Mixed resolution stereoscopic coding exploits the perceptual phenomenon of binocular suppression by encoding each view of a stereo pair at a different resolution. Many investigations have shown that a large reduction in bandwidth can be gained for a relatively small compromise in image quality by this asymmetric representation. However, the viability of such an encoding method depends on the subjective response to viewing such videos at length. While methods for mixed resolution coding have been developed on the presumption of a certain visual fatigue response, none have actually examined it. In this paper, we address this shortcoming in three experiments comparing two methods of binocular suppression processing. The first two experiments reveal subjects' preferences in terms of overall quality between the two methods for short exposures, and the third experiment examines the fatigue resulting from 10-min exposures to mixed resolution encoded videos.

Disparity estimation is a fundamental task in stereo imaging and is a well-studied problem. Recently, methods have been adapted to the video domain where motion is used as a matching criterion to help disambiguate spatially similar candidates. In this paper, we analyze the validity of the underlying assumptions of spatio-temporal disparity estimation, and determine the extent to which motion aids the matching process. By analyzing the error signal for spatio-temporal block matching under the sum of squared differences criterion and treating motion as a stochastic process, we determine the probability of a false match as a function of image features, motion distribution, image noise, and number of frames in the spatio-temporal patch. This performance quantification provides insight into when spatio-temporal matching is most beneficial in terms of the scene and motion, and can be used as a guide to select parameters for stereo matching algorithms. We validate our results through simulation and experiments on stereo video.

Mixed resolution stereoscopic coding is a compression method that reduces the bandwidth of stereo video by transmitting one of the two views at a lower resolution. While the visual system weights the sharper view more heavily resulting in a nearly fully sharp 3D percept, certain applications require, or would benefit from, having both views at full resolution. In this paper, we present a super-resolution method that recovers the lost frequency information in mixed resolution stereo video by exploiting stereo correspondence while emphasizing spatial, temporal, and spectral consistency. Our method is distinguished by operating on video modeled as a 3D Markov network, whereas previous approaches focused solely on images.

Binocular luster is an extremely salient effect seen in 3D when an object in each stereo image exhibits a different contrast polarity relative to the background. The object appears to shimmer, a phenomenon seen in nature and on 3D displays, which the Human Visual System rapidly detects. This binocular luster is also induced by compression of stereo imagery where corresponding blocks are quantized to different values. In this paper, we discuss the psychovisual background of binocular luster, introduce the "shine" artifact induced by compression, and present an algorithm for detection and removal of shine from JPEG compressed stereo images without introducing additional bitrate.

From a rectified stereo image pair, the task of view synthesis is to generate images from any viewpoint along the baseline. The main difficulty of the problem is how to fill occluded regions. In this pa per, we present a new method for view synthesis that is both fast and accurate. Occlusions are filled using color and disparity information to produce consistent pixel estimates. Results are comparable to current state-of-the-art methods in terms of objective measures while computation time is drastically reduced. This work has applications in free-viewpoint television, angular scalability for 3D video coding/decoding, and stereo-to-multiview conversion.

In this paper, we propose a novel method that uses coordinate alignment and background pixel extraction to synthesize highly accurate and spatially consistent intermediate views from a pair of stereo images and disparity maps. In contrast to the traditional depth image-based rendering (DIBR) method, where useful background pixels are discarded in the warping process, the proposed method extracts these background pixels and uses them as candidates for an exemplar-based image in-painting technique (EBIIT) to synthesize realistic content in disocclusion regions. Our second contribution is a coordinate alignment algorithm that aligns disocclusion regions in each view together and simultaneously synthesizes disocclusion regions to enhance spatial consistency across all virtual views. The proposed method compares favorably in quantitative measures to those obtained by existing techniques and has superior potential for stereo-to-multiview conversion.