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Coding of nonsmooth images in lossless manner

机译:以无损方式编码不平滑的图像

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Abstract: The considerations on effective lossless coding of non- smooth images are presented in this paper. Selection of the best not time consuming coding algorithms for a class of medical images is made a matter rather than completely new concept introduction. As a reference we consider the most efficient CALIC method, new lossless standard JPEG-LS and BTPC algorithm. Different methods of image scanning and 1D encoding are tested. Simple raster-scan data ordering followed by n-order arithmetic coding gives significant encoding efficiency for ultrasound images considered as a representative of the non-smooth image class. The lower bit rates could be achieved by additional statistical modeling in arithmetic coder based on the 12th order context quantized to one-order context. Therefore number of states in conditional probability model is reduced to overcome dilution problem. Finally, improved compression efficiency of non-smooth images in comparison to state-of-the-art CALIC algorithm is achieved. Average bit rate value is diminished over 30 percent. To compress smooth images the linear prediction scheme is incorporated for entire data redundancy reduction. The same model based on linear combination of adjacent pixels is used in prediction and entropy encoding steps. For smooth images our method performance is comparable to JPEG-LS and slightly worse than CALIC. !11
机译:摘要:本文提出了对有效的非光滑图像无损编码的考虑。为一类医学图像选择最佳而不费时的编码算法是一个问题,而不是全新的概念介绍。作为参考,我们考虑了最有效的CALIC方法,新的无损标准JPEG-LS和BTPC算法。测试了图像扫描和一维编码的不同方法。简单的光栅扫描数据排序后再进行n阶算术编码,可为被视为非平滑图像类的代表的超声图像提供显着的编码效率。较低的比特率可以通过在算术编码器中基于量化为一阶上下文的12阶上下文进行额外的统计建模来实现。因此,减少了条件概率模型中的状态数以克服稀释问题。最后,与最新的CALIC算法相比,可以提高非平滑图像的压缩效率。平均比特率值降低了30%以上。为了压缩平滑图像,为了减少整个数据的冗余,并入了线性预测方案。在预测和熵编码步骤中使用基于相邻像素的线性组合的相同模型。对于平滑图像,我们的方法性能可与JPEG-LS相媲美,但略逊于CALIC。 !11

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