The condition of the images is degraded in some environmental situations, such as haze, fog, and mist. In several computer vision (CV) applications, such as remote sensing, border surveillance, and automated driver-assisted systems, image quality plays a significant role. Therefore, it is necessary to design a procedure to eliminate the haze effect, thereby improving the image quality. Several techniques are proposed earlier for haze removal. However, most of these techniques produce under-exposure and halo artifacts. A brightness enhancement called low-brightness image enhancement (LBIE) scheme is developed to address the under-exposure issue. For dehazing purposes, the dual transmission maps (DTM) are implemented in this work which overcome the halo-artifacts problem. The application of LBIE and DTM methods improves the dehazing performance when compared to state-of-the-art haze-removal methods.