{'fraction_non_alphanumeric': 0.015810276679841896, 'fraction_numerical': 0.0, 'mean_word_length': 5.452229299363057, '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 Improved Method for Extraction of Intrinsic Images from a Single Image with Integrated Measures

Intrinsic images, including reflectance and illumination images, are desirable to many vision applications. An improved method for extracting intrinsic images from a single color image with integrated measures is presented. To start with, the input image convolves with a predefined set of derivative filters. The pixels of filtered images are then classified into reflectance-related or illumination-related using a criterion measure comprising three measures of filtered pixels calculated from the input image. The three measures are denoted as chromatic measure, blur measure, and intensity measure. Finally, the intrinsic images of the input image can be computed from the classification results of the filtered images. Both synthetic and real images have been utilized in our experiments. The results demonstrated that the proposed technique can effectively extract the intrinsic images from a single image.