DIRECTIONALLY ADAPTIVE SUPER-RESOLUTION

Date

2009-11-10

Author

Turgay, Emre
Akar, Gözde

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

226
views

0
downloads

In this paper a novel direction adaptive super-resolution (SR) image reconstruction method is proposed. The proposed maximum a-posteriori (MAP) based estimator uses gradient direction for optimal noise reduction while preserving the edges. Compared to the other edge-preserving methods, the proposed algorithm uses gradient direction in addition to the gradient amplitude for optimum regularization. The method comprises a gradient amplitude and direction estimation stage where a gradient direction map is obtained. This map guides the SR reconstruction stage through iterations. Three variations of the proposed method are compared against other edge-preserving super resolution methods. PSNR (Peak signal-to-noise-ratio), SSIM (Structural similarity index measure) values, and illustrations show that the proposed method has better performance especially on image pixel values where a strong gradient is present.

Subject Keywords

Maximum a-posteriori, Gradient, Directional regularization, Edge preservation, Super-resolution

URI

https://hdl.handle.net/11511/47764

DOI

https://doi.org/10.1109/icip.2009.5413662

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Direction Adaptive Super-Resolution Imaging Turgay, Emre; Akar, Gözde (2009-04-11) In this paper a novel edge-presenting super-resolution (SR) image reconstruction method is proposed. The proposed maximum a-posteriori (MAP) based estimator uses gradient direction and amount for optimal noise reduction while presenting the edges. Compared to the other edge-presenting methods, the proposed algorithm uses the gradient direction for optimum regularization. The proposed method estimates gradient amplitude and direction at each iteration. This gradient map guides the SR reconstruction stage thr...
Exploitation of multi-camera configurations for visual surveillance Akman, Oytun; Alatan, Abdullah Aydın; Çiloğlu, Tolga (2008-06-20) In this paper, we propose novel methods for background modeling, occlusion. handling and event recognition by using multi-camera configurations. Homography-related positions are utilized to construct a mixture of multivariate Gaussians to generate a background model for each pixel of the reference camera. Occlusion handling is achieved by generation of the top-view via trifocal tensors, as a result of matching over-segmented regions instead of pixels. The resulting graph is segmented into objects after dete...
Spatial control of a smart beam Kircali, Omer Faruk; Yaman, Yavuz; Nalbantoglu, Volkan; Şahin, Melin; Karadal, Fatih Mutlu; Ulker, Fatma Demet (2008-08-01) This study presents the design and implementation of a spatial H(infinity) controller for the active vibration control of a smart beam. The smart beam was modeled by assumed-modes method that results in a model including large number of resonant modes. The order of the model was reduced by direct model truncation and the model correction technique was applied to compensate the effect of the contribution of the out of range modes to the dynamics of the system. Additionally, spatial identification of the beam...
GEOMETRY-CONSTRAINED SPATIAL PYRAMID ADAPTATION FOR IMAGE CLASSIFICATION Tasli, H. Emrah; Sicre, Ronan; Gevers, Theo; Alatan, Abdullah Aydın (2014-10-30) This paper proposes a geometry-constrained spatial pyramid adaptation approach for the image classification task. Scene geometry is used as an input parameter for generating the spatial pyramid definitions. The resulting region adaptation is performed in accordance with the predefined geometric guidelines and underlying image characteristics. Using an approximate global geometric correspondence, exploits the idea that images of the same category share a spatial similarity. This assumption is evaluated and j...
Piecewise-planar 3D reconstruction in rate-distortion sense Imre, Evren; Gueduekbay, Ugur; Alatan, Abdullah Aydın (2007-05-09) In this paper, a novel rate-distortion optimization inspired 3D piecewise-planar reconstruction algorithm is proposed. The algorithm refines a coarse 3D triangular mesh, by inserting vertices in a way to minimize the intensity difference between an image and its prediction. The preliminary experiments on synthetic and real data indicate the validity of the proposed approach.

Citation Formats

E. Turgay and G. Akar, “DIRECTIONALLY ADAPTIVE SUPER-RESOLUTION,” 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47764.