Image Quality Assessment Based on Gradient Similarity

In this paper, we propose a new image quality assessment (IQA) scheme, with emphasis on gradient similarity. Gradients convey important visual information and are crucial to scene understanding. Using such information, structural and contrast changes can be effectively captured. Therefore, we use th...

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Vydáno v:IEEE transactions on image processing Ročník 21; číslo 4; s. 1500 - 1512
Hlavní autoři: Anmin Liu, Weisi Lin, Narwaria, M.
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States IEEE 01.04.2012
Témata:
Algorithms
Contrast masking
gradient similarity
human visual system (HVS)
Image coding
Image edge detection
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image quality
image quality assessment (IQA)
Pattern Recognition, Automated - methods
Quality Control
Reproducibility of Results
Sensitivity and Specificity
Signal Processing, Computer-Assisted
structural similarity (SSIM)
Subtraction Technique
Transform coding
Visualization
White noise
ISSN:1057-7149, 1941-0042, 1941-0042
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Popis
Shrnutí:In this paper, we propose a new image quality assessment (IQA) scheme, with emphasis on gradient similarity. Gradients convey important visual information and are crucial to scene understanding. Using such information, structural and contrast changes can be effectively captured. Therefore, we use the gradient similarity to measure the change in contrast and structure in images. Apart from the structural/contrast changes, image quality is also affected by luminance changes, which must be also accounted for complete and more robust IQA. Hence, the proposed scheme considers both luminance and contrast-structural changes to effectively assess image quality. Furthermore, the proposed scheme is designed to follow the masking effect and visibility threshold more closely, i.e., the case when both masked and masking signals are small is more effectively tackled by the proposed scheme. Finally, the effects of the changes in luminance and contrast-structure are integrated via an adaptive method to obtain the overall image quality score. Extensive experiments conducted with six publicly available subject-rated databases (comprising of diverse images and distortion types) have confirmed the effectiveness, robustness, and efficiency of the proposed scheme in comparison with the relevant state-of-the-art schemes.
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ISSN:1057-7149
1941-0042
1941-0042
DOI:10.1109/TIP.2011.2175935