Optimized JPEG image decompression with super-resolution interpolation using multi-order total variation
Optimized JPEG image decompression with super-resolution interpolation using multi-order total variation
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DOI：
10.1109/icip.2013.6738098
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发表时间：
2013-09
期刊：
影响因子：
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通讯作者：
Shunsuke Ono;I. Yamada
中科院分区：
文献类型：
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作者：
Shunsuke Ono;I. Yamada
我们提出了一种新的框架，从给定的JPEG图像中获得无伪影的放大图像。该方法基于新引入的JPEG图像采集模型，利用多阶总变分实现了图像的解压缩和超分辨率插值，从而大大降低了JPEG图像中出现的块噪声和蚊子噪声等伪影，而不会产生现有基于总变分的JPEG解压方法中常见的阶梯效应。我们还提出了一个计算效率高的优化方案，作为原始对偶分裂型算法的一个特例，用于解决与所提出的公式相关的凸优化问题。数值算例表明，与现有方法相比，该方法是有效的。
We propose a novel framework to obtain an artifact-free enlarged image from a given JPEG image. The proposed formulation based on a newly introduced JPEG image acquisition model realizes decompression and super-resolution interpolation simultaneously using multi-order total variation, so that we can drastically reduce artifacts appearing in JPEG images such as block noise and mosquito noise, without generating staircasing effect, which is typical in existing total variation-based JPEG decompression methods. We also present a computationally-efficient optimization scheme, derived as a special case of a primal-dual splitting type algorithm, for solving the convex optimization problem associated with the proposed formulation. Numerical examples show that the proposed method works effectively compared with existing methods.