Multiview Image Compression: Future Challenges and Today’s Solutions N.Sgouros, M.Sangriotis, D.Maroulis Dept. of Informatics and Telecommunications, University of Athens Panepistimiopolis, Ilissia, Athens 15784, Greece E-mail: {nsg, sathin, sagri, dmarou, optel}@di.uoa.gr Abstract Large data volumes that are produced during multiview image generation have to be efficiently compressed in order to be stored or transmitted. Two main classes of encoders use transform coding techniques either by utilizing spatial prediction methods or by using higher degree transforms. Our work summarizes the various types of multiview image sets and the corresponding coding techniques and, provides a useful comparison of the compression efficiency of these two classes of multiview image encoders over a variety of test images. Representation quality and application specific requirements are taken into account in order to decide in favour of the encoder to be used. Keywords: Multiview image coding, Transform coding, Higher order transformations 1. Introduction One of the dominant standards in today’s stereoscopic viewing methods is the use of stereoscopic image pairs that are appropriately projected to the viewer’s eyes and are called stereopairs. As new technologies evolve in the field, a series of multiview stereoscopic displays appear, that use larger image sets which are captured from slightly different viewpoints. Due to this fact the procedure produces more realistic three dimensional representations in regard to the classic two view approach. Most of the multiview techniques incorporate all necessary optical components in the display device, providing an unconstrained three dimensional experience within a viewing zone. It is evident that these image sets contain intra-image as well as inter-image redundancy that when properly exploited can reduce the total amount of image data that have to be stored or transmitted. To this end the large amount of data that result