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The autoregressive (AR) model has been widely used in signal processing for its effective estimation, especially in image processing. Many dedicated $2\times $ interpolation algorithms adopt the AR model to describe the strong correlation between low-resolution (LR) pixels and high-resolution (HR) pixels. However, these AR model-based methods closely depend on the fixed relative position between...
In this paper, we propose an adaptive general scale interpolation algorithm considering the non-stationarity of natural images in local areas. In image 2× enlargement, there are fixed relative positions between low-resolution (LR) pixels and high-resolution (HR) pixels. Unknown HR pixels can be estimated by their available LR neighbors. However, such relative positions are not fixed in the general-scale...
In this paper, we propose a novel frame rate up-conversion algorithm based on joint motion vector refinement and visual-weighted motion compensation interpolation (MCI). It utilizes a hierarchical motion vector refinement to correct inaccurate motion vectors (MVs), which is composed of the global level and the local level. In the global level, distinct inaccurate MVs are detected by global controlling...
In this paper, we present a novel method for Super Resolution (SR) reconstruction with rotation invariance and search window relocation. To combine complementary information in observed images to generate a higher resolution image, we first relocate search window to involve potential similar patches and then use rotation invariance similarity measure to find accurate similar patches. Comparing with...
Sparsity-based super-resolution has attracted lots of attention. Due to the high dimensionality of image data, sparsity-based methods are often in a patch-wise manner and simply impose the smoothness constraints on the overlapped regions between reconstructed patches. However, the imposed smoothness constraint is commonly weak to regularize super-resolution problem when the observed low-resolution...
Modeling the nonstationarity of image signals is one of the challenging issues for image interpolation. In this paper, we propose a similarity probability modeling to faithfully characterize the nonstationarity of image signals, and present a novel image interpolation algorithm based on the proposed model. The missing pixels are estimated in groups by weighted block estimation. The weight of each...
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