Novel evaluation index for image quality

Sheikh Md. Rabiul Islam, Xu HUANG, Kim LE

Research output: A Conference proceeding or a Chapter in BookConference contribution

Abstract

Indexes used for image quality evaluation are provided as computational models to measure the quality of images in a perceptually consistent manner. This paper presents a novel evaluation index for assessing image qualities. The index is a modification of the existing traditional Structural Similarity Index Measure (SSIM) by adding another factor to reflect the shape of the brightness histogram of the assessed image. The proposed index therefore is a combination of four major factors luminance, contrast, structure and shape of histogram. This index is mathematically simple and applicable in various image processing. For demonstration a new image de-noising approach using an adaptive shrinkage threshold in the shearlet domain is used. Experimental results show that the new image quality indexes give better prediction accuracy, better prediction monotonicity than PSNR, HQI, UIQI and SSIM.
Original languageEnglish
Title of host publication2014 International Conference on image Computing: Techniques and Applications (DlCTA),
Subtitle of host publicationTechniques and Applications, DICTA 2014
EditorsSon Lam Phung, Abdesselam Bouzerdoum, Philip Ogunbona, Wanqing Li, Lei Wang
Place of PublicationUSA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages293-300
Number of pages8
ISBN (Electronic)9781479954094
ISBN (Print)9781479954094
DOIs
Publication statusPublished - 25 Nov 2014
Event2014 International Conference on Digital Image Computing, Techniques and Applications - Wollongong, Wollongong, Australia
Duration: 25 Nov 201427 Nov 2014

Publication series

Name2014 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2014

Conference

Conference2014 International Conference on Digital Image Computing, Techniques and Applications
Abbreviated titleDICTA 2014
CountryAustralia
CityWollongong
Period25/11/1427/11/14

Fingerprint

Image quality
Luminance
Image denoising
Image processing
Demonstrations

Cite this

Islam, S. M. R., HUANG, X., & LE, K. (2014). Novel evaluation index for image quality. In S. L. Phung, A. Bouzerdoum, P. Ogunbona, W. Li, & L. Wang (Eds.), 2014 International Conference on image Computing: Techniques and Applications (DlCTA),: Techniques and Applications, DICTA 2014 (pp. 293-300). [7008120] (2014 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2014). USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/DICTA.2014.7008120
Islam, Sheikh Md. Rabiul ; HUANG, Xu ; LE, Kim. / Novel evaluation index for image quality. 2014 International Conference on image Computing: Techniques and Applications (DlCTA),: Techniques and Applications, DICTA 2014. editor / Son Lam Phung ; Abdesselam Bouzerdoum ; Philip Ogunbona ; Wanqing Li ; Lei Wang. USA : IEEE, Institute of Electrical and Electronics Engineers, 2014. pp. 293-300 (2014 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2014).
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abstract = "Indexes used for image quality evaluation are provided as computational models to measure the quality of images in a perceptually consistent manner. This paper presents a novel evaluation index for assessing image qualities. The index is a modification of the existing traditional Structural Similarity Index Measure (SSIM) by adding another factor to reflect the shape of the brightness histogram of the assessed image. The proposed index therefore is a combination of four major factors luminance, contrast, structure and shape of histogram. This index is mathematically simple and applicable in various image processing. For demonstration a new image de-noising approach using an adaptive shrinkage threshold in the shearlet domain is used. Experimental results show that the new image quality indexes give better prediction accuracy, better prediction monotonicity than PSNR, HQI, UIQI and SSIM.",
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Islam, SMR, HUANG, X & LE, K 2014, Novel evaluation index for image quality. in SL Phung, A Bouzerdoum, P Ogunbona, W Li & L Wang (eds), 2014 International Conference on image Computing: Techniques and Applications (DlCTA),: Techniques and Applications, DICTA 2014., 7008120, 2014 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2014, IEEE, Institute of Electrical and Electronics Engineers, USA, pp. 293-300, 2014 International Conference on Digital Image Computing, Techniques and Applications, Wollongong, Australia, 25/11/14. https://doi.org/10.1109/DICTA.2014.7008120

Novel evaluation index for image quality. / Islam, Sheikh Md. Rabiul; HUANG, Xu; LE, Kim.

2014 International Conference on image Computing: Techniques and Applications (DlCTA),: Techniques and Applications, DICTA 2014. ed. / Son Lam Phung; Abdesselam Bouzerdoum; Philip Ogunbona; Wanqing Li; Lei Wang. USA : IEEE, Institute of Electrical and Electronics Engineers, 2014. p. 293-300 7008120 (2014 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2014).

Research output: A Conference proceeding or a Chapter in BookConference contribution

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N2 - Indexes used for image quality evaluation are provided as computational models to measure the quality of images in a perceptually consistent manner. This paper presents a novel evaluation index for assessing image qualities. The index is a modification of the existing traditional Structural Similarity Index Measure (SSIM) by adding another factor to reflect the shape of the brightness histogram of the assessed image. The proposed index therefore is a combination of four major factors luminance, contrast, structure and shape of histogram. This index is mathematically simple and applicable in various image processing. For demonstration a new image de-noising approach using an adaptive shrinkage threshold in the shearlet domain is used. Experimental results show that the new image quality indexes give better prediction accuracy, better prediction monotonicity than PSNR, HQI, UIQI and SSIM.

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Islam SMR, HUANG X, LE K. Novel evaluation index for image quality. In Phung SL, Bouzerdoum A, Ogunbona P, Li W, Wang L, editors, 2014 International Conference on image Computing: Techniques and Applications (DlCTA),: Techniques and Applications, DICTA 2014. USA: IEEE, Institute of Electrical and Electronics Engineers. 2014. p. 293-300. 7008120. (2014 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2014). https://doi.org/10.1109/DICTA.2014.7008120