{'fraction_non_alphanumeric': 0.02611218568665377, 'fraction_numerical': 0.01160541586073501, 'mean_word_length': 5.052631578947368, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Algorithm with optimum noise suppression for surface profiling by white-light interferometry

We propose an effective algorithm for surface profiling by white-light interferometry based on the so-called partial projection filter, which is a signal estimation technique from a finite number of noisy sampled data. The present authors' group has proposed a fast surface profiling algorithm called the SEST algorithm, in which the world's widest sampling interval of 1.425μm is used. The SEST algorithm, however, has the following problem. That is, when we reduce the sampling interval in order to improve the measurement accuracy, the performance does not increase. In order to solve this problem, the new algorithm has been proposed. That is, when the sampling interval of 1.425μm is used, the new algorithm achieves the same performance as the SEST algorithm. When a narrower sampling interval than 1.425μm is used, the new algorithm improves the accuracy. By computer simulations, the effectiveness of the new algorithm is confirmed.