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High-dynamic-range still-image encoding in JPEG 2000

机译:JPEG 2000中的高动态范围静止图像编码

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The raw size of a high-dynamic-range (HDR) image brings about problems in storage and transmission. Many bytes are wasted in data redundancy and perceptually unimportant information. To address this problem, researchers have proposed some preliminary algorithms to compress the data, like RGBE/XYZE, OpenEXR, LogLuv, and so on. HDR images can have a dynamic range of more than four orders of magnitude while conventional 8-bit images retain only two orders of magnitude of the dynamic range. This distinction between an HDR image and a conventional image leads to difficulties in using most existing image compressors. JPEG 2000 supports up to 16-bit integer data, so it can already provide image compression for most HDR images. In this article, we propose a JPEG 2000-based lossy image compression scheme for HDR images of all dynamic ranges. We show how to fit HDR encoding into a JPEG 2000 encoder to meet the HDR encoding requirement. To achieve the goal of minimum error in the logarithm domain, we map the logarithm of each pixel value into integer values and then send the results to a JPEG 2000 encoder. Our approach is basically a wavelet-based HDR still-image encoding method.
机译:高动态范围(HDR)图像的原始尺寸在存储和传输中带来了问题。许多字节浪费在数据冗余和感知上不重要的信息上。为了解决这个问题,研究人员提出了一些初步的算法来压缩数据,例如RGBE / XYZE,OpenEXR,LogLuv等。 HDR图像的动态范围可以超过四个数量级,而常规的8位图像仅保留动态范围的两个数量级。 HDR图像和常规图像之间的这种区别导致在使用大多数现有图像压缩器时遇到困难。 JPEG 2000支持最多16位整数数据,因此它已经可以为大多数HDR图像提供图像压缩。在本文中,我们为所有动态范围的HDR图像提出了一种基于JPEG 2000的有损图像压缩方案。我们展示了如何将HDR编码适合JPEG 2000编码器,以满足HDR编码要求。为了实现对数域中最小误差的目标,我们将每个像素值的对数映射为整数值,然后将结果发送到JPEG 2000编码器。我们的方法基本上是基于小波的HDR静止图像编码方法。

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