SNR-Aware Error Detection for Low-Power Discrete Wavelet Lifting Transform in JPEG 2000

Shih-Hsin Hu, Tung-Yeh Wu, J. Abraham
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引用次数: 1

Abstract

This paper presents a SNR-aware error detection technique for a low-power wavelet lifting transform architecture in JPEG 2000. Power reduction is done by over-scaling the supply voltage (voltage-over-scaling (VOS)). A low-cost SNR-aware detection logic is integrated into the discrete wavelet lifting transform architecture, to check if the image quality degradation caused by the resulting timing errors is acceptable, in order to determine the optimal voltage setting in operating condition at run time. The technique behind the SNR-aware detection logic is the weighted checksum code. It is shown that image quality measured in SNR can be correlated with the image checksum difference. If the image checksum difference is above a certain threshold, the SNR of the image will be below the minimal requirement and image quality will be unacceptable. This novel quality-based error detection is significantly different from traditional error detection schemes which look for exact data equivalence. The technique is useful in exploring optimal voltage configurations for Dynamic Voltage Scaling (DVS).
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JPEG 2000中低功耗离散小波提升变换的信噪比感知误差检测
提出了一种基于JPEG 2000的低功耗小波提升变换体系结构的信噪比感知错误检测技术。功率降低是通过过缩放电源电压(电压过缩放(VOS))来实现的。在离散小波提升变换架构中集成了低成本的信噪比感知检测逻辑,以检查由时序误差引起的图像质量下降是否可接受,从而在运行时确定工作条件下的最佳电压设置。感知信噪比的检测逻辑背后的技术是加权校验和代码。结果表明,用信噪比测量的图像质量可以与图像校验和差相关。如果图像校验和差超过一定阈值,则图像的信噪比将低于最小要求,图像质量将不可接受。这种基于质量的错误检测方法与传统的寻找精确数据等价的错误检测方法有很大的不同。该技术有助于探索动态电压缩放(DVS)的最佳电压配置。
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