Measurement of digital photographic image quality : survey of psychophysics just noticeable threshold difference method
- Pierre, Lindeque, Nel, Andre, Robinson, Philip
- Authors: Pierre, Lindeque , Nel, Andre , Robinson, Philip
- Date: 2016
- Subjects: Image quality , Local psychophysics , JND
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/217056 , uj:21592 , Citation: Pierre, L., Nel, A. & Robinson, P. 2016. Measurement of digital photographic image quality : survey of psychophysics just noticeable threshold difference method.
- Description: Abstract: The modeling and quantification of digital photographic image quality has, from a psychophysics perspective, traditionally followed two paths, one of which is the discriminable small or just noticeable difference (local psychophysics) as detected in an image pair; further extended to cover a wide range of attribute artefactual quality variation. This method has its roots in the mathematical and psychological modeling of psychophysics and boasts a long history starting with the work of researchers such as Bernoulli, Weber and Fechner (18th, 19th century). The method models human perception of difference as a full scale logarithmic law and will be surveyed for its value in the determination of the quantitative quality of digital images.
- Full Text:
- Authors: Pierre, Lindeque , Nel, Andre , Robinson, Philip
- Date: 2016
- Subjects: Image quality , Local psychophysics , JND
- Language: English
- Type: Conference proceedings
- Identifier: http://hdl.handle.net/10210/217056 , uj:21592 , Citation: Pierre, L., Nel, A. & Robinson, P. 2016. Measurement of digital photographic image quality : survey of psychophysics just noticeable threshold difference method.
- Description: Abstract: The modeling and quantification of digital photographic image quality has, from a psychophysics perspective, traditionally followed two paths, one of which is the discriminable small or just noticeable difference (local psychophysics) as detected in an image pair; further extended to cover a wide range of attribute artefactual quality variation. This method has its roots in the mathematical and psychological modeling of psychophysics and boasts a long history starting with the work of researchers such as Bernoulli, Weber and Fechner (18th, 19th century). The method models human perception of difference as a full scale logarithmic law and will be surveyed for its value in the determination of the quantitative quality of digital images.
- Full Text:
Gaussian blur identification using scale-space theory
- Robinson, Philip, Roodt, Yuko, Nel, Andre
- Authors: Robinson, Philip , Roodt, Yuko , Nel, Andre
- Date: 2012
- Subjects: Blur identification , Blur estimation , Gaussian blur , Image deblurring algorithms , Scale-space theory
- Type: Article
- Identifier: http://ujcontent.uj.ac.za8080/10210/366248 , uj:6060 , ISBN 978-0-620-54601-0 , http://hdl.handle.net/10210/10475
- Description: Image deblurring algorithms generally assume that the nature of the blurring function that degraded an image is known before an image can be deblurred. In the case of most naturally captured images the strength of the blur present in the image is not known. This paper proposes a method to identify the standard deviation of a Gaussian blur that has been applied to a single image with no a priori information about the conditions under which the image was captured. This simple method makes use of a property of the Gaussian function and the Gaussian scale space representation of an image to identify the amount of blur. This is in contrast to the majority of statistical techniques that require extensive training or complex statistical models of the blur for identification.
- Full Text:
- Authors: Robinson, Philip , Roodt, Yuko , Nel, Andre
- Date: 2012
- Subjects: Blur identification , Blur estimation , Gaussian blur , Image deblurring algorithms , Scale-space theory
- Type: Article
- Identifier: http://ujcontent.uj.ac.za8080/10210/366248 , uj:6060 , ISBN 978-0-620-54601-0 , http://hdl.handle.net/10210/10475
- Description: Image deblurring algorithms generally assume that the nature of the blurring function that degraded an image is known before an image can be deblurred. In the case of most naturally captured images the strength of the blur present in the image is not known. This paper proposes a method to identify the standard deviation of a Gaussian blur that has been applied to a single image with no a priori information about the conditions under which the image was captured. This simple method makes use of a property of the Gaussian function and the Gaussian scale space representation of an image to identify the amount of blur. This is in contrast to the majority of statistical techniques that require extensive training or complex statistical models of the blur for identification.
- Full Text:
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