Masaru Miyao’s research while affiliated with Nagoya University and other places

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Publications (14)


Multi-view 3D CG image quality assessment for contrast enhancement based on S-CIELAB color space
  • Article

July 2017

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28 Reads

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17 Citations

IEICE Transactions on Information and Systems

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Masaru Miyao

Previously, it is not obvious to what extent was accepted for the assessors when we see the 3D image (including multi-view 3D) which the luminance change may affect the stereoscopic effect and assessment generally. We think that we can conduct a general evaluation, along with a subjective evaluation, of the luminance component using both the S-CIELAB color space and CIEDE2000. In this study, first, we performed three types of subjective evaluation experiments for contrast enhancement in an image by using the eight viewpoints parallax barrier method. Next, we analyzed the results statistically by using a support vector machine (SVM). Further, we objectively evaluated the luminance value measurement by using CIEDE2000 in the S-CIELAB color space. Then, we checked whether the objective evaluation value was related to the subjective evaluation value. From results, we were able to see the characteristic relationship between subjective assessment and objective assessment.


Multi-view 3D CG Image Quality Assessment for Contrast Enhancement Including S-CIELAB Color Space in case the Background Region is Gray Scale
  • Article
  • Full-text available

July 2016

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89 Reads

IEICE Proceeding Series

In this paper, we experimented the subjective evaluation for 3D CG image including the gray scale region with 8 viewpoints parallax barrier method, and we analyzed this result statistically. Next, we measured about the relation between the luminance change and the color difference by using S-CIELAB color space and CIEDE2000.

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Multi-view 3D CG Image Quality Assessment for Contrast Enhancement Including S-CIELAB Color Space in case the Background Region is Gray Scale

July 2016

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58 Reads

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2 Citations

In this paper, we experimented the subjective evaluation for 3D CG image including the gray scale region with 8 viewpoints parallax barrier method, and we analyzed this result statistically. Next, we measured about the relation between the luminance change and the color difference by using S-CIELAB color space and CIEDE2000. As a result, we obtained knowledge about the relation among the coded image quality, the contrast enhancement, and gray scale.


Multi-view 3D CG Image Quality Assessment by Using S-CIELAB Color Space Including Visible Digital Watermarking by Regions in case the Background Region is Gray Scale

May 2016

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23 Reads

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.


Multi-view 3D CG Image Quality Assessment by Using S-CIELAB Color Space Including Visible Digital Watermarking by Regions in case the Background Region is Gray Scale

May 2016

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20 Reads

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.



Fig. 1: 3D CG image and watermarking image  
Table 1 : Main specification of subjective evaluation experiment
Table 2 : EBU method
Table 3 : SVM of Exp. 1 ("Pv")
Table 7 : SVM of Exp. 2 ("Fp")
Multi-view 3D CG Image Quality Evaluation Including Visible Digital Watermarking Based on Color Information

March 2016

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117 Reads

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2 Citations

IEICE Proceeding Series

Thus far, we have studied multi-view 3D image quality evaluation, including visible digital watermarking, in the case of considering coded degradation, region, resistance, and number of viewpoints. As a result, the more we process watermarking in the low frequency domain, the more the assessment tends toward independence from image or video patterns. However, we do not consider color information in the case where we generate digital watermarking images. In this paper, first, for the 3D CG images encoded and decoded by H.265/HEVC with 8 Viewpoints Parallax Barrier Method, we process the wavelet transformation, and perform embedding for the arrangement of the high and low frequency domain (LL3, HL3, LH3) in the same frequency level per viewpoint. Next, we evaluate the generated image, analyze the results, and classify for RGB pattern and coded degradation using SVM (Support Vector Machine).


3D CG Image Quality Metrics by Regions with 8 Viewpoints Parallax Barrier Method

August 2015

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32 Reads

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15 Citations

IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences

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.


Table 2 : Experimental Specification
Table 3 : EBU method
Table 5 : SVM (í µí±¸í µí±¸í µí±¸í µí±¸)
3D CG Image Quality Assessment for the Luminance Change by Contrast Enhancement Including S-CIELAB Color Space with 8 Viewpoints Parallax Barrier Method

June 2015

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64 Reads

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2 Citations

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).


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

June 2015

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78 Reads

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2 Citations

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).


Citations (8)


... We have carried out statistical analyses of contrast enhancement considering S-CIELAB color space [1], evaluation methods of the coded image quality in the case of object or background regions [2], statistical analysis of subjective evaluation values with regard to evaluation of coded image quality of multi-view 3D CG images [3], and statistical analysis of questionnaire survey of 3D video clips considering visual function and characteristics [4]. In addition, as a previous study of this study, we experimented on H.265/HEVC encoded image quality evaluation of 360 degrees camera images from both objective and subjective image quality perspectives [5]. ...

Reference:

Image Quality Metrics for Cross Reality Considering Image Region and Perspective Based on 360 Degrees Camera
Multi-view 3D CG image quality assessment for contrast enhancement based on S-CIELAB color space
  • Citing Article
  • July 2017

IEICE Transactions on Information and Systems

... On the other hand, the ultra-high speed of the optical Internet has led to a rapid increase in the amount of image information transmitted and received, and opportunities to handle large-scale image data have increased [1], [2]. Thus far, there were studies on image processing using sparse coding, which represents part or all of the image data input with as few combinations as possible to achieve a highly efficient and effective representation of the image data. ...

Multi-view 3D CG Image Quality Assessment for Contrast Enhancement Including S-CIELAB Color Space in case the Background Region is Gray Scale
  • Citing Presentation
  • July 2016

... This study was carried out based on the Grant-in-Aid for Scientific Research (B) 24300046, and the research grant for Ph.D. student at Nagoya University. This paper is included improvement based on contents of our domestic conference proceeding [4], our international conference proceeding [13], and our technical report [14]. ...

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

... This study was carried out based on the Grant-in-Aid for Scientific Research (B) 24300046, and the research grant for Ph.D. student at Nagoya University. This international conference paper is included improvement based on contents of our domestic conference proceedings [3], [11]. ...

3D CG Image Quality Metrics Including the Coded Degradation by Regions with 8 Viewpoints Parallax Barrier Method

IEICE Proceeding Series

... For images created by 3D CG, color restoration by simple colorization is difficult because they contain multi-dimensional information. Therefore, we wondered if it would be possible to restore them using the visible digital watermarking technique we have been studying [4], [5]. ...

Multi-view 3D CG Image Quality Evaluation Including Visible Digital Watermarking Based on Color Information

IEICE Proceeding Series

... We have carried out statistical analyses of contrast enhancement considering S-CIELAB color space [1], evaluation methods of the coded image quality in the case of object or background regions [2], statistical analysis of subjective evaluation values with regard to evaluation of coded image quality of multi-view 3D CG images [3], and statistical analysis of questionnaire survey of 3D video clips considering visual function and characteristics [4]. In addition, as a previous study of this study, we experimented on H.265/HEVC encoded image quality evaluation of 360 degrees camera images from both objective and subjective image quality perspectives [5]. ...

3D CG Image Quality Metrics by Regions with 8 Viewpoints Parallax Barrier Method
  • Citing Article
  • August 2015

IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences

... 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. ...

3D CG Image Quality Assessment for the Luminance Change by Contrast Enhancement Including S-CIELAB Color Space with 8 Viewpoints Parallax Barrier Method
  • Citing Presentation
  • June 2015

... 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. ...

3D CG Image Quality Metrics Including the Coded Degradation by Regions with 8 Viewpoints Parallax Barrier Method
  • Citing Poster
  • September 2014