No-reference quality metrics estimate the perceived quality exploiting only the image itself. Typically, no-reference metrics are designed to measure specific artifacts using a distortion model. Some psycho-visual experiments have shown that the perception of distortions is influenced by the amount of details in the image's content, suggesting the need for a "content weighting factor." This dependency is coherent with known masking effects of the human visual system. in order to explore this phenomenon, we setup a series of experiments applying regression trees to the problem of no-reference quality assessment. in particular, we have focused on the blocking distortion of JPEG compressed images. Experimental results show that information about the visual content of the image can be exploited to improve the estimation of the quality of JPEG compressed images. © 2010 SPIE-IS&T.

Marini, F., Cusano, C., Schettini, R. (2010). No-reference metrics for JPEG: analysis and refinement using wavelets. In Proceedings of SPIE Image Quality and System Performance VII. S P I E - International Society for Optical Engineering [10.1117/12.839863].

No-reference metrics for JPEG: analysis and refinement using wavelets

MARINI, FABRIZIO;CUSANO, CLAUDIO;SCHETTINI, RAIMONDO
2010

Abstract

No-reference quality metrics estimate the perceived quality exploiting only the image itself. Typically, no-reference metrics are designed to measure specific artifacts using a distortion model. Some psycho-visual experiments have shown that the perception of distortions is influenced by the amount of details in the image's content, suggesting the need for a "content weighting factor." This dependency is coherent with known masking effects of the human visual system. in order to explore this phenomenon, we setup a series of experiments applying regression trees to the problem of no-reference quality assessment. in particular, we have focused on the blocking distortion of JPEG compressed images. Experimental results show that information about the visual content of the image can be exploited to improve the estimation of the quality of JPEG compressed images. © 2010 SPIE-IS&T.
No
paper
Blocking artifacts; Image content; Image quality; No-reference metric; Regression trees;
English
Image Quality and System Performance VII
9780819479228
2010
Marini, F., Cusano, C., Schettini, R. (2010). No-reference metrics for JPEG: analysis and refinement using wavelets. In Proceedings of SPIE Image Quality and System Performance VII. S P I E - International Society for Optical Engineering [10.1117/12.839863].
Marini, F; Cusano, C; Schettini, R
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/24973
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