Background: Real-time video coding is a very interesting area of research with extensive applications in remote sensing and medical imaging. Many research works and multimedia standards for this purpose have been developed. Some processing ideas in the area like here are focused on second-step (additional) compression of videos coded by existing standards like MPEG 4.14.
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 convolution (CC) interpolators (in some texts, CC is named bi-cubic convolution, a well-known version of bi-cubic interpolation). 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 are 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. The study explicitly illustrates that FWQI can be the best selection for ViSAR data.