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Progressive Lossy-to-Lossless Compression of DNA Microarray Images

机译:DNA微阵列图像的渐进有损至无损压缩

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摘要

The analysis techniques applied to DNA microarray images are under active development. As new techniques become available, it will be useful to apply them to existing microarray images to obtain more accurate results. The compression of these images can be a useful tool to alleviate the costs associated to their storage and transmission. The recently proposed Relative Quantizer (RQ) coder provides the most competitive lossy compression ratios while introducing only acceptable changes in the images. However, images compressed with the RQ coder can only be reconstructed with a limited quality, determined before compression. In this work, a progressive lossy-to-lossless scheme is presented to solve this problem. First, the regular structure of the RQ intervals is exploited to define a lossy-to-lossless coding algorithm called the Progressive RQ (PRQ) coder. Second, an enhanced version that prioritizes a region of interest, called the PRQ-region of interest (ROI) coder, is described. Experiments indicate that the PRQ coder offers progressivity with lossless and lossy coding performance almost identical to the best techniques in the literature, none of which is progressive. In turn, the PRQ-ROI exhibits very similar lossless coding results with better rate-distortion performance than both the RQ and PRQ coders.
机译:应用于DNA微阵列图像的分析技术正在积极开发中。随着新技术的出现,将其应用于现有的微阵列图像以获得更准确的结果将是有用的。这些图像的压缩可以成为减轻与其存储和传输相关的成本的有用工具。最近提出的相对量化器(RQ)编码器提供了最具竞争力的有损压缩比,同时仅在图像中引入了可接受的变化。但是,使用RQ编码器压缩的图像只能以有限的质量重建,该质量必须在压缩之前确定。在这项工作中,提出了一种渐进的有损无损方案来解决该问题。首先,利用RQ间隔的常规结构来定义一种称为渐进RQ(PRQ)编码器的有损无损编码算法。其次,描述了对优先区域进行优先级排序的增强版本,称为PRQ感兴趣区域(ROI)编码器。实验表明,PRQ编码器具有无损和有损编码性能的渐进性,几乎与文献中的最佳技术相同,但没有一种是渐进的。反过来,与RQ和PRQ编码器相比,PRQ-ROI表现出非常相似的无损编码结果,并且具有更好的速率失真性能。

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