{'fraction_non_alphanumeric': 0.01893939393939394, 'fraction_numerical': 0.005050505050505051, 'mean_word_length': 5.5, '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}}
3D building extraction with semi-global matching from stereo pair worldview-2 satellite imageries

Extraction of 3D building information from high resolution satellite imagery is generally carried out manually. Automatic algorithms to extract such information are highly desirable, but have so far met with limited success. Previously, we reported a highly automated method of extracting 3D building information from stereo pair high resolution satellite imagery by using normalized cross correlation (NCC) template matching technique. But the computation of depth is generally prone to error close to surface discontinuity with NCC template matching. In this paper, we present our results of using a semi-global matching (SGM) instead of NCC template matching technique to solve the problem.