Parvez Sazzad, Z. M.

堀田 裕弘

University of Toyama Repository

In this researchラ weuse stereoscopic techonology for 30 content presentation. Although the technologies required for 30 image are emerging rapidly, the effect of these technologies as well as image compr・essionon the perceptual quality of 30 viewing has not been thoroughly studied. However perceptual 30 image quality is an important evaluation criteria to assess the perfor・manceof 30 imaging systems. Consequentlyラperceivedquality is a great important issue to assess the performance of al 30 imaging applications. Perceived distortion and depth of any stereoscopic images are strongly dependent on the local featuresラsuchas edge, flat and texture. Thereforeラwepropose an no-reference (NIミ） perceptual quality assessment model for JPEG coded stereoscopic images based on segmented local features of artifacts and disparity. The local features information of stereoscopic pair images such as edgeラ日atand texture areas and also the blockiness and zero crossing rate within the block of the images are evaluated for artifacts and disparity in this method. Block diagram of the proposed model is shown in Figm・el(a). In order to verify the performance of our proposed modelラweconduct subjective experiments on our stereo images database (Mean Opinion Score (MOS) scaleラ 1-5ラ seeSubjective test conditions and parameters in Table 1) and divide the database into two parts for training and testing. The training data set consists of five randomly selected stereo images (from the total ten) and al of their different combinations of symmetric/asymmetric coded stereo images. The testing data set consists of the other five stereo images and their al symmetric/asymmetric coded versionsラandalso there is no overlapping between training and testing. The mode：’ s parameters and weighting factors are obtained by the Particle Swarm Optimization (PSO) algorithm with al of our training images. In order to provide quantitative measures on the performance of our proposed NR model, we follow the standard perfomrnnce evaluation procedm・esemployed in the video quality experts group (VQEG) FR-TV Phase I testラwheremainly Pearson linear correlation coefficient (CC), Average absolute prediction error (AAE), Outlier Ratio (OR), and Root mean square prediction error （設MSE)between objective (MOSp) and subjective (MOS) scores were used for evaluation. The evaluation results are summarized in Table 2. It has been observed from Table 2 that the proposed model perfo1111ances for every one of the evaluation metrics are sufficient. It has also been observed from Table 2 and that our proposed model provides sufficient prediction accuracy (higher CC), and sufficient prediction consistency (lower OR). The MOS versus MOS prediction (MOSp) of our proposed model for training and testing data sets is shown in Figure 1 (b). The symbols * and十respectivelyindicate MOSp points for data sets of training and testing. 3. Conclusions We have proposed an NR quality assessment model for JPEG coded ster・eoscopicimages based on segmentation based artifacts and disparity measures. The assessment was performed on different 96 97 combinations of symmetric/ asymmetric coded stereo images of different content. This model can be used for stereoscopic video quality assessment with the incorporation of the temporal dependency between adjacent images of the video. The results show that the model performs quite well over wide range of stereo image content and distortion levels. In order to improve the proposed modelラfutureresearch need to consider more efficient disparity estimation with incorporation of al three color components. 1: I¥fodelヲ然3 MOSp 

QoE向上のための映像コンテンツ提示方法に関する研究

https://toyama.repo.nii.ac.jp/?action=repository_action_common_download&item_id=6909&item_no=1&attribute_id=18&file_no=1

QoE向上のための映像コンテンツ提示方法に関する研究

Abstract

Similar works

Full text

Available Versions

University of Toyama Repository