PrISM-IQA：面向智能手机摄影的实用图像质量评估
PrISM-IQA: Image Quality Assessment Made Practical for Smartphone Photography
AI总结：
提出PrISM-IQA，将智能手机IQA重构为多问题有序诊断，预测每个ISP相关问题的严重等级，支持可操作的ISP调优。
摘要：
现有的智能手机图像质量评估（IQA）方法通常将感知质量简化为单一分数。然而，这种标量形式与实际的图像信号处理器（ISP）调优不太一致，因为工程师必须识别特定的质量问题，估计其严重程度，并确定它们是否可接受或需要干预。在这项工作中，我们引入了一种实用的ISP感知结构化IQA模型（PrISM-IQA），它将智能手机IQA重构为一个多问题有序诊断问题。PrISM-IQA不是回归单个质量分数，而是为每个ISP相关的问题预测一个有序的严重级别——不存在、轻微、严重或关键——涵盖全局图像级伪影和局部内容相关缺陷。为了产生逻辑一致的预测，PrISM-IQA结合了累积有序编码和结构化推理，捕获了问题内部的单调性以及问题间的包含和排斥关系。我们在一个重建的SPAQ基准上评估了PrISM-IQA，该基准标注了53个ISP相关的质量问题，并在一个小规模专家标注的真实世界数据集上进行了评估。实验结果表明，PrISM-IQA在实际问题级诊断中的有效性，通过线性探测揭示了可迁移的感知质量表示，并进一步展示了其预测如何支持可操作且有意义的ISP调优。
英文摘要：
Existing smartphone image quality assessment (IQA) methods commonly reduce perceptual quality to a single score. However, this scalar formulation is poorly aligned with practical image signal processor (ISP) tuning, where engineers must identify specific quality issues, estimate their severities, and determine whether they are acceptable or require intervention. In this work, we introduce a Practical ISP-aware Structured Model for IQA (PrISM-IQA), which reformulates smartphone IQA as a multi-issue ordinal diagnosis problem. Rather than regressing a single quality score, PrISM-IQA predicts an \textit{ordered} severity level -- absent, minor, severe, or critical -- for each ISP-relevant issue, covering both global image-level artifacts and local content-dependent defects. To produce logically consistent predictions, PrISM-IQA combines cumulative ordinal encoding with structured inference that captures within-issue monotonicity as well as cross-issue subsumption and exclusion relations. We evaluate PrISM-IQA on a reconstructed SPAQ benchmark annotated with $53$ ISP-relevant quality issues and on a small-scale expert-annotated real-world dataset. Experimental results demonstrate the effectiveness of PrISM-IQA for practical issue-level diagnosis, reveal transferable perceptual quality representations through linear probing, and further show how its predictions can support actionable and meaningful ISP tuning.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
