Reconstruction of Signal using Interpolation
Principal Moments of Area
Linear Approximation in Frequency Domain
Residuals and Least-Squares Property
Linear Approximation in Time Domain
Extraction: Partition and Distribution Coefficients
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Resolving Water, Proteins, and Lipids from In Vivo Confocal Raman Spectra of Stratum Corneum through a Chemometric Approach
Published on: September 26, 2019
Takahiro Ogawa1, Miki Haseyama
1Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan. ogawa@lmd.ist.hokudai.ac.jp
This study introduces a novel missing intensity interpolation method using kernel principal component analysis (PCA) and projection onto convex sets (POCS). The technique effectively reconstructs images with arbitrary missing areas, improving texture restoration and image quality.
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