In the past few years, ever-increasing amounts of image data have been generated by users globally, and these images are routinely stored in cold storage systems in compressed formats. This article investigates the use of approximate storage that leverages the use of cheaper, lower reliability memories that can have higher error rates. Since traditional JPEG-based schemes based on variable-length coding are extremely sensitive to error, the direct use of approximate storage results in severe quality degradation. We propose an error-resilient adaptive-length coding (ALC) scheme that divides all symbols into two classes, based on their frequency of occurrence, where each class has a fixed-length codeword. This provides a balance between the reliability of fixed-length coding schemes, which have a high storage overhead, and the storage-efficiency of Huffman coding schemes, which show high levels of error on low-reliability storage platforms. Further, we use data partitioning to determine which bits are stored in approximate or reliable storage to lower the overall cost of storage. We show that ALC can be used with general non-volatile storage, and can substantially reduce the total cost compared to traditional JPEG-based storage.

中文翻译：

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用于低成本近似存储的图像数据的自适应长度编码

在过去几年中，全球用户生成的图像数据量不断增加，这些图像通常以压缩格式存储在冷存储系统中。本文研究了近似存储的使用，该存储利用了可能具有更高错误率的更便宜、可靠性更低的存储器的使用。由于基于可变长度编码的传统基于 JPEG 的方案对错误极其敏感，因此直接使用近似存储会导致严重的质量下降。我们提出了一种容错自适应长度编码 (ALC) 方案，该方案根据它们的出现频率将所有符号分为两类，其中每一类都有一个固定长度的码字。这在具有高存储开销的固定长度编码方案的可靠性之间提供了平衡，以及霍夫曼编码方案的存储效率，这在低可靠性存储平台上显示出高水平的错误。此外，我们使用数据分区来确定哪些位存储在近似或可靠的存储中，以降低存储的总体成本。我们展示了 ALC 可以与一般的非易失性存储一起使用，并且与传统的基于 JPEG 的存储相比，可以大大降低总成本。