Department of Computing Science, University of Alberta, Edmonton, Alta., Canada T6G 2H1.
IEEE Trans Image Process. 1999;8(5):717-30. doi: 10.1109/83.760338.
In this paper, we describe a model of the human visual system (HVS) based on the wavelet transform. This model is largely based on a previously proposed model, but has a number of modifications that make it more amenable to potential integration into a wavelet based image compression scheme. These modifications include the use of a separable wavelet transform instead of the cortex transform, the application of a wavelet contrast sensitivity function (CSF), and a simplified definition of subband contrast that allows one to predict the noise visibility directly from the wavelet coefficients. Initially, we outline the luminance, frequency, and masking sensitivities of the HVS and discuss how these can be incorporated into the wavelet transform. We then outline a number of limitations of the wavelet transform as a model of the HVS, namely the lack of translational invariance and poor orientation sensitivity. In order to investigate the efficacy of this wavelet based model, a wavelet visible difference predictor (WVDP) is described. The WVDP is then used to predict visible differences between an original and compressed (or noisy) image. Results are presented to emphasize the limitations of commonly used measures of image quality and to demonstrate the performance of the WVDP. The paper concludes with suggestions on how the WVDP can be used to determine a visually optimal quantization strategy for wavelet coefficients and produce a quantitative measure of image quality.
本文描述了一种基于小波变换的人类视觉系统（HVS）模型。该模型主要基于先前提出的模型，但进行了一些修改，使其更适合潜在的集成到基于小波的图像压缩方案中。这些修改包括使用可分离小波变换代替皮质变换、应用小波对比敏感度函数（CSF）以及简化子带对比度的定义，这使得可以直接从小波系数预测噪声可见度。最初，我们概述了 HVS 的亮度、频率和掩蔽敏感度，并讨论了如何将这些敏感度纳入小波变换。然后，我们概述了小波变换作为 HVS 模型的一些局限性，即缺乏平移不变性和较差的方向敏感性。为了研究基于小波的模型的效果，描述了一种小波可见性差异预测器（WVDP）。然后，使用 WVDP 预测原始图像和压缩（或噪声）图像之间的可见性差异。结果表明，常用的图像质量度量方法存在局限性，并展示了 WVDP 的性能。最后，本文提出了如何使用 WVDP 确定小波系数的视觉最佳量化策略并产生图像质量的定量度量的建议。
