DNA微阵列图像压缩研究进展

Miguel Hernández-Cabronero, Ian Blanes, J. Serra-Sagristà, M. Marcellin
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引用次数: 5

摘要

我们回顾了DNA微阵列图像压缩技术的最新进展。首先,我们描述了文献中发表的最相关的方法,并根据每种方法做出贡献的典型图像压缩过程的阶段对它们进行了分类。然后,我们总结了这些特定图像压缩方案的压缩结果。在本文进行的一组实验中,我们获得了几种流行的图像编码技术的结果,包括最新的编码标准。基于预测的方案CALIC和JPEG-LS,以及使用零小波分解级别的JPEG2000是性能最好的标准压缩器,但都优于最佳的微阵列特定技术,Battiato基于cnn的方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review of DNA Microarray Image Compression
We review the state of the art in DNA micro array image compression. First, we describe the most relevant approaches published in the literature and classify them according to the stage of the typical image compression process where each approach makes its contribution. We then summarize the compression results reported for these specific-specific image compression schemes. In a set of experiments conducted for this paper, we obtain results for several popular image coding techniques, including the most recent coding standards. Prediction-based schemes CALIC and JPEG-LS, and JPEG2000 using zero wavelet decomposition levels are the best performing standard compressors, but are all outperformed by the best micro array-specific technique, Battiato's CNN-based scheme.
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