AI 中文总结
本文针对带宽受限信道下的轮廓编码问题，提出基于锚点优化的解码器引导有损轮廓编码框架，实现了比特率的显著降低并保持了高几何精度。
AI 中文摘要
目标轮廓为图像超分辨率、边缘条件生成、机器视觉等多种接收端视觉任务提供紧凑的结构先验。当这些任务在带宽受限的信道上部署时，发送端将高质量目标轮廓作为结构边信息传输，以指导接收端的重建；为节省带宽，仅传输低质量参考（如下采样图像或基础层重建）。因此，解码器可免费从该参考中提取粗略轮廓，形成编解码器不对称性：精细轮廓必须编码并发送，而解码器端已有免费的粗略版本。现有轮廓编解码器（如JBIG2和链编码）忽略了这种不对称性，它们是无损、对称的，且不提供率失真控制，导致比特率较高。本文提出一种由粗到细的轮廓编码框架，将高质量轮廓建模为解码器可用粗略轮廓的结构化几何优化。编码器沿精细轮廓提取有序锚点，并在失真约束下执行自适应锚点跳过；解码器随后利用粗略先验引导锚点连通性来重建轮廓。该公式实现了具有显式率失真权衡的有损轮廓压缩。实验表明，与无解码器端引导的方法相比，比特率降低54.5%-66.9%，相比JBIG2节省最高达5倍，同时保持了高几何精度。
英文摘要
Object contours serve as compact structural priors for many receiver-side vision tasks such as image super-resolution, edge-conditioned generation, and machine vision. When such tasks are deployed over a bandwidth-limited channel, the sender transmits the high-quality object contour as structural side information to guide reconstruction at the receiver, while-to save bandwidth-only a low-quality reference such as a downsampled image or base-layer reconstruction is delivered. As a result, the decoder can already extract a coarse contour from this reference at no transmission cost, creating an encoder-decoder asymmetry: the fine contour must be coded and sent, yet a free coarse version is available at the decoder. This asymmetry is ignored by existing contour codecs such as JBIG2 and chain coding, which are lossless, symmetric, and offer no rate-distortion control, leading to high bitrates. In this paper, we propose a coarse-to-fine contour coding framework that models a high-quality contour as a structured geometric refinement of the decoder-available coarse contour. The encoder extracts ordered anchors along the fine contour and performs adaptive anchor skipping under a distortion constraint. The decoder then reconstructs the contour by using the coarse prior to guide anchor connectivity. This formulation enables lossy contour compression with an explicit rate-distortion trade-off. Experiments show 54.5%-66.9% bitrate reduction over methods without decoder-side guidance, and up to 5 times savings over JBIG2, while preserving high geometric accuracy.
