DocumentCode :
710221
Title :
No-Reference Image Blur Assessment in the DWT Domain and Blurred Image Classification
Author :
Yoneyama, Akihiko ; Minamoto, Teruya
Author_Institution :
Dept. of Inf. Sci., Saga Univ., Saga, Japan
fYear :
2015
fDate :
13-15 April 2015
Firstpage :
329
Lastpage :
334
Abstract :
We propose several new no-reference/blind image quality indices for blur assessment based on the discrete wavelet transform (DWT) and demonstrate that a given image can be classified based on blur by using these indices. Our approach relies on the sharpness, granularity, and L1-norm estimation of the given image in the DWT domains with a relatively long support width. Unlike conventional methods, the reference image is produced from the given image without computing special statistics or using unsupervised methods. Instead, we produce the reference image from the given image by using certain sharpening and denoising methods, and by adopting ideas from reference image quality measures such as the PSNR and SSIM in the DWT domain. We describe the detailed procedure of our method and show some experimental results that demonstrate the high performance.
Keywords :
discrete wavelet transforms; image classification; image denoising; image restoration; DWT; DWT domain; L1-norm estimation; PSNR; SSIM; blind image quality indices; blurred image classification; denoising methods; discrete wavelet transform; image granularity; image sharpness; no-reference image blur assessment; sharpening methods; unsupervised methods; Cameras; Discrete wavelet transforms; Estimation; Image edge detection; Image quality; Noise reduction; Blurred image; Discrete wavelet transform; Image classification; No-reference;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology - New Generations (ITNG), 2015 12th International Conference on
Conference_Location :
Las Vegas, NV
Print_ISBN :
978-1-4799-8827-3
Type :
conf
DOI :
10.1109/ITNG.2015.59
Filename :
7113494
Link To Document :
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