MCPNS: A Macropixel Collocated Position and Its Neighbors Search for Plenoptic 2.0 Video Coding
Recently, it was demonstrated that a newly focused plenoptic 2.0 camera can capture much higher spatial resolution owing to its effective light field sampling, as compared to a traditional unfocused plenoptic 1.0 camera. However, due to the nature difference of the optical structure between the plen...
Gespeichert in:
Hauptverfasser: | , , , |
---|---|
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Recently, it was demonstrated that a newly focused plenoptic 2.0 camera can
capture much higher spatial resolution owing to its effective light field
sampling, as compared to a traditional unfocused plenoptic 1.0 camera. However,
due to the nature difference of the optical structure between the plenoptic 1.0
and 2.0 cameras, the existing fast motion estimation (ME) method for plenoptic
1.0 videos is expected to be sub-optimal for encoding plenoptic 2.0 videos. In
this paper, we point out the main motion characteristic differences between
plenoptic 1.0 and 2.0 videos and then propose a new fast ME, called macropixel
collocated position and its neighbors search (MCPNS) for plenoptic 2.0 videos.
In detail, we propose to reduce the number of macropixel collocated position
(MCP) search candidates based on the new observation of center-biased motion
vector distribution at macropixel resolution. After that, due to large motion
deviation behavior around each MCP location in plenoptic 2.0 videos, we propose
to select a certain number of key MCP locations with the lowest matching cost
to perform the neighbors MCP search to improve the motion search accuracy.
Different from existing methods, our method can achieve better performance
without requiring prior knowledge of microlens array orientations. Our
simulation results confirmed the effectiveness of the proposed algorithm in
terms of both bitrate savings and computational costs compared to existing
methods. |
---|---|
DOI: | 10.48550/arxiv.2310.08006 |