Robust Image Registration via Cepstral Analysis

González, Rubén

doi:10.1109/dicta.2011.16

Cited by 6 publications

(1 citation statement)

References 13 publications

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“…Instead of solving the deconvolution, we can alternatively approach the problem by using the cepstrum operation that has been used, e.g., in pitch determination [ 35 ], signal detection and extraction [ 36 ], image registration [ 37 , 38 ], and echo detection and removal [ 39 ]. The cepstrum operator has interesting properties that make it convenient for relative spectra extraction.…”

Section: Methodsmentioning

confidence: 99%

Visible Light Spectrum Extraction from Diffraction Images by Deconvolution and the Cepstrum

et al. 2021

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Accurate color determination in variable lighting conditions is difficult and requires special devices. We considered the task of extracting the visible light spectrum using ordinary camera sensors, to facilitate low-cost color measurements using consumer equipment. The approach uses a diffractive element attached to a standard camera and a computational algorithm for forming the light spectrum from the resulting diffraction images. We present two machine learning algorithms for this task, based on alternative processing pipelines using deconvolution and cepstrum operations, respectively. The proposed methods were trained and evaluated on diffraction images collected using three cameras and three illuminants to demonstrate the generality of the approach, measuring the quality by comparing the recovered spectra against ground truth measurements collected using a hyperspectral camera. We show that the proposed methods are able to reconstruct the spectrum, and, consequently, the color, with fairly good accuracy in all conditions, but the exact accuracy depends on the specific camera and lighting conditions. The testing procedure followed in our experiments suggests a high degree of confidence in the generalizability of our results; the method works well even for a new illuminant not seen in the development phase.

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