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A quality prediction method for stereoscopic images is proposed based on joint structure-texture sparse coding. The goal is to predict the perceptual quality of a stereoscopic image by solving the joint structure-texture sparse coding problem. First, structure and texture dictionaries from a training database are learnt. Then, the quality score for a testing stereoscopic image is predicted by computing...
No-reference stereoscopic image quality assessment (NR-SIQA) is an important research issue in three- dimensional researches. In this paper, a novel NR- SIQA method is proposed by analyzing the detail characteristic of the specific distortion type, and distortion-specific features are extracted to describe the distorted stereoscopic image. The relationship between stereoscopic features and subjective...
Subjective quality evaluation is the basis of quality evaluation of stereoscopic images. As the lack of a public and diverse testing database currently, in this paper, a symmetric stereoscopic images database is built. And then the subjective quality of stereoscopic images is analyzed from two aspects, one is the effects of JPEG, JPEG2000, H.264. The other is the comparisons between symmetric and...
In this paper, an objective assessment model based on three-component weighted structural similarity is presented for stereoscopic image. Since different distortions affect details of stereoscopic image differently, the image is classified into three kinds of regions including edge, smooth and texture regions so that different weights are associated to different regions to assess distorted stereoscopic...
Asymmetric stereoscopic coding can save bitrate and maintain the overall visual quality of stereoscopic perception, so it is an alternative for wireless environment in which the bandwidth is limited. In asymmetric stereoscopic coding, the right-view images are down-sampled to half resolution before coding, while the direction of sampling influences the rate-distortion performance of the asymmetric...
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