Abstract
In this paper, we propose a robust and accurate estimation method for the distance required for digital holography (DH) reconstruction using convolutional neural networks (CNN) in off-axis DH (off-axis DH). This method applies adaptive spectral pooling to reflect distance-related optical characteristics and minimize information loss during the training phase. Simulations and experiments have confirmed that the proposed method is more robust and accurate than search-based or CNN-based distance estimation methods.
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