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Improving mesh-based motion compensation by using edge adaptive graph-based compensated wavelet lifting for medical data sets
- Source :
- IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, LA, USA, 2017, pp. 1507-1511
- Publication Year :
- 2023
-
Abstract
- Medical applications like Computed Tomography (CT) or Magnetic Resonance Tomography (MRT) often require an efficient scalable representation of their huge output volumes in the further processing chain of medical routine. A downscaled version of such a signal can be obtained by using image and video coders based on wavelet transforms. The visual quality of the resulting lowpass band, which shall be used as a representative, can be improved by applying motion compensation methods during the transform. This paper presents a new approach of using the distorted edge lengths of a mesh-based compensated grid instead of the approximated intensity values of the underlying frame to perform a motion compensation. We will show that an edge adaptive graph-based compensation and its usage for compensated wavelet lifting improves the visual quality of the lowpass band by approximately 2.5 dB compared to the traditional mesh-based compensation, while the additional filesize required for coding the motion information doesn't change.
- Subjects :
- Electrical Engineering and Systems Science - Image and Video Processing
Subjects
Details
- Database :
- arXiv
- Journal :
- IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, LA, USA, 2017, pp. 1507-1511
- Publication Type :
- Report
- Accession number :
- edsarx.2301.04836
- Document Type :
- Working Paper