Iterative PCA approach for blind restoration of single blurred image

2013 ◽  
Author(s):  
Ryotaro Nakamura ◽  
Yasue Mitsukura ◽  
Nozomu Hamada
Keyword(s):  
Blurred Image ◽  
Blind Restoration

Motion blurred image blind restoration base on parameter estimation of PSF

2014 ◽  
Vol 40 (3) ◽  
pp. 235-239 ◽  
Author(s):  
廖永忠 LIAO Yongzhong ◽  
蔡自兴 CAI Zixing ◽  
何湘华 HE Xianghua
Keyword(s):  
Parameter Estimation ◽  
Blurred Image ◽  
Blind Restoration

A Blind Restoration Approach for Defocused Barcode Images

2017 ◽  
Vol 8 (3) ◽  
pp. 41-58
Author(s):  
Shamik Tiwari
Keyword(s):  
Neural Network ◽  
Image Restoration ◽  
Radial Basis Function ◽  
Basis Function ◽  
Accurate Estimation ◽  
Robust Method ◽  
Ridgelet Transform ◽  
Accurate Representation ◽  
Blurred Image ◽  
Blind Restoration

Use of a mobile camera for barcode decoding provides high portability and availability but it requires that the recorded barcode image must be accurate representation of the barcode that is available on the product. Barcode scanning is challenging because images may be degraded due to out-of-focus blur at the time of image acquisition. Therefore, image restoration is essential in making image sharp and useful. In case of blind restoration of such barcode images accurate estimation of out-of-focus blur parameter is highly desirable. In this article, a robust method has been proposed for estimating the radius of out-of-focus blur. Finite discrete ridgelet transform has been used to find the features of the blurred image and a radial basis function neural network is utilized to estimate the radius of out-of-focus blur. The experimental results reveal that proposed method more robust than the existing methods.

scholarly journals No-Reference Digital Image Quality Assessment Based on Structure Similarity

2021 ◽  
Author(s):  
Basma Ahmed ◽  
Mohamed Abdel-Nasser ◽  
Osama A. Omer ◽  
Amal Rashed ◽  
Domenec Puig
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Similarity Index ◽  
Structural Similarity ◽  
Structural Similarity Index ◽  
Spectral Kurtosis ◽  
Blurred Image ◽  
Blind Restoration ◽  
Index Measure

Blind or non-referential image quality assessment (NR-IQA) indicates the problem of evaluating the visual quality of an image without any reference, Therefore, the need to develop a new measure that does not depend on the reference pristine image. This paper presents a NR-IQA method based on restoration scheme and a structural similarity index measure (SSIM). Specifically, we use blind restoration schemes for blurred images by reblurring the blurred image and then we use it as a reference image. Finally, we use the SSIM as a full reference metric. The experiments performed on standard test images as well as medical images. The results demonstrated that our results using a structural similarity index measure are better than other methods such as spectral kurtosis-based method.

Blind restoration of camera shake blurred image based on L0 sparse priors

2017 ◽  
Vol 25 (9) ◽  
pp. 2490-2498 ◽  
Author(s):  
仇 翔 QIU Xiang ◽  
戴 明 DAI Ming
Keyword(s):  
Camera Shake ◽  
Blurred Image ◽  
Blind Restoration ◽  
Sparse Priors
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