Quantifying Light Harshness: Method Automation and Influence of Photographic Light Modifiers

Accurate assessment of light properties is essential and is measured with photometric and colorimetric standardized methods. However, the spatial characteristic of light—harshness—remains difficult to quantify. Building on the authors’ previous work, this study presented a fully automated method for determining light source harshness based on image analysis of cast shadows in a standardized environment. The improved method eliminated the need for manual shadow segmentation by introducing algorithmic noise removal and adaptive smoothing of shadow data. The method was applied to 180 test images comprising 30 combinations of photographic light-shaping attachments (e.g., softboxes, beauty dishes, and snoots) across two light sources (halogen and xenon) and three intensity levels. The results showed that the method was capable of detecting subtle differences in shadow properties and confirmed the influence of geometry, material, and orientation of the light modifiers on harshness. In addition, the results provided quantitative insight into the influence of photographic light modifiers on the original light.

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Publication Details

Journal
Journal of Imaging
Published
2026-03-27
DOI
https://doi.org/10.3390/jimaging12040148
Primary Topic
Skin Protection and Aging
Type
article
Field-Weighted Citation Impact
0.00
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article

Quantifying Light Harshness: Method Automation and Influence of Photographic Light Modifiers

Veronika Štampfl, Jure Ahtik
Journal of Imaging
Skin Protection and Aging
article

Quantifying Light Harshness: Method Automation and Influence of Photographic Light Modifiers

Veronika Štampfl, Jure Ahtik
article en

Abstract

Accurate assessment of light properties is essential and is measured with photometric and colorimetric standardized methods. However, the spatial characteristic of light—harshness—remains difficult to quantify. Building on the authors’ previous work, this study presented a fully automated method for determining light source harshness based on image analysis of cast shadows in a standardized environment. The improved method eliminated the need for manual shadow segmentation by introducing algorithmic noise removal and adaptive smoothing of shadow data. The method was applied to 180 test images comprising 30 combinations of photographic light-shaping attachments (e.g., softboxes, beauty dishes, and snoots) across two light sources (halogen and xenon) and three intensity levels. The results showed that the method was capable of detecting subtle differences in shadow properties and confirmed the influence of geometry, material, and orientation of the light modifiers on harshness. In addition, the results provided quantitative insight into the influence of photographic light modifiers on the original light.

Journal of ImagingVol. 12(4)
Slovenian Academy of Sciences and Arts (SI)
Openalex Percentile: Top 4%
Skin Protection and Aging
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