Image processing has experienced significant growth in recent years, emerging as a prominent area of study with numerous practical applications. The degradation of image quality is a consequence of the attenuation of light as depth increases. It exhibits a range of detrimental consequences, such as poor contrast, saturation deficiencies, texture distortion, color distortion, and edge distortion. The mitigation of these effects and the enhancement of image quality is achieved through the utilization of a computer vision algorithm known as image dehazing. Many researchers have put forth various techniques for single image dehazing in order to accomplish this task. This paper proposed a grey wolf optimization (GWO) algorithm to estimate the transmission map of the hazy image. The airlight is estimated using a statistical order filter. It is thoroughly examined using structure similarity index, peak signal-to-noise ratio, and naturalness image quality evaluator and comparative analysis is performed with other existing algorithms.