Background:
Real-time video coding is a very interesting area of research with extensive
applications into remote sensing and medical imaging. Many research works and multimedia
standards for this purpose have been developed. Some processing ideas in the area are focused on
second-step (additional) compression of videos coded by existing standards like MPEG 4.14.
Materials and Methods:
In this article, an evaluation of some techniques with different complexity
orders for video compression problem is performed. All compared techniques are based on interpolation
algorithms in spatial domain. In details, the acquired data is according to four different interpolators
in terms of computational complexity including fixed weights quartered interpolation (FWQI)
technique, Nearest Neighbor (NN), Bi-Linear (BL) and Cubic Cnvolution (CC) interpolators. They
are used for the compression of some HD color videos in real-time applications, real frames of video
synthetic aperture radar (video SAR or ViSAR) and a high resolution medical sample.
Results:
Comparative results are also described for three different metrics including two reference-
based Quality Assessment (QA) measures and an edge preservation factor to achieve a general
perception of various dimensions of the mentioned problem.
Conclusion:
Comparisons show that there is a decidable trade-off among video codecs in terms of
more similarity to a reference, preserving high frequency edge information and having low computational
complexity.
AV1 and VVC Video Codecs: Overview on Complexity Reduction and Hardware Design
