Computer vision is an interdisciplinary scientific field and has its own importance in the areas of agriculture, forestry, geography, land surveying, and military, with the advantage of rich information. Image processing techniques are frequently used to improve images and extract useful information from them. In foggy conditions, visual systems’ images suffer significantly, making it difficult to detect, track, and recognise targets. Image contrast is significantly masked by fog. Therefore, it is important to recover the real scene from such a blurry image. Due to the poor visibility of outdoor images generates significant problem for military applications, this leads to increase the soldier’s death because of the bad weather conditions on the border of Indian army. This paper presents an efficient Defogging algorithm using histogram specification/matching with wavelet transform for military images. In this technique, the RGB image is transferred into hue saturation intensity colour space before the algorithm is applied. Saturation and intensity in an image are impacted by fog. Therefore, the contact limited adaptive histogram equalization (CLAHE) is utilised in this proposed work to enhance the contrast. In this algorithm, two correction modules are there. To correct the Saturation component, the CLAHE is applied. To correct the Intensity component, have two major steps: wavelet transformation and histogram specification/matching that perform low frequency enhancement. The experimental results demonstrate that this algorithm produces appealing defogged images with some performance metrices.