In this paper we compare the classification accuracy of using compressed domain color (CDC) descriptors versus traditional full decoded images, for the purposes of topographic classification of wireless capsule endoscopy images. Results using a dataset of 26469 images, divided into stomach, small intestine and large intestine show a difference in classification accuracy below 1%. We also show that errors are mostly located near zone transitions (the pylorus and the ileo-cecal valve) and motivate the need for other visual descriptors (e.g. shape, motion) for addressing these specific areas. We conclude we can use the advantages of CDC in this type of classification with minor accuracy sacrifice.