{'fraction_non_alphanumeric': 0.02526395173453997, 'fraction_numerical': 0.003393665158371041, 'mean_word_length': 5.502450980392157, '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}}
Stereoscopic Image Processing

1. INTRODUCTION Static images and dynamic image sequences are the projection of time-varying three-dimensional real world scenes onto a two-dimensional plane. As a result of this planar projection, depth information of objects in the scene is generally lost. Only by cues such as shadow, relative size and sharpness, interposition, perspective factors, and object motion, we can form an impression of the depth organization of the real world scene. In a wide variety of image processing applications, explicit depth information is required in addition to the scene's gray value information (representing intensities, color, densities, etc.) [Dhond89,Horn86,Marr82]. Examples of such applications are found in 3-D vision (robot vision, photogrammetry, remote sensing systems), in medical imaging (computer tomography, magnetic resonance imaging, microsurgery), in remote handling of objects for instance in inaccessible industrial plants or in space exploration, and in visual communications aiming at virtual presence (conferencing, education, virtual travel and shopping, virtual reality). In each of these cases, depth information is essential for accurate image analysis or for enhancing the realism. In remote sensing the terrain's elevation needs to be accurately determined for map production, in remote handling an operator needs to have precise knowledge of the three-dimensional organization of the area to avoid collisions and misplacements, and in visual communications the quality and ease of information exchange significantly benefits from the high degree of realism provided by scenes with depth. Depth in real world scenes can be explicitly measured by a number of range sensing devices such as by laser range sensors, by structured light or by ultrasound. Often it is, however, undesirable or unnecessary to have separate systems for acquiring the intensity and the depth information because of the relative low resolution of the range sensing devices and because of the question of how to fuse information from different type of sensors. An often used alternative to acquire depth information is to record the real world scene from different perspective viewpoints. In this way multiple images or (preferably time-synchronized) image sequences are obtained that implicitly contain the scene's depth information. In the case that multiple views of a single scene are taken without any specific relation between the spatial positions of the viewpoints, such recordings are called multiview images. Generally speaking, when recordings are obtained from an increasing number of different viewpoints, the 3-D