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• W2461437958 abstract "This paper presents improvements in image gap restoration through the incorporation of edge-based directional interpolation within multi-scale pyramid transforms. Two types of image edges are reconstructed: 1) the local edges or textures, inferred from the gradients of the neighboring pixels and 2) the global edges between image objects or segments, inferred using a Canny detector. Through a process of pyramid transformation and downsampling, the image is progressively transformed into a series of reduced size layers until at the pyramid apex the gap size is one sample. At each layer, an edge skeleton image is extracted for edge-guided interpolation. The process is then reversed; from the apex, at each layer, the missing samples are estimated (an iterative method is used in the last stage of upsampling), up-sampled, and combined with the available samples of the next layer. Discrete cosine transform and a family of discrete wavelet transforms are utilized as alternatives for pyramid construction. Evaluations over a range of images, in regular and random loss pattern, at loss rates of up to 40%, demonstrate that the proposed method improves peak-signal-to-noise-ratio by 1-5 dB compared with a range of best published works." @default.
• W2461437958 created "2016-07-22" @default.
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• W2461437958 date "2016-09-01" @default.
• W2461437958 modified "2023-09-26" @default.
• W2461437958 title "Edge-Guided Image Gap Interpolation Using Multi-Scale Transformation" @default.
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• W2461437958 doi "https://doi.org/10.1109/tip.2016.2590825" @default.
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