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On the Use of JPEG 2000 to Achieve Minimum L-Infinity Error when Specifying a Compression Ratio

机译:在使用JPEG 2000时,在指定压缩比时实现最小L-Infinity错误

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In this paper, minimization of the maximum absolute error (MAE) is achieved under a JPEG 2000 framework when a compression ratio is specified. The process is founded on our recent JPEG 2000-based algorithm for minimizing bit rate for a desired MAE using a residual coding approach [1-3] that uses the EBCOT coder separately. This type of algorithm uses the lossy and lossless capabilities of JPEG 2000 to achieve a desired MAE or a desired total bit rate. The technique to achieve the lowest MAE possible for a specified average bit rate is developed here for application to 3-D scientific data sets. Lossy compression is applied to the original data, while lossless compression is employed on the quantized residuals (the difference between the original and the lossy decompressed data). The lowest MAE is achieved by optimizing the allocation of the desired total bit rate between the two contributing rates corresponding to the lossy and the lossless compression steps. The methodology for achieving minimum MAE and results for 3-D meteorological data are presented here.
机译:在本文中,当指定压缩比时,在JPEG 2000框架下实现最大绝对误差(MAE)的最小化。该过程建立在我们最近的JPEG 2000的算法上,用于使用剩余编码方法[1-3]单独使用使用EBCot编码器的剩余编码方法来最小化所需MAE的比特率。这种类型的算法使用JPEG 2000的损耗和无损能力来实现所需的MAE或期望的总比特率。实现指定平均比特率可能的最低MAE的技术在此开发用于应用于3-D科学数据集。有损压缩应用于原始数据,而在量化残差上采用无损压缩(原始和损耗的减压数据之间的差异)。通过优化与损耗和无损压缩步骤相对应的两种贡献率之间的所需总比特率的分配来实现最低的MAE。这里提出了实现最小MAE的方法和3-D气象数据的结果。

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