Ahmet Akyuz | Middle East Technical University (original) (raw)

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Papers by Ahmet Akyuz

Research paper thumbnail of Color appearance models and dynamic range reduction

Proceedings of the 1st Symposium on Applied perception in graphics and visualization - APGV '04, 2004

Research paper thumbnail of A reality check for radiometric camera response recovery algorithms

Research paper thumbnail of Robust generation of high dynamic range images

Research paper thumbnail of Evaluating deghosting algorithms for HDR images

2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014

ABSTRACT The real world encompasses a high range of luminances. In order to capture and represent... more ABSTRACT The real world encompasses a high range of luminances. In order to capture and represent this range correctly, High Dynamic Range (HDR) imaging techniques are introduced. Some of these techniques are based on constructing an HDR image from several Low Dynamic Range (LDR) images with different exposures. In the capture and reconstruction phases, the HDR reproduction techniques must resolve the differences between the input LDR images due to camera and object movement. In this study, two recent approaches addressing this issue are compared using a novel dataset comprised of image sequences with varying complexity. The results are evaluated by using both objective and subjective measures.

Research paper thumbnail of Evaluation of radiometric camera response recovery methods

SIGGRAPH Asia 2011 Posters on - SA '11, 2011

The camera response function determines the relationship between the incident light on the camera... more The camera response function determines the relationship between the incident light on the camera sensor and the output pixel values that are produced. For most consumer cameras, this function is proprietary and needs to be estimated to create HDR images that accurately represent the light distribution of the captured scene. Several methods have been proposed in the literature to estimate

Research paper thumbnail of Ghost Removal in High Dynamic Range Images

2006 International Conference on Image Processing, 2006

Research paper thumbnail of Rendering

Research paper thumbnail of Noise reduction in high dynamic range imaging

Journal of Visual Communication and Image Representation, 2007

Research paper thumbnail of Color appearance in high-dynamic-range imaging

Journal of Electronic Imaging, 2006

Research paper thumbnail of Perceptual evaluation of tone-reproduction operators using the Cornsweet--Craik--O'Brien illusion

ACM Transactions on Applied Perception, 2008

Research paper thumbnail of Do HDR displays support LDR content?

ACM Transactions on Graphics, 2007

Research paper thumbnail of Real-time color blending of rendered and captured video

Augmented reality involves mixing captured video with rendered elements in real-time. For augment... more Augmented reality involves mixing captured video with rendered elements in real-time. For augmented reality to be effective in training and simulation applications, the computer generated c omponents need to blend in well with the captured video. Straightforward compositing is not sufficient, since the chromatic content of video and rendered data may be very different such that it is immediately obvious

Research paper thumbnail of Color appearance models and dynamic range reduction

Proceedings of the 1st Symposium on Applied perception in graphics and visualization - APGV '04, 2004

Research paper thumbnail of A reality check for radiometric camera response recovery algorithms

Research paper thumbnail of Robust generation of high dynamic range images

Research paper thumbnail of Evaluating deghosting algorithms for HDR images

2014 22nd Signal Processing and Communications Applications Conference (SIU), 2014

ABSTRACT The real world encompasses a high range of luminances. In order to capture and represent... more ABSTRACT The real world encompasses a high range of luminances. In order to capture and represent this range correctly, High Dynamic Range (HDR) imaging techniques are introduced. Some of these techniques are based on constructing an HDR image from several Low Dynamic Range (LDR) images with different exposures. In the capture and reconstruction phases, the HDR reproduction techniques must resolve the differences between the input LDR images due to camera and object movement. In this study, two recent approaches addressing this issue are compared using a novel dataset comprised of image sequences with varying complexity. The results are evaluated by using both objective and subjective measures.

Research paper thumbnail of Evaluation of radiometric camera response recovery methods

SIGGRAPH Asia 2011 Posters on - SA '11, 2011

The camera response function determines the relationship between the incident light on the camera... more The camera response function determines the relationship between the incident light on the camera sensor and the output pixel values that are produced. For most consumer cameras, this function is proprietary and needs to be estimated to create HDR images that accurately represent the light distribution of the captured scene. Several methods have been proposed in the literature to estimate

Research paper thumbnail of Ghost Removal in High Dynamic Range Images

2006 International Conference on Image Processing, 2006

Research paper thumbnail of Rendering

Research paper thumbnail of Noise reduction in high dynamic range imaging

Journal of Visual Communication and Image Representation, 2007

Research paper thumbnail of Color appearance in high-dynamic-range imaging

Journal of Electronic Imaging, 2006

Research paper thumbnail of Perceptual evaluation of tone-reproduction operators using the Cornsweet--Craik--O'Brien illusion

ACM Transactions on Applied Perception, 2008

Research paper thumbnail of Do HDR displays support LDR content?

ACM Transactions on Graphics, 2007

Research paper thumbnail of Real-time color blending of rendered and captured video

Augmented reality involves mixing captured video with rendered elements in real-time. For augment... more Augmented reality involves mixing captured video with rendered elements in real-time. For augmented reality to be effective in training and simulation applications, the computer generated c omponents need to blend in well with the captured video. Straightforward compositing is not sufficient, since the chromatic content of video and rendered data may be very different such that it is immediately obvious

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