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3D CG Image Quality Assessment for the Luminance Change by Contrast Enhancement Including S-CIELAB Color Space with 8 Viewpoints Parallax Barrier Method

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Abstract

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).
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... And then , we classify the evaluation score for the coded image quality and image region by using SVM (Support Vector Machine). Furthermore, we carried out the objective assessment by measuring the luminance of generated image by using S -CIELAB color space [11][12][13][14], the color difference between reference and processed images by using CIEDE2000 [11][12][13][14], finally, we compared to the subjective assessment. ...
... And then , we classify the evaluation score for the coded image quality and image region by using SVM (Support Vector Machine). Furthermore, we carried out the objective assessment by measuring the luminance of generated image by using S -CIELAB color space [11][12][13][14], the color difference between reference and processed images by using CIEDE2000 [11][12][13][14], finally, we compared to the subjective assessment. ...
Technical Report
Previously, we studied about multi-view 3D CG image quality evaluation including visible digital watermarking by regions. As a result, it becomes clear that there was the mutual relationship between the watermarking by regions and the coded image quality for the multi-view 3D image. However, it is not clear that there is the relation between two focus points whether background region is color or gray scale. On the other hand, it is possible for assessors to focus on the object mutually by using gray scale for the background region of an image. Therefore, in case the background region is gray scale, we need to clear the relation among the gray scale background, the watermarking by regions, and the coded image quality by evaluating for the multi-view 3D CG image quality including the watermarking by regions. In this paper, first, we carried out the subjective quality assessment of 3D CG images including visible digital watermarking by regions with 8 viewpoints parallax barrier method. From results, we analyzed and classified the evaluation values statistically for the image region and the coded image quality by Support Vector Machine (SVM). On the other hand, we measured the luminance for the generated images by using S-CIELAB color space, and we also measured the color difference by using CIEDE2000. We carried out the objective assessments by these measurements, and compared to subjective assessment mutually.
Article
Full-text available
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.
Article
Full-text available
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.
Poster
Full-text available
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.
Presentation
Full-text available
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.
Article
We are developing an objective evaluation method for the H.264/AVC codec images which is highly correlated with subjective evaluation by human observers. In our previous report, we proposed an S-CIELAB-based method with a spatial limitation in calculation for this purpose. We also presented that the objective evaluation values by the proposed method for the images at just noticeable compression rate are similar. In this paper, it is confirmed that the similarity is still maintained among an increased number of images. Next, for the images at several levels of degradation noticeable compression rates, the correlation between the subjective evaluation value and the objective evaluation values by the proposed method and other conventional methods were compared. As a result, the proposed method was superior to the other methods both in the evaluation at just noticeable compression rate and in the evaluation at degradation noticeable compression rates.
Article
Recent work in color difference has led to the recommendation of CIEDE2000 for use as an industrial color difference equation. While CIEDE2000 was designed for predicting the visual difference for large isolated patches, it is often desired to determine the perceived difference of color images. The CIE TC8-02 has been formed to examine these differences. This paper presents an overview of spatial filtering combined with CIEDE2000, to assist TC8-02 in the evaluation and implementation of an image color difference metric. Based on the S-CIELAB spatial extension, the objective is to provide a single reference for researchers desiring to utilize this technique. A general overview of how S-CIELAB functions, as well as a comparison between spatial domain and frequency domain filtering is provided. A reference comparison between three CIE recommended color difference formulae is also provided. © 2003 Wiley Periodicals, Inc. Col Res Appl, 28, 425–435, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/col.10195
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