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IEEE Transactions on Image Processing, 2006
We propose the concept of quality-aware image, in which certain extracted features of the original (high-quality) image are embedded into the image data as invisible hidden messages. When a distorted version of such an image is received, users can decode the hidden messages and use them to provide an objective measure of the quality of the distorted ...
Zhou Wang 0001 +5 more
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We propose the concept of quality-aware image, in which certain extracted features of the original (high-quality) image are embedded into the image data as invisible hidden messages. When a distorted version of such an image is received, users can decode the hidden messages and use them to provide an objective measure of the quality of the distorted ...
Zhou Wang 0001 +5 more
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Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2002
Summary form only given. Image quality research traditionally focuses on the subjective measurement, prediction, or improvement of image quality. The fundamental question of what image quality is, however, has been given surprisingly little attention.
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Summary form only given. Image quality research traditionally focuses on the subjective measurement, prediction, or improvement of image quality. The fundamental question of what image quality is, however, has been given surprisingly little attention.
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The semantics of image quality
Color and Imaging Conference, 1997Using an "infonnation-processing" approach we give a semantic description of image quality. Experimental evidence for this description, which allows one to meaningfully characterize the quality of an image as the degree to whieh the image can be successfully exploited by the observer, will be discussed.
Janssen, T.J.W.M., Blommaert, F.J.J.
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Clinical Physics and Physiological Measurement, 1990
The measurement of image quality is an essential stage in the evaluation of imaging techniques. Yet there is no accepted way of quantitatively assessing image quality. Current theories suggest that the quality of the raw data acquired by the device can be assessed independently from that of the displayed image.
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The measurement of image quality is an essential stage in the evaluation of imaging techniques. Yet there is no accepted way of quantitatively assessing image quality. Current theories suggest that the quality of the raw data acquired by the device can be assessed independently from that of the displayed image.
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Computers & Chemical Engineering, 2009
Abstract Process monitoring using imaging can provide valuable information. However, the large number of images obtained necessitate automated classification into those showing “good” and “bad” product. This paper shows how a database of reference images can be used to modify image quality so as to obtain extremely high classification accuracies. The
Shuo Yan, Saed Sayad, Stephen T. Balke
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Abstract Process monitoring using imaging can provide valuable information. However, the large number of images obtained necessitate automated classification into those showing “good” and “bad” product. This paper shows how a database of reference images can be used to modify image quality so as to obtain extremely high classification accuracies. The
Shuo Yan, Saed Sayad, Stephen T. Balke
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An image quality measure for image communication
SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483), 2004In this paper, we propose an image quality measure that closely resembles the image quality measure used by the human visual system. In our application, we are more concerned with localized errors due to transmission than the global errors due to compression, and we develop an approach that is appropriate for this purpose.
Mohamed Bingabr +2 more
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2019
Deep learning with Convolutional Neural Networks (CNN) requires large number of training and test data sets which involves usually time-consuming visual inspection of medical image data. Recently, crowdsourcing methods have been proposed to gain such large training sets from untrained observers.
Medha Juneja +8 more
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Deep learning with Convolutional Neural Networks (CNN) requires large number of training and test data sets which involves usually time-consuming visual inspection of medical image data. Recently, crowdsourcing methods have been proposed to gain such large training sets from untrained observers.
Medha Juneja +8 more
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Evaluation of image quality in tomographic imaging
Physics in Medicine & Biology, 1977Modulation Transfer Functions (MTF) for tomographic imaging with linear, circular, hypocycloidal and spiral motion are given. They may be determined experimentally from tomographs of slits or line pair test patterns. In some cases calculation of the MTF from the blur pattern by Fourier transformation is possible.
M, Wolf, A, Stargardt, W, Angerstein
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Applied Optics, 1967
The steps in reproducing evaporograph images are discussed. An analysis of signal and noise is given for different stages of the evaporograph process. The factors which limit the threshold sensitivity and resolving power of the evaporograph transducer are determined.
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The steps in reproducing evaporograph images are discussed. An analysis of signal and noise is given for different stages of the evaporograph process. The factors which limit the threshold sensitivity and resolving power of the evaporograph transducer are determined.
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Linear discriminants and image quality
Image and Vision Computing, 1992The use of linear discriminant functions, and particularly a discriminant function derived from the work of Harold Hotelling, as a means of assessing image quality is reviewed. The relevant theory of ideal or Bayesian observers is briefly reviewed, and the circumstances under which this observer reduces to a linear discriminant are discussed.
Harrison H. Barrett +5 more
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