Sorry, you need to enable JavaScript to visit this website.

Jointly Optimized Transform Domain Temporal Prediction and Sub-pixel Interpolation

Citation Author(s):
Tejaswi Nanjundaswamy, Kenneth Rose
Submitted by:
Shunyao Li
Last updated:
11 March 2017 - 12:06am
Document Type:
Presentation Slides
Document Year:
2017
Event:
Presenters:
Shunyao Li
Paper Code:
IVMSP-L4.2
Categories:
 

Conventional pixel-domain block matching temporal (inter) prediction is suboptimal, since it ignores the underlying spatial correlation. Hence in our recent research we proposed transform domain temporal prediction (TDTP), wherein spatially de-correlated transform coefficients are individually predicted. Later we proposed extended block TDTP (EB-TDTP), which fully exploits spatial correlation around reference block boundaries. However, the transform domain temporal correlation exploited by (EB-)TDTP interferes with the frequency response of sub-pixel interpolation filters. Thus, in this paper, we propose to replace the standard sub-pixel interpolation with filters which are jointly designed with EB-TDTP based on statistics of the data, for either separable or non-separable interpolation structures. We also employ a two-loop asymptotic closed-loop (ACL) approach for statistically stable off-line design. Experiments show that our framework can achieve up to 1dB gain in PSNR over HEVC.

up
0 users have voted: