Blur estimation and superresolution from multiple registered images

Download

index.pdf

Date

2008

Author

Şenses, Engin Utku

Metadata

Show full item record

Item Usage Stats

120
views

45
downloads

Resolution is the most important criterion for the clarity of details on an image. Therefore, high resolution images are required in numerous areas. However, obtaining high resolution images has an evident technological cost and the value of these costs change with the quality of used optical systems. Image processing methods are used to obtain high resolution images with low costs. This kind of image improvement is named as superresolution image reconstruction. This thesis focuses on two main titles, one of which is the identification methods of blur parameters, one of the degradation operators, and the stochastic SR image reconstruction methods. The performances of different stochastic SR image reconstruction methods and blur identification methods are shown and compared. Then the identified blur parameters are used in superresolution algorithms and the results are shown.

Subject Keywords

Electrical engineering., Computer Hardware.

URI

http://etd.lib.metu.edu.tr/upload/3/12609929/index.pdf
https://hdl.handle.net/11511/18104

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Video shot boundary detection by graph theoretic approaches Aşan, Emrah; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2008) This thesis aims comparative analysis of the state of the art shot boundary detection algorithms. The major methods that have been used for shot boundary detection such as pixel intensity based, histogram-based, edge-based, and motion vectors based, are implemented and analyzed. A recent method which utilizes “graph partition model” together with the support vector machine classifier as a shot boundary detection algorithm is also implemented and analyzed. Moreover, a novel graph theoretic concept, “dominant...
Noise reduction in high dynamic range imaging Akyüz, Ahmet Oğuz (Elsevier BV, 2007-10-01) A common method to create high dynamic range (HDR) images is to combine several different exposures of the same scene. In this approach, the use of higher ISO settings will reduce exposure times, and thereby the total capture time. This is advantageous in certain environments where it may help minimize ghosting artifacts. However, exposures taken at high sensitivity settings tend to be noisy, which is further amplified by the HDR creation algorithm. We present a robust and efficient technique to significant...
User directed view synthesis on omap processors Yıldız, Mürsel; Akar, Gözde; Department of Electrical and Electronics Engineering (2009) In this thesis, real time image rendering for hand held devices is studied according to user’s view point choice and using image frames with corresponding depth maps obtained from 2 different cameras, of which positions on coordinate system is known. User’s view point choice is restricted to the area between right, and left cameras. Occlusion handling methods for image rendering systems is explored and discussed together with frame enhancement techniques. Median filtering is studied for multicolor image fra...
Texture and edge preserving multiframe super-resolution Turgay, Emre; Akar, Gözde (Institution of Engineering and Technology (IET), 2014-09-01) Super-resolution (SR) image reconstruction refers to methods where a higher resolution image is reconstructed using a set of overlapping aliased low-resolution observations of the same scene. Although edge preservation has been a widely explored topic in SR literature, texture-specific regularisation has recently gained interest. In this study, texture-specific regularisation is handled as a post-processing step. A two stage method is proposed, comprising multiple SR reconstructions with different regularis...
3d geometric hashing using transform invariant features Eskizara, Ömer; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2009) 3D object recognition is performed by using geometric hashing where transformation and scale invariant 3D surface features are utilized. 3D features are extracted from object surfaces after a scale space search where size of each feature is also estimated. Scale space is constructed based on orientation invariant surface curvature values which classify each surface point's shape. Extracted features are grouped into triplets and orientation invariant descriptors are defined for each triplet. Each pose of eac...

Citation Formats

E. U. Şenses, “Blur estimation and superresolution from multiple registered images,” M.S. - Master of Science, Middle East Technical University, 2008.