DIBR synthesized image quality assessment based on morphological wavelets
Résumé
Most of the Depth Image Based Rendering (DIBR) techniques produce synthesized images which contain nonuniform geometric distortions affecting edges coherency. This type of distortions are challenging for common image quality metrics. Morphological filters maintain important geometric information such as edges across different resolution levels. In this paper, morphological wavelet peak signal-to-noise ratio measure, MW-PSNR, based on morphological wavelet decomposition is proposed to tackle the evaluation of DIBR synthesized images. It is shown that MW-PSNR achieves much higher correlation with human judgment compared to the state-of-the-art image quality measures in this context.
Mots clés
depth image based rendering
DIBR synthesized image evaluation
DIBR synthesized image quality assessment
distortion
edge coherency
edge detection
image filtering
image quality
image quality metrics
Lattices
lifting scheme
measurement
morphological filters
morphological wavelet decomposition
morphological wavelet peak signal-to-noise ratio measure
morphological wavelets
Multi-scale PSNR
MW-PSNR
nonseparable morphological wavelet decomposition
nonuniform geometric distortions
quincunx sampling
rendering (computer graphics)
Signal resolution
wavelet transforms