论文标题
视觉流连接性预测图像质量的评估
Visual stream connectivity predicts assessments of image quality
论文作者
论文摘要
早期视力的某些生物学机制相对充分理解，但尚未评估它们准确预测和解释人类对图像相似性的判断的能力。从早期视觉的精心研究的简单连通性模式中，我们得出了相似性心理物理学的新型形式化，显示了差异几何形状，该几何形状提供了对感知相似性判断的准确和解释性的说明。然后，通过对人类行为报告的简单回归进一步改善了这些预测，这些预测又用于构建更详细的假设神经连通性模式。两种方法都超过了文献中感知到的图像保真度的成功量度，并提供了相似性知觉的解释原理。
Some biological mechanisms of early vision are comparatively well understood, but they have yet to be evaluated for their ability to accurately predict and explain human judgments of image similarity. From well-studied simple connectivity patterns in early vision, we derive a novel formalization of the psychophysics of similarity, showing the differential geometry that provides accurate and explanatory accounts of perceptual similarity judgments. These predictions then are further improved via simple regression on human behavioral reports, which in turn are used to construct more elaborate hypothesized neural connectivity patterns. Both approaches outperform standard successful measures of perceived image fidelity from the literature, as well as providing explanatory principles of similarity perception.
