In this paper, we present a nonlocal structure tensor for feature description and apply it to the pixel level image fusion
within the wavelet framework. Local geometric shape information in wavelet coefficients can be extracted and
recognized by structure tensor. The structure tensor element is processed by use of the nonlocal means filter before
calculating its eigen-values. With the eigen-values of two source data, an adaptive weight function is employed to
reconstruct new detail coefficients of the fused image. Experimental results show the performance of the proposed
scheme.
KEYWORDS: Diffusion, Image restoration, Partial differential equations, Image denoising, Palladium, Denoising, Image processing, Sensors, Signal to noise ratio, Control systems
This paper presents an edge-preserving fourth order partial differential equation (PDE) for image restoration
derived from a new surface-based energy functional. The corresponding fourth order PDE can preserve edges and
avoid the staircase effect. The proposed model contains a function of gradient norm as an edge detector, which
controls the diffusion speed according to the local structure of the image and preserves more details. Denoising
results are given and we have also compared our method with some related PDE models.
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