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Fast Inpainting-Based Compression: Combining Shepard Interpolation with Joint Inpainting and Prediction

机译:基于快速修复的压缩:将Shepard插值与联合修复和预测相结合

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Inpainting-based compression has been suggested as a qualitative competitor to the JPEG family of transform-based codecs, specifically for high compression ratios. However, it also requires sophisticated interpolation, data optimisation and encoding tasks that are both slow and hard to implement. We propose a fast and simple alternative that combines Shepard interpolation with a novel joint inpainting and prediction approach. It represents the image by a fraction of its pixel values on a sparse regular subgrid that are selected by an efficient optimisation strategy. Experiments show that our codec is up to five orders of magnitude faster than traditional inpainting-based approaches. Qualitatively, it can surpass transform-based codecs, in particular for high compression ratios and cartoon-like images.
机译:已经提出基于绘画的压缩是JPEG系列基于变换的编解码器的质的竞争者,特别是对于高压缩率。但是,它还需要复杂且缓慢且难以实现的内插,数据优化和编码任务。我们提出了一种快速,简单的替代方案,将Shepard插值与一种新颖的联合修复和预测方法相结合。它通过稀疏规则子网格上的像素值的一部分来表示图像,该子网格由有效的优化策略选择。实验表明,我们的编解码器比传统的基于绘画的方法快五个数量级。从质量上讲,它可以超越基于变换的编解码器,尤其是对于高压缩率和类似卡通的图像而言。

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