Researching | Subjective Image Quality Assessment for Large Samples

Laser & Optoelectronics Progress, Volume. 56, Issue 13, 131103(2019)

Subjective Image Quality Assessment for Large Samples

Yang Liu, Runqiang Jiang^*, Hongjun Yu, and Jian Chen

Author Affiliations

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, Jilin 130033, China

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Figures&Tables (19)

References (23)

Paper Information

Figures & Tables(19)

Fig. 1. Screenshot of software used in subjective assessment experiments of TID2013

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Fig. 2. Effects of r1 and r2 on results of subjective assessment

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Fig. 3. Screenshot of software used in cyclical integrating

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Fig. 4. Screenshot of software used in selecting best quality

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Fig. 5. Screenshot of software used in adjusting sequence

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Fig. 6. Reference image

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Fig. 7. Results of subjective assessment experiments

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Fig. 8. Dynamic clustering diagram of images

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Fig. 9. Subjective assessment scores of image quality

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Fig. 10. Screenshot of software used in test of just-noticeable difference

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Fig. 11. Areas that are easily perceived to change in quality

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Fig. 12. Euclidean distances between test results and true values

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Fig. 13. STDs of results obtained by proposed method

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Fig. 14. Comparison of STDs between proposed method and other image quality databases

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Table 1. Widely used image quality databases

Table 1. Widely used image quality databases

Database	Year	Reference	Distortion	Level	Total	Format	Resolution
LIVE(image)	2006	29	5	5	1011	BMP	≤768×512
IVC	2005	10	10	4	195	BMP	512×512
CSIQ	2010	30	6	4-5	930	PNG	512×512
TID2008	2008	25	17	4	1725	BMP	512×384
TID2013	2013	25	24	5	3025	BMP	512×384

Table 2. Experiments of subjective assessment

Table 2. Experiments of subjective assessment

Database	Method	Score	Subject	Rating	Screen	Distance
LIVE(image)	SS	DMOS	161	20-29	CRT/21″	2H_s-2.5H_s
IVC	DSIS	DMOS	15	15	CRT/21″	6H_s
CSIQ	SS	DMOS	25	5-7	LCD/21″	80 cm
TID2008	DSCQS	MOS	838	33	LCD/19″	2H_s-4H_s
TID2013	DSCQS	MOS	985	47	LCD&CRT/19″	2H_s-4H_s

Table 3. Quality scale of subjective assessment for ITU-R BT.500-13
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Table 3. Quality scale of subjective assessment for ITU-R BT.500-13
Score Distortion level Score Distortion level
-3 Much worse +1 Slightly better
-2 Worse +2 Better
-1 Slightly worse +3 Much better
0 The same

Table 4. Simplified quality scale of subjective assessment
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Table 4. Simplified quality scale of subjective assessment
Score Distortion level
+2 Better
+1 The same

Table 5. Mean JND

Table 5. Mean JND

Distortion level	1	3	5	17	24	32	40	48	56
Point spread blur radius	0.31	0.94	1.56	5.31	7.50	10.00	12.50	15.00	17.50
Just noticeable difference	+0.33	+0.28	+0.34	+0.51	+0.66	+0.97	+1.52	+1.93	+3.35
Obvious difference	+0.69	+0.75	+0.84	+1.86	+2.05	+2.66	+2.84	+3.67	+3.96

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Yang Liu, Runqiang Jiang, Hongjun Yu, Jian Chen. Subjective Image Quality Assessment for Large Samples[J]. Laser & Optoelectronics Progress, 2019, 56(13): 131103

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Paper Information

Category: Imaging Systems

Received: Dec. 5, 2018

Accepted: Jan. 29, 2019

Published Online: Jul. 11, 2019

The Author Email: Jiang Runqiang (jiang_runqiang@sina.com)

DOI:10.3788/LOP56.131103

Topics

laser devices and laser physics

Lasers and Laser Optics

laser manufacturing

Instrumentation, Measurement and Metrology