{'fraction_non_alphanumeric': 0.015473887814313346, 'fraction_numerical': 0.0, 'mean_word_length': 5.234939759036145, '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}}
An infrared dim and small target detection method based on fractional differential

Dim target detection in infrared image with complex background and low signal-ratio(SCR) is a significant and difficult task in the infrared target tracking system, this paper proposes a real time dim target detection algorithm based on fractional differential algorithm. An improved top-hat operator is adopted to process the original image which can restrain the background well. After we enhance the target based on a fractional differential algorithm, to further eliminate residual clutter and gain the saliency map, we process the enhanced image with a spectral residual method. The pipeline filter can reduce the false alarm rate further at last. The algorithm is tested on three different infrared image sequences, and the experimental results show that the algorithm is efficient and robust, which would be very useful for infrared dim small target detection. In particular, the proposed method can improve the SNR of the image significantly.