基于hevc的全切片病理图像无损压缩

Victor Sanchez, Francesc Aulí Llinàs, Joan Bartrina-Rapesta, J. Serra-Sagristà
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引用次数: 18

摘要

提出了一种基于hevc的病理切片图像无损压缩方法。由于所描述的细胞结构和组织种类繁多,wsi通常具有大量的边缘和多向模式,因此我们将逐样本差分脉冲编码调制(SbS-DPCM)和边缘预测的优势结合到帧内编码过程中。目标是在遇到强边缘信息时提高预测性能。本文还提出了一种在采用SbS-DPCM和边缘预测的情况下,保持HEVC分块编码结构的译码过程实现方法。在各种wsi上的实验结果表明,该方法平均比特率节省了7.67%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
HEVC-based lossless compression of Whole Slide pathology images
This paper proposes an HEVC-based method for lossless compression of Whole Slide pathology Images (WSIs). Based on the observation that WSIs usually feature a high number of edges and multidirectional patterns due to the great variety of cellular structures and tissues depicted, we combine the advantages of sample-by-sample differential pulse code modulation (SbS-DPCM) and edge prediction into the intra coding process. The objective is to enhance the prediction performance where strong edge information is encountered. This paper also proposes an implementation of the decoding process that maintains the block-wise coding structure of HEVC when SbS-DPCM and edge prediction are employed. Experimental results on various WSIs show that the proposed method attains average bit-rate savings of 7.67%.
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