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Context-Free Decoding of High-Density 2D Bit Fields with Alias Disambiguation

机译:具有别名消歧的高密度2D比特字段的无上下文解码

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摘要

PROBLEM: Conventional decoding techniques tend to operate exclusively in the space domain and often rely on code-specific “finder features,” ECC, high-resolution imaging, image resampling (a “lossy” process), encoded data “clues” and low code density relative to image resolution (see EASY examples below). This limits the amount of information that can be reliably encoded into a given area. RESEARCH OBJECTIVES: Recover randomly-oriented 2D bit fields without resampling, without reliance on finder features, and without dependency on encoding or data content. Decode at image densities that produce aliasing of primary grid frequencies – alias disambiguation (see HARD example below). Provide linear code density improvement of 1.5:1 to 2:1 over conventional techniques, resulting in an increase in data density per unit area of 2.25:1 to 4:1.
机译:问题:常规解码技术倾向于仅在空间域中运行,并且通常依赖于特定于代码的“查找器功能”,ECC,高分辨率成像,图像重采样(“有损”过程),编码数据“线索”和低代码相对于图像分辨率的密度(请参见下面的EASY示例)。这限制了可以可靠地编码到给定区域中的信息量。研究目的:恢复随机定向的2D位域,而无需重新采样,不依赖查找器功能并且不依赖于编码或数据内容。以产生主栅格频率混叠的图像密度进行解码-混叠消除歧义(请参见下面的HARD示例)。与传统技术相比,可将线性代码密度提高1.5:1至2:1,从而使每单位面积的数据密度增加2.25:1至4:1。

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