Rombaut Joost, Pizurica Aleksandra, Philips Wilfried
Department for Telecommunications and Information Processing, Ghent University, Ghent, Belgium.
IEEE Trans Image Process. 2008 Oct;17(10):1849-63. doi: 10.1109/TIP.2008.2002834.
In image communication over lossy packet networks (e.g., cell phone communication), packet loss errors lead to damaged images. Damaged images can be repaired with passive error concealment methods, which use neighboring coefficient or pixel values to estimate the missing ones. Neighboring image data should, thus, be spread over different packets. This paper presents a novel robust packetization method for the transmission of image content in lossy packet networks. We first define novel criteria for a good packetization. Based on these properties, we propose a cost function for packetization masks. We then use stochastic optimization to calculate optimal packetization masks. We test our packetization technique on both wavelet coding and DCT coding. Compared to other packetization techniques, we are able to achieve the same or better mean quality of the reconstructed images but with less fluctuation in quality, which is important for the viewer experience. In this way, we significantly increase the worst case quality, especially for high packet loss rates. This leads to visually more pleasing images in case of a passive reconstruction.
在有损分组网络（如手机通信）上进行图像通信时，分组丢失错误会导致图像受损。受损图像可以用被动错误隐藏方法修复，该方法利用相邻系数或像素值来估计缺失的系数或像素值。因此，相邻图像数据应分布在不同的分组中。本文提出了一种用于在有损分组网络中传输图像内容的新型鲁棒分组方法。我们首先为良好的分组定义了新的标准。基于这些特性，我们提出了一个用于分组掩码的代价函数。然后，我们使用随机优化来计算最优分组掩码。我们在小波编码和离散余弦变换（DCT）编码上测试了我们的分组技术。与其他分组技术相比，我们能够实现相同或更好的重建图像平均质量，但质量波动更小，这对观看体验很重要。通过这种方式，我们显著提高了最坏情况下的质量，特别是对于高分组丢失率的情况。在被动重建的情况下，这会产生视觉上更令人愉悦的图像。
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