Abstract
Subjective image quality assessment for a large database is a lengthy and tiring process. The task becomes more complicated when the testing of tone-mapped images is desired as it is not possible to directly display HDR content on standard displays, hence unavailability of reference images for comparison. This limits the quality evaluation methods to comparative or categorical judgement. For this study, we used the comparative judgement method to subjectively test the performance of images tone-mapped by different operators against each other on eight different visual image appearance attributes. Attributes having a higher correlation with overall image preference scores are used to develop the proposed no-reference image quality metric. Results of the psychophysical experiment and performance of the resulting metric are reported here.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Reinhard E, Heidrich W, Debevec P et al (2012) High dynamic range imaging, 2nd edn. Morgan Kaufmann, Burlington, MA, pp 438–439
Wang Z, Bovik AC (2009) Mean squared error: love it or leave it? A new look at signal fidelity measures. IEEE Signal Process Mag 26(1):98–117
Wang Z, Bovik AC, Sheikh HR et al (2004) Image quality assessment: From error visibility to structural similarity. IEEE Trans Imag Process 13(4):600–612
Yeganeh H, Wang Z (2013) Objective quality assessment of tone-mapped images. IEEE Trans Image Process 22(2):657–667
Nafchi HZ, Shahkolaei A, Moghammadam RF (2015) FSITM: A feature similarity index for tone-mapped images. IEEE Signal Process Lett 22(8):1026–1029
Wang Z, Sheikh HR, Bovik AC (2002) No-reference perceptual quality assessment of JPEG compressed images. In: IEEE international conference on image processing, pp 477–480
Caviedes J, Oberti F (2004) A new sharpness metric based on local kurtosis, edge and energy information. Signal Process Image Commun 19:147–161
Mittal A, Soundararajan R, Bovik AC (2013) Making a completely blind image quality analyzer. IEEE Signal Process Lett 22(3):209–212
Zhang L, Zhang L, Bovik AC (2015) A feature-enriched completely blind local image quality analyzer. IEEE Trans Image Process 24(8):2579–2591
Gong R, Xu H, Luo MR et al (2015) Comprehensive model for predicting perceptual image quality of smart mobile devices. Appl Opt 54:85–95
Fairchild MD (2007) The HDR photographic survey. In: Color and imaging conference, Society for Imaging Science and Technology, pp 233–238
Drago F, Myszkowski K, Annen T et al (2003) Adaptive logarithmic mapping for displaying high contrast scenes. Comput Graph Forum 22(3):419–426
Reinhard E, Devlin K (2005) Dynamic range reduction inspired by photoreceptor physiology. IEEE Trans Vis Comput Graph 11(1):13–24
Reinhard E, Stark M, Shirley P et al (2002) Photographic tone reproduction for digital images. ACM Trans Graph 21(3):267–276
Schlick C (1995) Quantization techniques for visualization of high dynamic range pictures. In: Sakas G, Müller S, Shirley P (eds) Photorealistic rendering techniques: focus on computer graphics (Tutorials and perspectives in computer graphics). Springer, Berlin, Heidelberg, pp 7–20
Ward G, Rushmeier H, Piatko C (1997) A visibility matching tone reproduction operator for high dynamic range scenes. IEEE Trans Vis Comput Graph 3(4):291–306
Choi SY, Luo MR, Pointer MR et al (2008) Predicting perceived colorfulness, contrast, naturalness and quality for color images reproduced on a large display. In: 16th color imaging conference, IS&T and SID, pp 158–164
Li C, Li Z, Wang Z et al (2017) Comprehensive color solutions: CAM16, CAT16, and CAM16-UCS. Color Res Application 42(6):703–718
Calabria AJ, Fairchild MD (2003) Perceived image contrast and observer preference II. Empirical modeling of perceived image contrast and observer preference data. J Imaging Sci Technol 47(6):494–508
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Khan, M.U., Mehmood, I., Luo, M.R. (2020). Experiment Based No-Reference Objective Image Quality Metric for Testing Performance of Different Tone Mapped Images. In: Zhao, P., Ye, Z., Xu, M., Yang, L. (eds) Advanced Graphic Communication, Printing and Packaging Technology. Lecture Notes in Electrical Engineering, vol 600. Springer, Singapore. https://doi.org/10.1007/978-981-15-1864-5_1
Download citation
DOI: https://doi.org/10.1007/978-981-15-1864-5_1
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-1863-8
Online ISBN: 978-981-15-1864-5
eBook Packages: EngineeringEngineering (R0)