Digital cameras are used in various scenarios; however, the sharpness of images captured outdoors may be reduced due to bad weather conditions such as fog and haze. Therefore, to obtain a clear image, it is essential to remove haze. In this study, we propose a haze removal method by separating the sky and foreground regions and applying different processes to the sky region because it has different features from the foreground region; this improves the visibility of the image. We assume that the sky region is a bright region that does not change much throughout the image and extract multiple sky region candidates, which are merged according to color distance. Next, we estimate atmospheric light and transmittance of haze. Atmospheric light is the light scattered in the entire image, and transmittance of haze is the amount of scattered light. The sky region determines the brightness of atmospheric light, and the impression of the entire image determines the color of the atmospheric light. Transmittance of haze is estimated by dark channel features and morphological operations. The conventional method uses a fixed-sized patch due to which a smooth transmission map may not be generated. Our method generates a smooth transmission map for any image by changing the patch size. The haze in the image is removed using the estimated atmospheric light and transmittance; however, the resulting image is dark for which brightness correction is performed and a clean image without haze is obtained.