Applied Optics · 1994 · 366 citations · 20 references
Natural SciencesBiomedical EngineeringComputer VisionDiagnostic ImagingDigital ImagingDigital Image ProcessingDigital Signal ProcessingImage ProcessingImage ReconstructionImagingSignal ProcessingImage Reconstruction AlgorithmsModel-based Image ReconstructionPhase ReconstructionPhase RetrievalRandom NoiseReconstruction AlgorithmsSignal Reconstruction
The Yang–Gu algorithm generalizes Gerchberg–Saxton and effectively solves amplitude–phase retrieval in both unitary and nonunitary linear transform systems, reducing to the same algorithm under unitary conditions. The study compares the Gerchberg–Saxton and Yang–Gu algorithms for reconstructing model images from two intensity measurements in a nonunitary transform system. The authors reconstruct images from two intensity measurements, examining performance under random noise corruption. Simulations demonstrate that the Yang–Gu algorithm is relatively noise‑insensitive and consistently yields highly accurate phase recovery.
A detailed comparison of the original Gerchberg–Saxton and the Yang–Gu algorithms for the reconstruction of model images from two intensity measurements in a nonunitary transform system is presented. The Yang–Gu algorithm is a generalization of the Gerchberg–Saxton algorithm and is effective in solving the general amplitude–phase-retrieval problem in any linear unitary or nonunitary transform system. For a unitary transform system the Yang–Gu algorithm is identical to the Gerchberg–Saxton algorithm. The reconstruction of images from data corrupted with random noise is also investigated. The simulation results show that the Yang–Gu algorithm is relatively insensitive to the presence of noise in data. In all cases studied the Yang–Gu algorithm always resulted in a highly accurate recovered phase.
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Phase retrieval algorithms: a comparison
James R. Fienup · Applied Optics · 1982 · 5.6K citations
Super-resolution through Error Energy Reduction
R.W. Gerchberg · Optica Acta International Journal of Optics · 1974 · 988 citations
Computing, Computer Science, Physics +11