Motion Vector Forecast and Mapping (MV-FMap) Method for Entropy Coding based Video Coders

Julien Le Tanou (1) , Jean-Marc Thiesse (1, 2) , Joël Jung (1) , Marc Antonini (2)

1 Orange Labs [Issy les Moulineaux]
2 Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe IMAGES-CREATIVE

Since the finalization of the H.264/AVC standard and in order to meet the target set by both ITU-T and MPEG to define a new standard that reaches 50% bit rate reduction compared to H.264/AVC, many tools have efficiently improved the texture coding and the motion compensation accuracy. These improvements have resulted in increasing the proportion of bit rate allocated to motion information. Thus, the bit rate reduction of this information becomes a key subject of research. This paper proposes a method for motion vector coding based on an adaptive redistribution of motion vector residuals before entropy coding. Motion information is gathered to forecast a list of motion vector residuals which are redistributed to unexpected residuals of lower coding cost. Compared to H.264/AVC, this scheme provides systematic gain on tested sequences, and 2.3% in average, reaching up to 4.9% for a given sequence.

Mots clés: Video coding; competition index signalization; chroma and luma sample; data hiding

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Julien Le Tanou, Jean-Marc Thiesse, Joël Jung, Marc Antonini. Motion Vector Forecast and Mapping (MV-FMap) Method for Entropy Coding based Video Coders. MMSP'10 2010 IEEE International Workshop on Multimedia Signal Processing, Oct 2010, Saint Malo, France. pp.206. ⟨hal-00531819⟩