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商业步行街道是高度人工化的视觉廊道,随着商业的不断聚集,其内容趋于更加丰富和多样化。为了更好地进行街道景观的设计和评价,需要提出一种可以衡量景观视觉复杂性的量化指标。本文引入视觉熵来衡量商业步行街道景观视觉的复杂性。首先借助数字图像处理技术在MATLAB平台上实现视觉熵的数据计算,而后用SPSS分析软件对1组被试(105人)的评价结论与视觉熵值进行相关分析。分析结果认为视觉熵值与评价结论之间存在显著相关关系,视觉熵可以作为衡量商业步行街道景观视觉复杂性的量化指标。
Commercial pedestrian streets are highly artificial visual corridors, whose content tends to be richer and more diverse as business continues to gather. In order to better design and evaluate the street landscape, we need to present a quantitative index that can measure the complexity of landscape visual. This paper introduces visual entropy to measure the complexity of landscape visual in commercial pedestrian streets. Firstly, visual entropy data was calculated on the MATLAB platform by means of digital image processing technology, and then SPSS analysis software was used to correlate the evaluation conclusion of one set of subjects (105 persons) with visual entropy. The results show that there is a significant correlation between visual entropy and evaluation conclusion, and visual entropy can be used as a quantitative index to measure the visual complexity of commercial pedestrian street landscape.