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A comparative test of different compression methods applied to solar images

机译：应用于太阳影像的不同压缩方法的对比测试

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In this work we conduct a comparative study on different data compression methods applied to high resolution images of the solar surface acquired at the Solar Dunn Telescope in Sacramento Peak with the IBIS (Interfero-metric Bidimensional Spectrometer) instrument. Our aim is to pen-form an estimation of the quality, efficiency and workload of the considered computing techniques both in the so-called lossless modality, where in the reconstruction phase there is no loss of information, and in lossy mode, where it should be possible to reach a high compression ratio at the expense of image information. In the latter case we quantify the quality with image analysis conventional methods and more specifically with the reconstruction of physical parameters through standard procedures used in this kind of observations. The considered methods constitute the most frequently adopted image compression procedures in a variety of fields of application; they exploit in different ways the properties of the Discrete Wavelet Transforms often coupled with standard entropy coders or similar coding procedures applied to the different bit planes in order to allow a progressive handling of the original image. In the lossless approach we found that all methods give a compression ratio around 2. For a lossy compression we reached a compression ratio of 8 (equivalent to a 2 bit per pixel) without any perceptual difference between original and reconstructed images, but with effects on the photometric accuracy. We also tested the performance of 3-D lossy methods for the compression of data-cubes. Maintaining the same data degradation level, those methods allows us to gain a 2x in the compression ratio over the 2-D methods.
机译：在这项工作中，我们对不同数据压缩方法进行了比较研究，这些数据压缩方法是使用IBIS（干涉式二维光谱仪）仪器在萨克拉曼多峰的Solar Dunn望远镜获得的高分辨率太阳表面图像上进行的。我们的目标是在所谓的无损模态（在重建阶段不丢失任何信息）和有损模式下，对所考虑的计算技术的质量，效率和工作量进行笔式估算。可能以牺牲图像信息为代价达到高压缩比。在后一种情况下，我们使用常规的图像分析方法来量化质量，更具体地说，通过在这种观测中使用的标准程序来重建物理参数。所考虑的方法构成了各种应用领域中最常采用的图像压缩过程；他们以不同的方式利用离散小波变换的属性，这些属性通常与标准的熵编码器或应用于不同位平面的类似编码过程相结合，以便逐步处理原始图像。在无损方法中，我们发现所有方法的压缩率均约为2。对于有损压缩，我们达到了8的压缩率（相当于每个像素2位），原始图像和重建图像之间没有任何感知差异，但对光度精度。我们还测试了3D有损方法对数据多维数据集的压缩性能。保持相同的数据降级水平，这些方法使我们的压缩率比二维方法高2倍。

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