Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Camera electronics and image enhancement software for infrared detector arrays
Download
index.pdf
Date
2012
Author
Küçükkömürler, Alper
Metadata
Show full item record
Item Usage Stats
265
views
117
downloads
Cite This
This thesis aims to design and develop camera electronics and image enhancement software for infrared detector arrays. It first discusses the camera electronics suitable for infrared detector arrays, then it concentrates on image enhancement software that are implemented including defective pixel correction, contrast enhancement, noise reduction and pseudo coloring. After that, testing and results of the implemented algorithms were presented. Camera electronics and circuit operation frequency are selected considering the available standard programmable devices and the output rate of the detector readout circuitry. The target device for implementation of algorithms was Xilinx Spartan – 3 XC3S1500 which is used in the camera tests at METU-MEMS Research and Applications Center. Considering the real time operation, the target clocking frequency for operation of the circuitry was selected as 2MHz. Image enhancement algorithms primarily aim to be implemented for 320 x 240 resolution detectors, however with parametric implementation, they aim to support other resolutions, including 160 x 120 and 640 x 512. In addition, all implementations aim to be modular and reusable. Various different approaches are used for image enhancement software: (i) defective pixel correction is achieved by using a selective median filtering approach, (ii) contrast enhancement is achieved by employing contrast stretching and histogram based methods, and (iii) noise reduction is achieved by implementing a spatial filter. In addition to these, four types of pseudo coloring methods were applied and tested. Test results show that defective pixel correction algorithm operates at 20.0 MHz, with 0.0 x 10-3 RMS error from its MATLAB prototype, and contrast enhancement algorithms are able to operate at 3.3 MHz, with an average of 545.0 x 10-3 RMS error. Spatial filtering for noise reduction operates at 20.0 MHz, with a 2.6 x 10-3 RMS. Pseudo-coloring operates at 125.0 MHz, with a 0.0 x 10-3 RMS deviation from its MATLAB prototype,
Subject Keywords
Image processing
URI
http://etd.lib.metu.edu.tr/upload/12614106/index.pdf
https://hdl.handle.net/11511/21412
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
A Shadow based trainable method for building detection in satellite images
Dikmen, Mehmet; Halıcı, Uğur; Department of Geodetic and Geographical Information Technologies (2014)
The purpose of this thesis is to develop a supervised building detection and extraction algorithm with a shadow based learning method for high-resolution satellite images. First, shadow segments are identified on an over-segmented image, and then neighboring shadow segments are merged by assuming that they are cast by a single building. Next, these shadow regions are used to detect the candidate regions where buildings most likely occur. Together with this information, distance to shadows towards illuminati...
Thermal Infrared Hyperspectral Dimension Reduction Experiment Results For Global And Local Information Based Linear Discriminant Analysis
Sakarya, Ufuk (2015-05-19)
Thermal infrared hyperspectral image processing has become an important research topic in remote sensing. One of the research topics in thermal infrared hyperspectral image classification is dimension reduction. In this paper, thermal infrared hyperspectral dimension reduction experiment results for global and local information based linear discriminant analysis is presented. Advantages of the use of not only global pattern information, but also local pattern information are tested in thermal infrared hyper...
Alignment of uncalibrated images for multi-view classification
Arık, Sercan Ömer; Vural, Elif; Frossard, Pascal (2011-12-29)
Efficient solutions for the classification of multi-view images can be built on graph-based algorithms when little information is known about the scene or cameras. Such methods typically require a pairwise similarity measure between images, where a common choice is the Euclidean distance. However, the accuracy of the Euclidean distance as a similarity measure is restricted to cases where images are captured from nearby viewpoints. In settings with large transformations and viewpoint changes, alignment of im...
Vibration-based damage identification in beam-like composite laminates by using artificial neural networks
Şahin, Melin (SAGE Publications, 2003-01-01)
This paper investigates the effectiveness of the combination of global (changes in natural frequencies) and local (curvature mode shapes) vibration-based analysis data as input for artificial neural networks (ANNs) for location and severity prediction of damage in fibre-reinforced plastic laminates. A finite element analysis tool has been used to obtain the dynamic characteristics of intact and damaged cantilever composite beams for the first three natural modes. Different damage scenarios have been introdu...
Image resolution enhancement using wavelet domain Hidden Markov Tree and coefficient sign estimation
Temizel, Alptekin (2007-01-01)
Image resolution enhancement using wavelets is a relatively new subject and many new algorithms have been proposed recently. These algorithms assume that the low resolution image is the approximation subband of a higher resolution image and attempts to estimate the unknown detail coefficients to reconstruct a high resolution image. A subset of these recent approaches utilized probabilistic models to estimate these unknown coefficients. Particularly, hidden Markov tree (HMT) based methods using Gaussian mixt...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
A. Küçükkömürler, “Camera electronics and image enhancement software for infrared detector arrays,” M.S. - Master of Science, Middle East Technical University, 2012.