Noise Prism: A Novel Multispectral Visualization Technique

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A novel technique for visualizing multispectral images is proposed. Inspired by how prisms work, our method spreads spectral information over a chromatic noise pattern. This is accomplished by populating the pattern with pixels representing each measurement band at a count proportional to its measured intensity. The method is advantageous because it allows for lightweight encoding and visualization of spectral information while maintaining the color appearance of the stimulus. A four alternative forced choice (4AFC) experiment was conducted to validate the method's information-carrying capacity in displaying metameric stimuli of varying colors and spectral basis functions. The accuracy scores ranged from 100% to 20% (less than chance given the 4AFC task), with many conditions falling somewhere in between at statistically significant intervals. Using this data, color and texture difference metrics can be evaluated and optimized to predict the legibility of the visualization technique.

 

​The graphic below is from a more recent submission on this work, where we collaborated with HP to produce visualizations with different spatial patterns. While the chromatic noise patterns in each column contain exactly the same pixels (they are all noise prism renderings of the spectral power distribution in the bottom row), HP's pattern formation algorithms make it such that similar colors are maximally dispersed (first row) or clustered together (second row), or randomly distributed (third row).​

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Trevor Canham is studying color imaging under the supervision of Michael Brown at York University in Toronto. He recieved a BSc in Motion Picture Science from the Rochester Institute of Technology, and spent several years working in Marcelo Bertalmío's Image Processing for Enhanced Cinematography lab in Barcelona. His interests lie in the interaction between color phenomenology and imaging systems.

 

A link to the CIC publication: https://library.imaging.org/admin/apis/public/api/ist/website/downloadArticle/cic/31/1/34

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