Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

3D scanning of cultural heritage with consumer depth cameras

Three dimensional reconstruction of cultural heritage objects is an expensive and time-consuming process. Recent consumer real-time depth acquisition devices, like Microsoft Kinect, allow very fast and simple acquisition of 3D views. However 3D scanning with such devices is a challenging task due to the limited accuracy and reliability of the acquired data. This paper introduces a 3D reconstruction pipeline suited to use consumer depth cameras as hand-held scanners for cultural heritage objects. Several new contributions have been made to achieve this result. They include an ad-hoc filtering scheme that exploits the model of the error on the acquired data and a novel algorithm for the extraction of salient points exploiting both depth and color data. Then the salient points are used within a modified version of the ICP algorithm that exploits both geometry and color distances to precisely align the views even when geometry information is not sufficient to constrain the registration. The proposed method, although applicable to generic scenes, has been tuned to the acquisition of sculptures and in this connection its performance is rather interesting as the experimental results indicate

Depth mapping of integral images through viewpoint image extraction with a hybrid disparity analysis algorithm

Integral imaging is a technique capable of displaying 3–D images with continuous parallax in full natural color. It is one of the most promising methods for producing smooth 3–D images. Extracting depth information from integral image has various applications ranging from remote inspection, robotic vision, medical imaging, virtual reality, to content-based image coding and manipulation for integral imaging based 3–D TV. This paper presents a method of generating a depth map from unidirectional integral images through viewpoint image extraction and using a hybrid disparity analysis algorithm combining multi-baseline, neighbourhood constraint and relaxation strategies. It is shown that a depth map having few areas of uncertainty can be obtained from both computer and photographically generated integral images using this approach. The acceptable depth maps can be achieved from photographic captured integral images containing complicated object scene