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Statisically lossless image compression for CR and DR

机译:统计上无损的CR和DR图像压缩

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Abstract: This paper proposes an image compression algorithm that can improve the compression efficiency for digital projection radiographs over current lossless JPEG by utilizing a quantization companding function and a new lossless image compression standard called JPEG-LS. The companding and compression processes can also be augmented by a pre- processing step to first segment the foreground portions of the image and then substitute the foreground pixel values with a uniform code value. The quantization companding function approach is based on a theory that relates the onset of distortion to changes in the second-order statistics in an image. By choosing an appropriate companding function, the properties of the second-order statistics can be retained to within an insignificant error, and the companded image can then be lossless compressed using JPEG-LS; we call the reconstructed image statistically lossless. The approach offers a theoretical basis supporting the integrity of the compressed-reconstructed data relative to the original image, while providing a modest level of compression efficiency. This intermediate level of compression could help to increase the conform level for radiologists that do not currently utilize lossy compression and may also have benefits form a medico-legal perspective. !13
机译:摘要:本文提出了一种图像压缩算法,该算法可通过利用量化压扩函数和一种称为JPEG-LS的新无损图像压缩标准来提高当前无损JPEG上数字投影X射线照片的压缩效率。压扩和压缩处理还可以通过预处理步骤来增强,以首先分割图像的前景部分,然后用统一的代码值替换前景像素值。量化压扩函数方法基于将失真的发生与图像中二阶统计量的变化相关的理论。通过选择合适的压扩函数,可以将二阶统计量的属性保留在很小的误差范围内,然后可以使用JPEG-LS对压缩后的图像进行无损压缩;我们称重建图像在统计上是无损的。该方法提供了理论基础,支持相对于原始图像的压缩重建数据的完整性,同时提供适度的压缩效率。对于目前不使用有损压缩的放射科医生来说,这种中等的压缩水平可能有助于提高放射医师的顺应性水平,并且从医学法律角度来看也可能有好处。 !13

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