Patent · US Active

System and method for training of noise model using noisy signal pairs

US12394024B2 · kind B2 · utility

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6References
20Claims
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Key dates

Filing dateNov 10, 2022
Grant dateAug 19, 2025
Priority date
Expiry dateNov 22, 2043

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06T2207/20084
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

A noise model is iteratively trained to simulate introduction of noise by a capture device, by use of a denoiser and a training data set of pairs of noisy signals. First and second noisy signals of each pair are independently sampled by the capture device from source information corresponding to the pair. Each iteration of training obtains first and second denoised signals from respective noisy signals, then optimizes at least one loss function which sums first and second terms to train both the noise model and the denoiser, where the first term is based on the first denoised signal and the second noisy signal, and the second term is based on the second denoised signal and the first noisy signal. By using noisy samples, the complexities of obtaining “clean” signals are avoided. By using “cross-sample” loss functions, convergence on undesired training results is avoided without complex regularization.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.