Klamer Schutte - Academia.edu (original) (raw)
Papers by Klamer Schutte
Emerging Imaging and Sensing Technologies for Security and Defence IV
ACM Transactions on Multimedia Computing, Communications, and Applications
Multimedia Tools and Applications
Proceedings of the 17th International Conference on Pattern Recognition 2004 Icpr 2004, Aug 23, 2004
Ned Tijdschr Geneeskd, 2003
Ieee Transactions on Instrumentation and Measurement February 1 56 199 203, Feb 1, 2007
Proceedings of the 21st International Conference on Pattern Recognition, 2012
Proceedings Icip International Conference on Image Processing, Aug 11, 2002
Ipas, 2005
ABSTRACT This paper presents a method to predict the limit of possible resolution enhancement,giv... more ABSTRACT This paper presents a method to predict the limit of possible resolution enhancement,given a sequence of lowresolution images. Three important parameters influence the outcome of this limit: the total Point Spread Function (PSF), the Signal-to-Noise Ratio (SNR) and the number of input images. Although a large number of input images captured by a system with a narrow PSF and a high SNR are desirable, these conditions are often not achievable simultaneously. To improve the SNR, cameras are designed with near optimal quantum efficiency and maximum fill-factor. However, the latter widens the system PSF, which puts more weight on the deblurring part of a super-resolution (SR) reconstruction algorithm. This paper analyzes the contribution of each input parameters to the SR reconstruction and predicts the best attainable SR factor for given a camera setting. The predicted SR factor agrees well with an edge sharpness measure computed from the reconstructed SR images. A sufficient number of randomly positioned input images to achieve this limit for a given scene can also be derived assuming Gaussian noise and registration errors. Keywords: super-resolution limit, fill-factor, under-sampling, deconvolution limit, registration error.
4Th International Symposium on Optronics in Defense and Security Optro 2010 3 5 February Paris France, 2010
Method of improving the resolution of a small moving object in a digital image sequence comprises... more Method of improving the resolution of a small moving object in a digital image sequence comprises the steps of: constructing (101) a high-resolution image background model, detecting (102) the moving object using the high-resolution image background model, fitting (103) a model-based trajectory for object registration, and producing (104) a high-resolution object description. The step of producing a high-resolution object description involves an iterative optimisation of a cost function (109) based upon a polygonal model of an edge of the moving object. The cost function is preferably also based upon a high resolution intensity description. The iterative optimisation of the cost function may involve a polygon description parameter and/or an intensity parameter
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXIV, 2013
Optical Engineering
Linear polarization of thermal infrared (TIR) radiation occurs when radiation is reflected or emi... more Linear polarization of thermal infrared (TIR) radiation occurs when radiation is reflected or emitted from a smooth surface (such as the top of a landmine) and observed from a grazing angle. The background (soil and vegetation) is generally much rougher and therefore shows less pronounced linearly polarized radiation. This difference in polarization is utilized to enhance detection of landmines using TIR cameras. A setup has been constructed for the acquisition of polarized TIR images. This setup contains a polarization filter that rotates synchronously to the frame sync of the camera. Either a long wave infrared (LWIR) or a mid wave infrared (MWIR) camera can be mounted behind the rotating polarization filter. The synchronization allows a sequence of images to be taken with a predefined constant angle of rotation between the images. Using this image sequence, three independent Stokes images are calculated, consisting of the unpolarized radiance, the difference between vertically an...
The TOSO data is the (toy and office-supplies objects) dataset. It contains a set of 145 test ima... more The TOSO data is the (toy and office-supplies objects) dataset. It contains a set of 145 test images used for the GOOSE demonstrator as described in: "Interactive detection of incrementally learned concepts in images with ranking and semantic query interpretation", Klamer Schutte , Henri Bouma , John Schavemaker , Laura Daniele , Maya Sappelli, Gijs Koot , Pieter Eendebak , George Azzopardi , Martijn Spitters , Maaike de Boer , Maarten Kruithof , Paul Brandt To be published 13th International Workshop on Content-Based Multimedia Indexing (CBMI) June 10.-12. 2015, Prague, Czech Republic
Emerging Imaging and Sensing Technologies for Security and Defence IV
ACM Transactions on Multimedia Computing, Communications, and Applications
Multimedia Tools and Applications
Proceedings of the 17th International Conference on Pattern Recognition 2004 Icpr 2004, Aug 23, 2004
Ned Tijdschr Geneeskd, 2003
Ieee Transactions on Instrumentation and Measurement February 1 56 199 203, Feb 1, 2007
Proceedings of the 21st International Conference on Pattern Recognition, 2012
Proceedings Icip International Conference on Image Processing, Aug 11, 2002
Ipas, 2005
ABSTRACT This paper presents a method to predict the limit of possible resolution enhancement,giv... more ABSTRACT This paper presents a method to predict the limit of possible resolution enhancement,given a sequence of lowresolution images. Three important parameters influence the outcome of this limit: the total Point Spread Function (PSF), the Signal-to-Noise Ratio (SNR) and the number of input images. Although a large number of input images captured by a system with a narrow PSF and a high SNR are desirable, these conditions are often not achievable simultaneously. To improve the SNR, cameras are designed with near optimal quantum efficiency and maximum fill-factor. However, the latter widens the system PSF, which puts more weight on the deblurring part of a super-resolution (SR) reconstruction algorithm. This paper analyzes the contribution of each input parameters to the SR reconstruction and predicts the best attainable SR factor for given a camera setting. The predicted SR factor agrees well with an edge sharpness measure computed from the reconstructed SR images. A sufficient number of randomly positioned input images to achieve this limit for a given scene can also be derived assuming Gaussian noise and registration errors. Keywords: super-resolution limit, fill-factor, under-sampling, deconvolution limit, registration error.
4Th International Symposium on Optronics in Defense and Security Optro 2010 3 5 February Paris France, 2010
Method of improving the resolution of a small moving object in a digital image sequence comprises... more Method of improving the resolution of a small moving object in a digital image sequence comprises the steps of: constructing (101) a high-resolution image background model, detecting (102) the moving object using the high-resolution image background model, fitting (103) a model-based trajectory for object registration, and producing (104) a high-resolution object description. The step of producing a high-resolution object description involves an iterative optimisation of a cost function (109) based upon a polygonal model of an edge of the moving object. The cost function is preferably also based upon a high resolution intensity description. The iterative optimisation of the cost function may involve a polygon description parameter and/or an intensity parameter
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXIV, 2013
Optical Engineering
Linear polarization of thermal infrared (TIR) radiation occurs when radiation is reflected or emi... more Linear polarization of thermal infrared (TIR) radiation occurs when radiation is reflected or emitted from a smooth surface (such as the top of a landmine) and observed from a grazing angle. The background (soil and vegetation) is generally much rougher and therefore shows less pronounced linearly polarized radiation. This difference in polarization is utilized to enhance detection of landmines using TIR cameras. A setup has been constructed for the acquisition of polarized TIR images. This setup contains a polarization filter that rotates synchronously to the frame sync of the camera. Either a long wave infrared (LWIR) or a mid wave infrared (MWIR) camera can be mounted behind the rotating polarization filter. The synchronization allows a sequence of images to be taken with a predefined constant angle of rotation between the images. Using this image sequence, three independent Stokes images are calculated, consisting of the unpolarized radiance, the difference between vertically an...
The TOSO data is the (toy and office-supplies objects) dataset. It contains a set of 145 test ima... more The TOSO data is the (toy and office-supplies objects) dataset. It contains a set of 145 test images used for the GOOSE demonstrator as described in: "Interactive detection of incrementally learned concepts in images with ranking and semantic query interpretation", Klamer Schutte , Henri Bouma , John Schavemaker , Laura Daniele , Maya Sappelli, Gijs Koot , Pieter Eendebak , George Azzopardi , Martijn Spitters , Maaike de Boer , Maarten Kruithof , Paul Brandt To be published 13th International Workshop on Content-Based Multimedia Indexing (CBMI) June 10.-12. 2015, Prague, Czech Republic