DocumentCode
641484
Title
Perceptual image quality: A dissimilarity measure to quantify the degradation of image quality
Author
Saha, Simanto ; Si Liu ; Tahtali, Murat ; Lambert, Andrew ; Pickering, Mark
Author_Institution
Sch. of Eng. & Inf. Technol., Univ. of New South Wales, Canberra, ACT, Australia
fYear
2013
fDate
10-12 June 2013
Firstpage
245
Lastpage
249
Abstract
This paper introduces a novel image quality metric that outperforms other existing and widely used metrics, namely the Root Mean Square Error (RMSE) and Structural Similarity Index (SSIM). Objective methods for assessing perceptual image quality are important for many image processing applications nowadays, however none of the existing metrics are completely satisfactory. Structural Similarity Index has been found promising in some cases, however for medical imaging (especially for CT and MRI images) it still remains immature. Perceptual Dissimilarity (PD) has been found reliable considering medical imaging demands; however for natural images, SSIM still outperforms PD. On that perspective, the proposed image quality metric named Perceptual Image Quality (PIQ) is more consistent with the human visual system´s characteristics than SSIM and RMSE.
Keywords
biomedical MRI; computerised tomography; medical image processing; visual perception; CT image; MRI image; PD; RMSE; SSIM; human visual system characteristics; image processing applications; image quality degradation; image quality metric; medical imaging; natural images; perceptual dissimilarity measure; perceptual image quality assessment; root mean square error; structural similarity index; Biomedical imaging; Degradation; Image quality; Image reconstruction; Indexes; Measurement; Visual systems; Root Mean Square Error; Structural Similarity Index; image quality metric; visual saliency;
fLanguage
English
Publisher
ieee
Conference_Titel
Visual Information Processing (EUVIP), 2013 4th European Workshop on
Conference_Location
Paris
Type
conf
Filename
6623969
Link To Document