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3D CG Image Quality Metrics Including the Coded Degradation by Regions with 8 Viewpoints Parallax Barrier Method
Abstract
Until now, there have been many studies about image quality for multi-viewpoint 3D images. Particularly, as represented by ROI (Region Of Interest), it becomes important that users are interested in or focused on what region or area. Also, in the multi-viewpoint 3D still images, it's not clearly that users focused on objects or background in their images since there are many viewpoints. Until now, there were the case studies considered about the coded degradation for 2D videos, binocular 3D videos. However, there were not case studies for multi-viewpoint 3D, and their results were not cleared. In this paper, we demonstrated image quality assessment in the case of occurring the coded degradation for objects or background region with 8 viewpoints parallax barrier method, and we analyzed experimental results.
... On the other hand, as represented by ROI, it is important that we know where the assessors are interested in the part of the 3D image when they see the 3D image, and previously, there were many studies about the image quality evaluation for the look-at point. In the past, we verified by carrying out the subjective quality evaluation experiment of 3D CG images in the case of the coded degradation by regions with 8 viewpoints parallax barrier method [8], [9]. As a result, we can see that evaluation value in the case of the coded degradation for the object region of 3D CG image, which is affected by types of contents. ...
Previously, there were many studies about the image quality evaluation based on S-CIELAB color space including the spatial frequency characteristics of human vision system. It is not obvious to what extent was accepted for the assessors when we see the 3D image which the luminance change may affect the stereoscopic effect and assessment generally. Similarly, it is not obvious when we see the multi-view 3D image. As represented by ROI (Region Of Interest), it is important where the assessors are interested in or focused on the part of the 3D image when they see the 3D image. Seeing the content creators, we consider that they create expecting for users to focus on the object region than the background region. Therefore, we considered that we need to verify by subjective evaluation experiment to what extent was not interfered with regard to the contrast enhancement and the coded degradation. Furthermore, we consider that we are able to become to carry out the general evaluation for the luminance component using both S-CIELAB color space and CIEDE2000, in addition to the subjective evaluation. In this paper, first, we carried out the subjective evaluation experiment for the contrast enhancement of the object region in an image with 8 viewpoints parallax barrier method. Next, we analyzed their results statistically using a Support Vector Machine (SVM). On the other hand, we evaluated objectively about luminance value measurement using CIEDE2000 in S-CIELAB color space. We considered whether the objective evaluation value related to the subjective evaluation value or not.
... By quantifying these assessments, we consider that the general assessment is possible. There were many studies about the subjective evaluation of 3D image or video quality [6][7][8][9][10]. However, the studies for the luminance and the coded degradation, which is not reported previously. ...
In this paper, we processed the contrast enhancement for multi-view 3D image, therefore, we changed luminance. Next, we generated image by composing each view image by coding H.265/HEVC. Then, we carried out the subjective evaluation about generating image. On the other hand, we evaluated objectively about luminance value measurement by using color difference (such as CIEDE2000) in S-CIELAB color space. We considered whether the objective evaluation value related to the subjective evaluation value or not. Finally, we analyzed their results statistically using a Support Vector Machine (SVM).
... In this study, we used many evaluation image patterns. Compared to the previous studies [1], [2], [6], [25], [26], we were able to consider better for the background or object region using a SVM classification. Therefore, we were able to gain different tendencies and knowledge. ...
Many previous studies on image quality assessment of 3D still images or video clips have been conducted. In particular, it is important to know the region in which assessors are interested or on which they focus in images or video clips, as represented by the ROI (Region of Interest). For multi-view 3D images, it is obvious that there are a number of viewpoints; however, it is not clear whether assessors focus on objects or background regions. It is also not clear on what assessors focus depending on whether the background region is colored or gray scale. Furthermore, while case studies on coded degradation in 2D or binocular stereoscopic videos have been conducted, no such case studies on multi-view 3D videos exist, and therefore, no results are available for coded degradation according to the object or background region in multi-view 3D images. In addition, in the case where the background region is gray scale or not, it was not revealed that there were affection for gaze point environment of assessors and subjective image quality. In this study, we conducted experiments on the subjective evaluation of the assessor in the case of coded degradation by JPEG coding of the background or object or both in 3D CG images using an eight viewpoint parallax barrier method. Then, we analyzed the results statistically and classified the evaluation scores using an SVM.
Previously, there were many studies about the image quality evaluation based on S-CIELAB color space including the spatial frequency characteristics of human vision system. It is not obvious to what extent was accepted for the assessors when we see the 3D image which the luminance change may affect the stereoscopic effect and assessment generally. Similarly, it is not obvious when we see the multi-view 3D image. As represented by ROI (Region Of Interest), it is important where the assessors are interested in or focused on the part of the 3D image when they see the 3D image. Seeing the content creators, we consider that they create expecting for users to focus on the object region than the background region. Therefore, we considered that we need to verify by subjective evaluation experiment to what extent was not interfered with regard to the contrast enhancement and the coded degradation. Furthermore, we consider that we are able to become to carry out the general evaluation for the luminance component using both S-CIELAB color space and CIEDE2000, in addition to the subjective evaluation. In this paper, first, we carried out the subjective evaluation experiment for the contrast enhancement of the object region in an image with 8 viewpoints parallax barrier method. Next, we analyzed their results statistically using a Support Vector Machine (SVM). On the other hand, we evaluated objectively about luminance value measurement using CIEDE2000 in S-CIELAB color space. We considered whether the objective evaluation value related to the subjective evaluation value or not.
In this paper, we processed the contrast enhancement for multi-view 3D image, therefore, we changed luminance. Next, we generated image by composing each view image by coding H.265/HEVC. Then, we carried out the subjective evaluation about generating image. On the other hand, we evaluated objectively about luminance value measurement by using color difference (such as CIEDE2000) in S-CIELAB color space. We considered whether the objective evaluation value related to the subjective evaluation value or not. Finally, we analyzed their results statistically using a Support Vector Machine (SVM).
We analyze the subjective perceived picture quality of coded stereoscopic pictures which are disparate in the object-and background-regions using a single stimulus evaluation method. In.addition, we examine subjective differences in perceptions of picture quality between stereoscopic pictures and 2-dimensional displayed pictures. When the picture quality in the object-and background-region is the same, no significant difference is seen in the evaluation value of the stereoscopic picture and the counterpart 2-dimensional displayed picture. When the picture quality of the object-region is different from the picture quality of the background-region, the obtained subjective picture quality of the stereoscopic picture is the same as or better than the evaluation value of the 2-dimensional displayed picture. The extent of this tendency correlates with the proportion of the object region to the entire image.
Recently, we are able to watch 3D videos or movies increasingly without glasses. However, they are various stereological and evaluation methods for multi-view 3D with no glasses for image quality, and their display methods are not unified. In this paper, we showed 3D CG images with 8 viewpoints lenticular lens method by ACR and DSIS methods, when we analyzed the results statistically with subjective evaluation. The experiment examined whether or not assessor were able to comfortable view the images by degree of camera’s interval and viewpoints, and whether or not they perceive or annoy degree of coded degradation at certain viewpoints.