Normal mapping is a powerful technique for simulation of surface roughness by means of normal maps. The high polygon count model is represented by coarse polygon mesh with fine details stored in the normal map. Thus, the technique greatly reduces geometric complexity of models and shifts the demands on effective normal map compression algorithms. In this paper we present normal compression algorithm which extends the commonly used 3Dc algorithm introduced by ATI with wavelet compression based on Haar basis. Each block component is coded by one of two modes and the one which introduce the smallest error is chosen for block component representation. This allows for better adaptation to normal map data and improves the peak signal to noise ratio as compared to standalone 3Dc.