计算机工程2026，Vol.52Issue(6)：68-79,12.DOI:10.19678/j.issn.1000-3428.0253191
基于顺序分级与数据偏置修正优化的二阶段超分辨率量化方案
A Two-Phase Super-Resolution Quantization Scheme Optimized by Sequential Grading and Data Bias Correction
摘要
Abstract
Model quantization technology effectively reduces model storage and computational overhead by mapping high-precision floating-point data to low-bit discrete spaces.A core focus of model quantization research is how to rationally account for the characteristics of parameter distributions to construct superior mapping schemes.Existing Post-Training Quantization(PTQ)schemes nearly universally assume that the data distribution of non-activation layers follows a symmetric bell-shaped curve,but overlook the fact that small biases introduced by the model's activation layers and inputs induce distributional asymmetry.Consequently,the resulting quantization mapping is skewed to one side due to this subtle asymmetry,leading to significant approximation loss.This paper investigates quantization schemes for image Super-Resolution(SR)and proposes improvements to the widely recognized two-stage PTQ scheme.First,the max-min-based equal partitioning employed in the pre-search for quantization bounds is modified to a sorting-based non-uniform partitioning approach.Second,a bias term is introduced during the pseudo-quantization process,where a portion of the data and its mean are adaptively shifted to mitigate estimation loss caused by data bias.The improved scheme outperforms the original counterpart across all performance metrics while maintaining comparable high compression ratio and acceleration ratio-compared to the original SwinIR-light model,it reduces the parameter count by more than 60％and accelerates the SR process by more than 3 times.关键词
模型量化/图像超分辨率/数据偏移/后训练量化/排序/偏置Key words
model quantization/image Super-Resolution(SR)/data bias/Post-Training Quantization(PTQ)/sorting/bias分类
信息技术与安全科学引用本文复制引用
郝亮,苏博何俊,王京华,徐勇..基于顺序分级与数据偏置修正优化的二阶段超分辨率量化方案[J].计算机工程,2026,52(6):68-79,12.基金项目
河钢集团重点科技项目(HG2025129) （HG2025129）
深圳市技术攻关项目(JSGG20220831104402004). （JSGG20220831104402004）
