A methodology for contrast enhancement in laser speckle imaging : applications in Phaseolus vulgaris and Lactuca sativa seed bioactivity
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Show full item recordAuthor(s)
Herrera, Edher Zacarias
; Mello Román, Julio César
; Florentín Báez, Joel Miguelangel; Palacios Bogarín, José Luis; Mereles Menesse, Gustavo Eduardo; Jara Ávalos, Jorge Antonio; Franco, Marcos; Méndez, Fernando José
; García Torres, Miguel; Vázquez Noguera, José Luis
; Pérez Estigarribia, Pastor Enmanuel
; Grillo, Sebastián Alberto
; Legal Ayala, Horacio Andrés
Date of publishing
2025-11-27Type of publication
info:eu-repo/semantics/articleSubject(s)
Contrast enhancement
GAVD
Laser Speckle Imaging (LSI)
Phaseolus vulgaris (SP)
Seed Lactuca sativa (SL)
Speckle patterns
GAVD
Laser Speckle Imaging (LSI)
Phaseolus vulgaris (SP)
Seed Lactuca sativa (SL)
Speckle patterns
Abstract
Laser Speckle Imaging (LSI) is a non-invasive optical technique used to assess biological activity by detecting dynamic variations in speckle patterns. These patterns exhibit statistical symmetry in static regions, while biological activity induces symmetry breaking that can be captured through the Graphic Absolute Value of Differences (GAVD), producing the activity map IGAVD. This work evaluates the effect of four contrast enhancement algorithms: Histogram Equalization (HE), Contrast Limited Adaptive Histogram Equalization (CLAHE), Multiscale Morphological Contrast Enhancement (MMCE), and Multiscale Top-Hat Transform with an Open-Close Close-Open (OCCO) filter, applied to intermediate LSI images, with the final activity map used for quantitative evaluation. Each method represents a distinct enhancement paradigm: HE and CLAHE are histogram-based techniques for global and local contrast adjustment, whereas MMCE and OCCO-MTH are morphological approaches that emphasize structural preservation and local detail enhancement. The dataset consisted of images of Phaseolus vulgaris (SP) and Lactuca sativa (SL) seeds. Evaluation was conducted through expert visual inspection and quantitative analysis using contrast, entropy, spatial frequency (SF), structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and contrast improvement ratio (CIR). All metrics were computed on IGAVD activity maps, which reflect bioactivity through the disruption of statistical symmetry. Non-parametric statistical tests (Friedman, aligned Friedman, and Quade) revealed that CLAHE and MMCE significantly improved image quality compared to the original images (p < 0.05). Among the evaluated algorithms, CLAHE increased global contrast by approximately 25% and entropy by 6% relative to the original speckle frames, enhancing the visibility of bioactive regions. MMCE achieved the highest bioactivity contrast ratio (CIR = 0.64), while OCCO-MTH provided the best structural fidelity (SSIM = 0.91) and noise suppression (PSNR = 30.7 dB). These results demonstrate that suitable contrast enhancement can substantially improve the interpretability of LSI activity maps without altering acquisition hardware. This finding is particularly relevant for experimental applications aiming to maximize information quality without modifying acquisition hardware.






