink.