Local Scale Control for Edge Detection and Blur Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image quality assessment using the joint spatial/spatial-frequency representation
EURASIP Journal on Applied Signal Processing
No reference image quality assessment for JPEG2000 based on spatial features
Image Communication
A no-reference objective image sharpness metric based on the notion of just noticeable blur (JNB)
IEEE Transactions on Image Processing
A new look to multichannel blind image deconvolution
IEEE Transactions on Image Processing
A New Free Reference Image Quality Index Based on Perceptual Blur Estimation
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Blind and semi-blind deblurring of natural images
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
No-reference quality assessment using natural scene statistics: JPEG2000
IEEE Transactions on Image Processing
A Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms
IEEE Transactions on Image Processing
Wireless Video Quality Assessment: A Study of Subjective Scores and Objective Algorithms
IEEE Transactions on Circuits and Systems for Video Technology
Blind Image Quality Assessment: From Natural Scene Statistics to Perceptual Quality
IEEE Transactions on Image Processing
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A new approach for analyzing the blur effect on real images is proposed. This approach is based on the Multiplicative Multi-resolution Decomposition MMD. From MMD image-content analysis, a blind image quality measure dedicated to blur is then derived. The proposed measure has been applied on Gaussian-blurred and JPEG2000-compressed images from the LIVE, TID and IVC databases. The performance of the proposed measure is evaluated and compared with some referenced image quality metrics. The experimental results measured in terms of correlation with the subjective assessment of the images, demonstrate the efficiency of the proposed image quality measure in predicting the amount of blur.