Cosine transform coding captures the major features of an image at bit rates as low as 0.5 bits per pixel (BPP). However, because the coding is done in transform space, spatial edge information is lost and the images appear soft even at 3BPP. Spatial techniques such as DPCM with entropy encoding preserve edges but fail, ungracefully, at about 2BPP. In this paper we combine the two. The reconstruction from transform coding is compared with the original and the spatial error signal is quantized and encoded. The results are compared with conventional DPCM and cosine transform encoding.