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Depth Modeling With Spectral Selective Region Coding For Image Inpainting

机译:深度建模与谱选择区编码图像修复

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Image inpainting, has an evolving approach for image quality enhancement and image visualization. In the process of image inpainting, pixels of similar area variants are considered in a tracing manner to achieve the objectives of unwanted image coefficient which are introduced due to detritions in image handing. To overcome this issue, images are processed in spatial domain, where, images are traced using 8-neighbor region growing method to achieve the objective of image enhancement However, in such approach, the pixel variations are observed in one variation plane. The variation with respect to successive pixel variants is not observed. To develop a new coding in considering with multiple domains, in this paper a new inpainting approach based on image depth coding is suggested.
机译:图像修正,具有一种不断变化的图像质量增强和图像可视化方法。在图像染色的过程中,以追踪方式考虑类似区域变体的像素,以实现由于图像递送中的偏移而引入的不希望的图像系数的目标。为了克服这个问题,在空间域中处理图像,其中,使用8邻区域越来越多的方法来追踪图像以实现图像增强的目标,然而,在这种方法中,在一个变型平面中观察到像素变化。未观察到相对于连续像素变体的变化。为了在考虑多个域中开发新的编码,本文提出了一种基于图像深度编码的新的一种新的初步方法。

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