{'fraction_non_alphanumeric': 0.019417475728155338, 'fraction_numerical': 0.0, 'mean_word_length': 5.444444444444445, '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}}
Low Light Mobile Video Processing

Low contrast and noise remain a barrier to visually pleasing videos in low light conditions. Recording appealing video at concerts, social gatherings, and in security monitoring situations is still an unsolved problem, with many groups searching for a solution. Our target application for this research is finding a better software solution for mobile low-light video, particularly in concert venues. Although mobile image processing products such as Instagram create nice-looking photos after applying overlay filters, these algorithms fail to create nicer low-light image results. Here we explore mobile video enhancement via advanced histogram equalization (HE) and denoising via a novel algorithm which performs probabilistic temporal averaging using a Hidden Markov Model (HMM). Finally we implement these algorithms on a realtime video feed on the iPhone through calculation on the GPU.