Low-complexity merge candidate decision for fast HEVC encoding Multimedia and Expo Workshops (ICMEW), 2013 IEEE International Conference on Muchen LI, Keiichi Chono, Satoshi Goto 1

outline  Introduction  Low-complexity merge candidate decision  A. GMV Based Merge Candidate Decision  B. Position-Priority Based Merge Candidate Decision  Simulation Results 2

Introduction #1  Although the Merge mode brings significant coding efficiency improvements, the complexity of its Merge candidate decision associated with Rate-Distortion cost computation is proportional to the number of Merge candidates.  The investigation shows that redundant and unnecessary RD cost computation for particular Merge candidates between Ground-truth MVs (GMVs) obtained by motion estimation (ME) and Merge candidates. 3

Introduction #2  For each PU, the Merge mode utilizes up to 5 MVP candidates and selects the best one based on computationally expensive Rate- Distortion (R-D) cost check for each Merge candidate.  Sun of absolute transformed difference (SATD)  8-tap filter 4

Introduction #3  Merge mode allows at most 5 Merge MV candidates from the previously inter-coded blocks located in the positions described.  5 spatial  2 temporal 5

Introduction #4 6

Introduction #5  As well as Merge mode, AMVP mode also introduces MVP competition technology and predicts the MV of current PU as one of the MVPs.  Ground-truth MV 7

Introduction #6 8

Introduction #7  In the study, it is found that the Merge candidates are typically distributed in the SR and the Merge candidate decision is based on the R-D cost that also uses the SATD measurement.  Checking the SATD for all the Merge candidates is redundant and excessive in some cases. 9

Low-complexity merge candidate decision #A1 GMV Based Merge Candidate Decision  The ME in the AMVP mode check and the merge candidate decision employ the same SATD measurement and there is a correlation between them.  Basically, the GMV has the minimum SATD in the SR and it can be taken as a reference for the Merge candidate decision. 10

Low-complexity merge candidate decision #A2 GMV Based Merge Candidate Decision 11

Low-complexity merge candidate decision #A3 GMV Based Merge Candidate Decision  In Case (2), the GMV is identical to the BMMV, including the prediction direction, reference picture index and MV components. Case (2) can also be called as equal case.  The GMV represents the true MV of the current PU better than or equal to the BMMV (up to 88.38% for LP and 72.91% for RA). 12

Low-complexity merge candidate decision #A4 GMV Based Merge Candidate Decision 13

Low-complexity merge candidate decision #B1 Position-Priority Based Merge Candidate Decision 14

Low-complexity merge candidate decision #B2 Position-Priority Based Merge Candidate Decision  A1, B1, and T are always the dominant positions for all the cases. When the CU size becomes larger, the total proportion of A1, B1 and T becomes smaller and the order of them is varying a little for different partitions.  A1, B1 and T are available  A1, B1 and T are not available 15

Low-complexity merge candidate decision #B3 Position-Priority Based Merge Candidate Decision 16

Simulation Results #1 17

Simulation Results #2 18

Simulation Results #3 19

Simulation Results #4 20