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Hash-Based Line-by-Line Template Matching for Lossless Screen Image Coding

机译:基于散列的逐行模板匹配,可实现无损屏幕图像编码

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Template matching (TM) was proposed in the literature a decade ago to efficiently remove non-local redundancies within an image without transmitting any overhead of displacement vectors. However, the large computational complexity introduced at both the encoder and the decoder, especially for a large search range, limits its widespread use. This paper proposes a hash-based line-by-line template matching (hLTM) for lossless screen image coding, where the non-local redundancy commonly exists in text and graphics parts. By hash-based search, it can largely reduce the search complexity of template matching without an accuracy degradation. Besides, the line-by-line template matching increases prediction accuracy by using a fine granularity. Experimental results show that the hLTM can significantly reduce both the encoding and decoding complexities by 68 and 23 times, respectively, compared with the traditional TM with a search radius of 128. Moreover, when compared with High Efficiency Video Coding screen content coding test model SCM-1.0, it can largely improve coding efficiency by up to 12.68% bits saving on screen contents with rich texts/graphics.
机译:十年前在文献中提出了模板匹配(TM),以有效去除图像中的非局部冗余,而无需传输任何位移矢量的开销。但是,特别是对于较大的搜索范围,在编码器和解码器处引入的大量计算复杂性限制了其广泛使用。本文提出了一种用于无损屏幕图像编码的基于哈希的逐行模板匹配(hLTM),其中文本和图形部分通常存在非局部冗余。通过基于散列的搜索,它可以在不降低准确性的情况下大大降低模板匹配的搜索复杂度。此外,逐行模板匹配通过使用精细的粒度提高了预测精度。实验结果表明,与搜索半径为128的传统TM相比,hLTM可以分别将编码和解码复杂度分别降低68和23倍。此外,与高效视频编码屏幕内容编码测试模型SCM相比-1.0,可以通过在带有丰富文本/图形的屏幕内容上节省多达12.68%的位来大大提高编码效率。

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