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IEEE Signal Processing Letters, ISSN 1070-9908, 06/2014, Volume 21, Issue 6, pp. 751 - 755
Journal Article
IEEE Transactions on Multimedia, ISSN 1520-9210, 08/2016, Volume 18, Issue 8, pp. 1568 - 1578
Journal Article
Journal of Visual Communication and Image Representation, ISSN 1047-3203, 01/2018, Volume 50, pp. 145 - 158
•A blind image sharpness assessment model based on local contrast maps is proposed.•The higher dynamic range of contrast maps significantly improves... 
Wavelet | Image quality assessment | Dynamic range | No-reference | Percentile | Contrast | COMPUTER SCIENCE, SOFTWARE ENGINEERING | PHASE | COMPUTER SCIENCE, INFORMATION SYSTEMS | QUALITY ASSESSMENT | Electrical engineering | Algorithms | Image processing | Analysis | Equipment and supplies | Statistics | Computer programs
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 04/2009, Volume 18, Issue 4, pp. 717 - 728
Journal Article
IEEE Transactions on Image Processing, ISSN 1057-7149, 09/2011, Volume 20, Issue 9, pp. 2678 - 2683
Journal Article
Procedia Engineering, ISSN 1877-7058, 2013, Volume 64, pp. 149 - 158
One of the most challenging problems for researchers in the field of image processing is image quality assessment. A very important factor in image quality... 
Image Sharpness | Image Quality | No-reference image Quality | Blurring | Frequency Domain Image processing
Conference Proceeding
2007 IEEE International Conference on Image Processing, ISSN 1522-4880, 09/2007, Volume 1, pp. I - 397 - I - 400
Powerful digital media editing tools make producing good quality forgeries very easy for almost anyone. Therefore, proving the authenticity and integrity of... 
Wavelet transforms | Forgery Detection | Law | Digital images | Image processing | Image Authentication | Watermarking | Statistics | Authentication | Digital Forensics | Cameras | Robustness | Forgery | Regularity | Digital forensics | Forgery detection | Image authentication
Conference Proceeding
Journal of Visual Communication and Image Representation, ISSN 1047-3203, 11/2017, Volume 49, pp. 382 - 391
•Our method outperforms most recently proposed NR metrics and state-of-the-art blind sharpness/blurriness measures.•Our method is inspired by the piece-wise... 
Blurriness/sharpness | Image quality assessment (IQA) | No reference (NR) | Local binary pattern (LBP) | COMPUTER SCIENCE, SOFTWARE ENGINEERING | COMPUTER SCIENCE, INFORMATION SYSTEMS | CLASSIFICATION | QUALITY ASSESSMENT | Analysis | Models | Algorithms
Journal Article
2008 15th IEEE International Conference on Image Processing, ISSN 1522-4880, 10/2008, pp. 401 - 404
The computation of existing sharpness/blurriness objective metrics involves measuring the spread of edge pixels in blurred images. However, in blurred images,... 
Real time systems | Availability | Image edge detection | HVS | Image quality | Histograms | Objective | Sharpness Metric | Accuracy | Edge Detection | Electric variables measurement | Video compression | Perception | Iterative algorithms | Pixel | Edge detection | Sharpness metric
Conference Proceeding
2007 IEEE International Conference on Image Processing, ISSN 1522-4880, 09/2007, Volume 3, pp. III - 445 - III - 448
This work presents a perceptual-based no-reference objective image sharpness/blurriness metric by integrating the concept of just noticeable blur (JNB) into a... 
Costs | Digital images | HVS | Extraterrestrial measurements | Biomedical measurements | Image quality | Image sensors | Image Assessment | No-reference | Objective | Sharpness Metric | Video compression | Perception | Image enhancement | Monitoring | Testing | Image assessment | Sharpness metric
Conference Proceeding
Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science), ISSN 1008-973X, 02/2014, Volume 48, Issue 2, pp. 312 - 320
This paper presented a novel no-reference sharpness/blurriness metric due to its importance in image, video applications. Based on the principle that image... 
No-reference | Histogram | Edge width | Image sharpness | Distance factor | Histograms | Algorithms | Images | Spreads | Mathematical models | Sharpness | Gain
Journal Article
2010 IEEE International Conference on Image Processing, ISSN 1522-4880, 09/2010, pp. 1553 - 1556
This work presents a semantic level no-reference image sharpness/blurriness metric under the guidance of top-down & bottom-up saliency map, which is learned... 
Measurement | Image quality | Visualization | No-reference | Image edge detection | Conferences | Top-down & bottom-up saliency map | Semantics | Image quality assessment | Pixel
Conference Proceeding
IEEE International Conference on Image Processing 2005, ISSN 1522-4880, 2005, Volume 1, pp. I - 405
Conference Proceeding
11/2018
Described is a method and apparatus to accelerate rendering of 3D graphics images. When rendering, the transformation matrix (or equivalent) used for... 
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL | COMPUTING | COUNTING | PHYSICS | CALCULATING
Patent
07/2017
Described is a method and apparatus to accelerate rendering of 3D graphics images. When rendering, the transformation matrix (or equivalent) used for... 
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL | COMPUTING | COUNTING | PHYSICS | CALCULATING
Patent
01/2007, ISBN 0549309454, Volume 68, Issue 11
The Human Visual System (HVS) behavior is investigated and its response to different amount of blur in an image is studied. A no-reference objective... 
Algorithms | Thresholds | Images | Mathematical models | Sharpness | Texture | Pixels | Visual
Book Chapter
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