Camera electronics and image enhancement software for infrared detector arrays

Küçükkömürler, Alper
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,


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...
Kilickaya, Mert; Erdem, Erkut; Erdem, Aykut; İKİZLER CİNBİŞ, NAZLI; Çakıcı, Ruket (2014-04-25)
Automatic image captioning, the process cif producing a description for an image, is a very challenging problem which has only recently received interest from the computer vision and natural language processing communities. In this study, we present a novel data-driven image captioning strategy, which, for a given image, finds the most visually similar image in a large dataset of image-caption pairs and transfers its caption as the description of the input image. Our novelty lies in employing a recently' pr...
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...
Optical flow based video frame segmentation and segment classification
Akpınar, Samet; Alpaslan, Ferda Nur; Department of Computer Engineering (2018)
Video information retrieval is a field of multimedia research enabling us to extract desired semantic information from video data. In content-based video information retrieval, visual content obtained from video scenes is utilized. For developing methods to cope with content-based video information retrieval in terms of temporal concepts such as action, event, etc., representation of temporal information becomes critical. In this thesis, action detection is tackled based on a temporal video representation m...
Citation Formats
A. Küçükkömürler, “Camera electronics and image enhancement software for infrared detector arrays,” M.S. - Master of Science, Middle East Technical University, 2012.