The image captured by camera is degraded by various atmospheric parameters for example rain, storm, wind, haze, snow. The removing haze is called dehazing, is naturally done in the physical degradation model, which requires a solution of an ill-posed inverse problem. In this paper we will discuss and do the comparative study of Adaptive Histogram Equalization (AHE), Contrast limited adaptive histogram equalization (CLAHE) and dark channel prior (modified DCP). This article suggest image and video image defogging algorithm working on dark channel prior technique. The modified DCP is derived from the characteristic of natural outdoor images that the intensity value of at least one color channel within a local window is close to zero. The modified DCP system has good haze elimination and color managing potential for the images with various angles of haze. The dehazing is done through four major steps: atmospheric light estimation, transmission map estimation, transmission map refinement, and image reconstruction. This four step solution of modified DCP will give solution to ill-posed inverse problem. This dehazing techniques can be used in advanced driverless assisted systems in autonomous cars, satellite imaging, underwater imaging etc