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Abstract

Iterative algorithms are currently the most effective approaches to solving a number of difficult signal reconstruction and recovery problems, and all of these algorithms suffer from stagnation and computational complexity. We propose a new multiresolution iterative approach that employs the concept of a multiresolution pyramid. This method attempts to solve the problem of image reconstruction from the measurement of the image’s Fourier modulus by decomposing the prob- lem onto different resolution grids, which enables the iterative algorithm to avoid stagnation by providing a better initial guess and enabling a higher likelihood of arriving at a global minimum while dramatically reducing the computational cost. Results on both synthetic and real-world images are shown; a performance comparison with the direct iterative algorithm demonstrates the effectiveness of our approach in terms of convergence, robustness and computational efficiency.

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APA

Rabadi, W. a. (1996). Iterative multiresolution algorithm for image reconstruction from the magnitude of its Fourier transform. Optical Engineering, 35(4), 1015. https://doi.org/10.1117/1.600718

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