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Overlapped adaptive partitioning for image coding based on the theory of iterated functions systems

机译:基于迭代函数系统理论的图像编码重叠自适应分区

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Memoryless blockwise partitioning induces blockiness artifacts highly disturbing to the human visual system. This paper presents a new partitioning with overlapped blocks in the context of image coding based on iterated transformations systems. Each block of the partition is extended by n pixels. As usual each cell is expressed as the contractive transformation of another part of the image. During the decoding, values of pixels corresponding to overlapped regions are computed as the weighted sum of the different contributions leading to that pixel. This overlapped partitioning is embedded in a quadtree segmentation of the image support. In order to avoid blurring effects in small blocks while maintaining efficiency in bigger ones, the overlapping width n is a function of the block size. Simulations show a very significant improvement of the visual quality of decoded images with no increase of the bitrate request.
机译:无记忆的按块划分会引起对人的视觉系统造成极大干扰的块状伪影。本文基于迭代变换系统,在图像编码的背景下提出了一种具有重叠块的新分区方法。分区的每个块都扩展了n个像素。像往常一样,每个单元格表示为图像另一部分的收缩变换。在解码期间,将与重叠区域相对应的像素的值计算为导致该像素的不同贡献的加权和。此重叠分区嵌入在图像支持的四叉树分割中。为了避免小块中的模糊效果,同时保持大块中的效率,重叠宽度n是块大小的函数。仿真显示在不增加比特率请求的情况下,解码图像的视觉质量有了非常显着的提高。

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