{'fraction_non_alphanumeric': 0.01621923937360179, 'fraction_numerical': 0.0, 'mean_word_length': 5.802281368821292, '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}}
A regional density distribution based wide dynamic range algorithm for infrared camera systems

Forward Looking InfraRed (FLIR) imaging system has been widely used for both military and civilian purposes. Military applications include target acquisition and tracking, night vision system. Civilian applications include thermal efficiency analysis, short-ranged wireless communication, weather forecasting and other various applications. The dynamic range of FLIR imaging system is larger than one of commercial display. Generally, auto gain controlling and contrast enhancement algorithm are applied to FLIR imaging system. In IR imaging system, histogram equalization and plateau equalization is generally used for contrast enhancement. However, they have no solution about the excessive enhancing when luminance histogram has been distributed in specific narrow region. In this paper, we proposed a Regional Density Distribution based Wide Dynamic Range algorithm for Infrared Camera Systems. Depending on the way of implementation, the result of WDR is quite different. Our approach is single frame type WDR algorithm for enhancing the contrast of both dark and white detail without loss of bins of histogram with real-time processing. The significant change in luminance caused by conventional contrast enhancement methods may introduce luminance saturation and failure in object tracking. Proposed method guarantees both the effective enhancing in contrast and successive object tracking. Moreover, since proposed method does not using multiple images on WDR, computation complexity might be significantly reduced in software / hardware implementation. The experimental results show that proposed method has better performance compared with conventional Contrast enhancement methods.