Utilizing <b>Photoelectromagnetic</b> Degradation <b>Imagery </b>for Enhanced Forensic Assessment

Photoelectromagnetic (PEM) imagery offers advanced capabilities for analyzing digital image degradation by capturing and visualizing electromagnetic spectrum characteristics. This paper presents a technique that utilizes repeated photo degradation to reveal hidden aspects of the electromagnetic (light) spectrum, such as refraction, direction, intensity, and light type. The method provides new insights into light behavior in digital media, distinguishing between artificial and natural light sources. PEM imagery, therefore, supports both image quality analysis and comprehensive light spectrum assessment, enhancing our understanding of image compression’s impact on visual fidelity and spectrum visibility.

Publication Details

Journal
Figshare
Published
2024-10-26
DOI
https://doi.org/10.6084/m9.figshare.27308148
Primary Topic
Legal and Regulatory Analysis
Type
article
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Utilizing Photoelectromagnetic Degradation Imagery for Enhanced Forensic Assessment

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Legal and Regulatory Analysis
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Utilizing Photoelectromagnetic Degradation Imagery for Enhanced Forensic Assessment

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Abstract

Photoelectromagnetic (PEM) imagery offers advanced capabilities for analyzing digital image degradation by capturing and visualizing electromagnetic spectrum characteristics. This paper presents a technique that utilizes repeated photo degradation to reveal hidden aspects of the electromagnetic (light) spectrum, such as refraction, direction, intensity, and light type. The method provides new insights into light behavior in digital media, distinguishing between artificial and natural light sources. PEM imagery, therefore, supports both image quality analysis and comprehensive light spectrum assessment, enhancing our understanding of image compression’s impact on visual fidelity and spectrum visibility.

Figshare
Openalex Percentile: Top 46%
Legal and Regulatory Analysis
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Utilizing <b>Photoelectromagnetic</b> Degradation <b>Imagery </b>for Enhanced Forensic Assessment · Figshare (2024) | TGRS Research Map | TGRS