Abstract
The development of general purpose no-reference approaches to dehazed image quality evaluation still lags in recent advances in image dehazing methods. While a number of image dehazing methods have been established and have shown to perform well, these are correlating highly with subjective evaluation of image quality. Toward ameliorating this we introduce the DIAS (Dehazed Image Assessment using Statistics) which is a no-reference approach to dehazed image quality assessment (DIQA) that does not assume a specific type of distortion of the image. It is based on detecting dehazed image quality based on Circularly Symmetric Gaussian Normalization Procedure Visible Edges Feature and it requires no training. The method is shown to correlate highly with human perception of quality. Our contribution in this direction is the development of dehazed image quality assessment method based on Circularly Symmetric Gaussian Normalization Procedure Visible Edges Feature which does not require exposure to distorted images priori and training.
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Acknowledgments
The authors acknowledge the financial support from the Fundamental Research Funds for the Central Universities, Natural Science Foundation of China (project No: 51279152) and Zhejiang Provincial Natural Science Foundation of China (project No.: LY12F02015). The author is grateful to the anonymous referee for a careful checking of the details and for helpful comments that improved this paper.
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Hu, Z., Liu, Q. (2014). A Method for Dehazed Image Quality Assessment. In: Wen, Z., Li, T. (eds) Practical Applications of Intelligent Systems. Advances in Intelligent Systems and Computing, vol 279. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54927-4_87
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DOI: https://doi.org/10.1007/978-3-642-54927-4_87
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