Image De-Quantization Using Plate Bending Model
AbstractDiscretized image signals might have a lower dynamic range than the display. Because of this, false contours might appear when the image has the same pixel value for a larger region and the distance between pixel levels reaches the noticeable difference threshold. There have been several methods aimed at approximating the high bit depth of the original signal. Our method models a region with a bended plate model, which leads to the biharmonic equation. This method addresses several new aspects: the reconstruction of non-continuous regions when foreground objects split the area into separate regions; the incorporation of confidence about pixel levels, making the model tunable; and the method gives a physics-inspired way to handle local maximal/minimal regions. The solution of the biharmonic equation yields a smooth high-order signal approximation and handles the local maxima/minima problems. View Full-Text
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Völgyes, D.; Martinsen, A.C.T.; Stray-Pedersen, A.; Waaler, D.; Pedersen, M. Image De-Quantization Using Plate Bending Model. Algorithms 2018, 11, 110.
Völgyes D, Martinsen ACT, Stray-Pedersen A, Waaler D, Pedersen M. Image De-Quantization Using Plate Bending Model. Algorithms. 2018; 11(8):110.Chicago/Turabian Style
Völgyes, David; Martinsen, Anne C.T.; Stray-Pedersen, Arne; Waaler, Dag; Pedersen, Marius. 2018. "Image De-Quantization Using Plate Bending Model." Algorithms 11, no. 8: 110.
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