METU Signal Processing Group

Signal processing group studies methods of processing information bearing signals for a particular aim. Signals can be one or multi-dimensional; deterministic or random. The goal can be restoration of a noise corrupted image, compression of a video sequence, generation of alternative viewpoint of a scene, optimal methods of decision under uncertainty (detection and estimation) and efficient usage of resources such as bandwidth, computation or time etc. Also: What is Signal Processing?, Signal Processing and Machine Learning, The Future of Signal Processing Symposium (playlist of youtube videos).

Signal processing tools are widely applied. Some applications are multimedia signal processing (speech, image and video processing), control theory, communications (statistical signal processing, detection/estimation theory), biomedical applications, radar-sonar problems and more.

Signal processing group at METU is specifically working on multimedia signal processing (all aspects), radar signal processing (including SAR imaging and STAP techniques), spectrum estimation techniques, direction of arrival estimation methods.

Signal Processing Courses on the Web:

Faculty Members

Emeritus Faculty Members

  • Severcan, Mete (Image processing, radar signal processing, communications)
  • Ünver, Zafer (Signal representation theory, statistical signal processing)

Research Labs

Related Labs

Description of Signal Processing Courses

Undergraduate Courses:
EE 230 : Introduction to probability. Required background for statistical signal processing.
EE 301 : Introduction to signal representation and transforms. Foundations
EE 306 : Random processes. Undergraduate level introduction, but fairly complete.
EE 430 : Digital Signal Processing.
EE 497 : Special Topics: Real-Time Applications of Digital Signal Processing
EE 499 : Special Topics: Vector Space Methods in Signal Processing

Graduate Courses:
EE 503 : Statistical Signal Processing and Modeling
EE 504 : Adaptive Filtering (Pre-requisite: 503)
EE 505 : Wavelets, Filterbanks, Time-Frequency Distributions (Advanced)
EE 531 : Probability and Stochastic Processes
EE 543 : Neurocomputers and Deep Learning
EE 583 : Pattern Recognition
EE 584 : Machine Vision
EE 603 : Spectrum Estimation (Advanced)
EE 604 : Sensor Array Signal Processing (Advanced)
EE 633 : Speech Processing
EE 634 : Image Processing
EE 636 : Video Processing
EE 732 : Probabilistic Graphical Models
EE 746 : Radar Signal Processing
EE 798 : Theory of Remote Image Formation
EE 5506 : Advanced Statistical Signal Processing (Pre-requisite: 503)

Related Courses

EE 501 : Linear System Theory I
EE 502 : Linear System Theory II
EE 533 : Information Theory
EE 553 : Optimization
EE 557 : Estimation Theory
EE 585 : Statistical Techniques in Mobile Robotics
EE 625 : Fundamentals of Radar Systems I
EE 626 : Fundamentals of Radar Systems II
EE 635 : Fourier Optics
EE 793 : Target Tracking
EE 5420 : Probabilistic Graphical Models


  • 2018, Vural E., Guillemot C., A Study of the Classification of Low-Dimensional Data with Supervised Manifold Learning, “Journal of Machine Learning Research”, vol.18.
  • 2018, Oktem S. F., Kamalabadi F., Davila J. M., Analytical Fresnel imaging models for photon sieves, “Optics Express”, 26, p.32259-32279.
  • 2018, Epcacan E., Ciloglu, T., A Hybrid Nonlinear Method for Array Thinning, “IEEE Transactions on Antennas and Propagation”, 66, p.2328-2325.
  • 2018, Gundogdu E., Alatan A., Good Features to Correlate for Visual Tracking, “IEEE Transactions on Image Processing”, 27, p.2526-2540.
  • 2018, Bayram E., Frossard P., Vural E., Alatan A., Analysis of Airborne LiDAR Point Clouds With Spectral Graph Filtering, “IEEE Geoscience and Remote Sensing Letters”, 15, p.1284-1288.
  • 2018, Solmaz B., Gundogdu E., Yucesoy V., Koc A. , Alatan A., Fine-grained recognition of maritime vessels and land vehicles by deep feature embedding, “IET Computer Vision”, 12, p.1121-1132.
  • 2018, O. Cayir, C. Candan, Performance Improvement of Time-Balance Radar Schedulers Through Decision Policies, “IEEE Transactions on Aerospace and Electronic Systems”, 54, p.1679-1691.
  • 2018, Erdemir E., E. Tuncer, Path planning for mobile-anchor based wireless sensor network localization: Static and dynamic schemes, “Ad Hoc Networks”, 77, p.1-10.
  • 2017, E. Tuncer, Ozlem Tuğfe Demir, Max–Min Fair Resource Allocation for SWIPT in Multi-Group Multicast OFDM Systems, “IEEE Communications Letters”, 21, p.2508-2511.
  • 2017, E. Tuncer, Ozlem Tuğfe Demir, Optimum QoS-Aware Beamformer Design for Full-Duplex Relay With Self-Energy Recycling, “IEEE Wireless Communications Letters”, 7, p.122-125.
  • 2017, Gundogdu, E., Ozkan, H., Alatan, A., Extending Correlation Filter-Based Visual Tracking by Tree-Structured Ensemble and Spatial Windowing, “IEEE Transactions on Image Processing”, 26 (11), pp. 5270-5283.
  • 2017, Oktem, F.S., Ozaktas, H.M., Effect of spatial distribution of partial information on the accurate recovery of optical wave fields, “Applied Optics”, 56 (1), pp. A133-A144.
  • 2017, Alici Kamil, Buyuk Hakan, Yilmaz Serdar, Ozdemir Ceyda, Karci Ozgur, Oktem F.S., Selimoglu O., Periodic aperture imaging, “Optical Engineering”, v. 56.
  • 2016, A. Koc, F. S. Oktem, H. M. Ozaktas, and M. A. Kutay, Chapter 9: Fast Algorithms for Digital Computation of Linear Canonical Transforms, “Linear canonical transforms: Theory and applications”, Springer-Verlag New York, p.197-239.
  • 2016, F. S. Oktem and H. M. Ozaktas, Chapter 7: Linear canonical domains and degrees of freedom of signals and systems, “Linear canonical transforms: Theory and applications”, Springer-Verlag New York, p.293-327.
  • 2016, J. C. Ferreira, E. Vural, C. Guillemot, Geometry-Aware Neighborhood Search for Learning Local Models for Image Reconstruction. “IEEE Transactions on Image Processing”, 25, p.1354-1367.
  • 2016, E. Vural, C. Guillemot, Out-of-Sample Generalizations for Supervised Manifold Learning for Classification. “IEEE Transactions on Image Processing”, 25, p.1410-1424.
  • 2016, Ahmet M. Elbir, T. Engin Tuncer, 2-D DOA and Mutual Coupling Coefficient Estimation for Arbitrary Array Structures With Single and Multiple Snapshots. “Digital Signal Processing”, 54, p.75-86.
  • 2016, Özlem Tuğfe Demir, T. Engin Tuncer, Antenna Selection and Hybrid Beamforming for Simultaneous Wireless Information and Power Transfer in Multi-Group Multicasting Systems. “IEEE Transactions on Wireless Communications”, 15, p.6948 – 6962.
  • 2016, Melih Günay, U. Orguner, Mübeccel Demirekler, Chernoff Fusion of Gaussian Mixtures Based on Sigma-Point Approximation. “IEEE Transactions on Aerospace and Electronic Systems”, 52, p.2732 – 2746.
  • 2016, Saeed Ranjbar Alvar, F. Kamisli, On lossless intra coding in HEVC with 3-tap filters. “Signal Processing: Image Communication”, 47, p.252-262.
  • 2016, F. Kamisli, A low-complexity image compression approach with single spatial prediction mode and transform. “Signal, Image and Video Processing”, 10, p.1409-1416.
  • 2016, M. Ispir, C. Candan, On the design of staggered moving target indicator filters. “IET Radar, Sonar & Navigation”, 10, p.205-215
  • 2016, Neslihan Y. Bayramoglu and A.Aydin Alatan, Comparison of 3D local and global descriptors for similarity retrieval of range data. “Neurocomputing”, 184, p.13-27.
  • 2016, O. Kumtepe, G. B. Akar, E. Yuncu, Driver aggressiveness detection via multisensory data fusion. “EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING”, 5, p.1-16.
  • 2016, Turgay Koç, T. Çiloğlu, Nonlinear Interactive Source-Filter Models for Speech, “Computer Speech & Language”, 36, p. 365-394.
  • 2015, Özlem Tuğfe Demir, T. Engin Tuncer, Optimum Discrete Transmit Beamformer Design. “Digital Signal Processing”, 36, p.57-68.
  • 2015, Özlem Tuğfe Demir, T. Engin Tuncer, Optimum Discrete Phase-Only Multicast Beamforming With Joint Antenna And User Selection In Cognitive Radio Networks. “Digital Signal Processing”, 46, p.81-96.
  • 2015, T. Ardeshiri, K. Granström, E. Özkan, U. Orguner, Greedy Reduction Algorithms for Mixtures of Exponential Family. “IEEE Signal Processing Letters”, Cilt 22.
  • 2015, T. Ardeshiri, E. Özkan, U. Orguner, F. Gustafsson, Approximate Bayesian Smoothing with Unknown Process and Measurement Noise Covariances. “IEEE Signal Processing Letters”, Cilt 22.
  • 2015, Fatih Kamisli, Block-Based Spatial Prediction and Transforms Based on 2D Markov Processes for Image and Video Compression. “IEEE Transactions on Image Processing”, 24, p.1247-1260.
  • 2015, Burcu Karasoy, Fatih Kamisli, Multiview video compression with 1-D transforms. “Signal Processing: Image Communication”, p.14-28.
  • 2015, C. Candan, Fine resolution frequency estimation from three DFT samples: Case of windowed data. “Elsevier Signal Processing”, 114, p.245-250.
  • 2015, C. Candan, S. Koç, Direction finding accuracy of sequential lobing under target amplitude fluctuations. “IET Radar, Sonar & Navigation”, 9, p.92-103.
  • 2015, H. Emrah Tasli, Cevahir Cigla, A. Aydin Alatan, Convexity constrained efficient superpixel and supervoxel extraction. “Signal Processing: Image Communication”, 33, p.71-85.
  • 2015, Medeni Soysal, A. Aydin Alatan, Joint utilization of local appearance and geometric invariants for 3D object recognition. “Multimedia Tools and Applications”, 74, p.2611-2637.
  • 2015,Seckin Ozsarac, Gozde Bozdagi Akar, Atmospheric Effects Removal for the Infrared Image Sequences. ” IEEE Trans. Geoscience and Remote Sensing”, 53, p.4899-4909.
  • 2014, Ahmet M. Elbir, T. Engin Tuncer, “Far-Field DOA Estimation and Near-Field Localization For Multipath Signals,” Radio Science, 49, p.765-776, 2014.
  • 2014, Tansu Filik, T. Engin Tuncer, “2-D DOA Estimation in case of Unknown Mutual Coupling for Multipath Signals,” Multidimensional Systems and Signal Processing, p.1-18, 2014.
  • 2014, M. B. Guldogan, D. Lindgren, F. Gustafsson, H. Habberstad, U. Orguner, “Multi-target Tracking with PHD Filter Using Doppler-Only Measurements,” Digital Signal Processing, 27, p.1-11, 2014.
  • 2014, C. Fritsche, U. Orguner, L. Svensson, F. Gustafsson, “The Marginal Enumeration Bayesian Cramer-Rao Bound for Jump Markov Systems,” IEEE Signal Processing Letters, 21, p.464-468, 2014.
  • 2014, K. Granström, C. Lundquist, F. Gustafsson, U. Orguner, “Random Set Methods: Estimation of Multiple Extended Objects,” IEEE Robotics & Automation Magazine, 21, p.73-82, 2014.
  • 2014, K. Granström, U. Orguner, “A New Prediction for Extended Targets with Random Matrices,” IEEE Transactions on Aerospace and Electronic Systems, 50, p.1577-1589, 2014.
  • 2014, Fatih Kamisli, “Recursive Prediction for Joint Spatial and Temporal Prediction in Video Coding,” IEEE Signal Processing Letters, 21, p.732-736, 2014.
  • 2014, Turgay Koc, Tolga Ciloglu, “Automatic Segmentation of High Speed Video Images of Vocal Folds,” Journal of Applied Mathematics, 2014.
  • 2014, C. Candan, H. Inan, “A unified framework for derivation and implementation of SavitzkyGolay filters,” Signal Processing, 104, p.203-211,, 2014.
  • 2014, U. Orguner, C. Candan, “A Fine-Resolution Frequency Estimator Using an Arbitrary Number of DFT Coefficients,” Signal Processing”, 105, p.17-21, 2014.
  • 2014, Y.Kalkan, B.Baykal, “Frequency Based Target Localization Methods for Widely Separated MIMO Radar,” Radio Science, 2014.
  • 2014, Y.Kalkan, B.Baykal, “Multiple target localization & data association for frequency-only widely separated MIMO radar,” Digital Signal Processing, 2014.
  • 2014, Cevahir Çigla, A. Aydin Alatan, “An efficient recursive edge-aware filter,” Signal Processing: Image Communication, 29, p.998-1014, 2014.
  • 2014, Medeni Soysal, Berker Logoglu, Mashar Tekin, Ersin Esen, Ahmet Saracoglu,, “Multimodal concept detection in broadcast media: KavTan,” Multimedia Tools Applications, 72, p.2787-2832, 2014.
  • 2014, Burak Özkalayci, A. Aydin Alatan, “3D Planar Representation of Stereo Depth Images for 3DTV Applications,” IEEE Transactions on Image Processing, 23, p.5222-5232, 2014.
  • 2014, Ozan Sener, Kemal Ugur, A. Aydin Alatan, “Efficient MRF Energy Propagation for Video Segmentation via Bilateral Filters,” IEEE Transactions on Multimedia, 16, p.1292-1302, 2014.
  • 2013, Taylan Aksoy, T. Engin Tuncer, ““Sectorized Approach and Measurement Reduction for Mutual Coupling Calibration of Non-Omnidirectional Antenna Arrays”,” Radio Science, Vol.48, No.2, pp.102-110, 2013.
  • 2013, Ahmet M. Elbir, T. Engin Tuncer, “Calibration of Antenna Arrays For Aeronautical Vehicles on Ground”,” Aerospace Science and Technology, 30, p.18-25, 2013.
  • 2013, C. Lundquist, K. Granström and U. Orguner, “An Extended Target CPHD Filter and a Gamma Gaussian Inverse Wishart Implementation.,” IEEE Journal of Selected Topics in Signal Processing, 7, 2013.
  • 2013, K. Granström and U. Orguner, “On Spawning and Combination of Extended/Group Targets Modeled with Random Matrices,” IEEE Transactions on Signal Processing, 61, 2013.
  • 2013, Fatih Kamisli, “Intra prediction based on markov process modeling of images,” IEEE Transactions on Image Processing, 22, p.3916-3925, 2013.
  • 2013, Oktay Sipahigil, Tolga Çiloğlu, “Comments on “Detection of signals of unknown duration by multiple energy detectors,” Signal Processing, 2013.
  • 2013, C. Candan, “A Low Complexity Two-Stage Target Detection Scheme for Resource Limited Radar Systems,” IEEE Trans. Aerospace and Electronics Systems, 49, p.594-601, 2013.
  • 2013, C. Candan, “Analysis and Further Improvement of Fine Resolution Frequency Estimation Method From Three DFT Samples,” IEEE Signal Processing Letters, 20, (2013), p.913916, 2013.
  • 2013, C. Candan, “Capacity of Zero-Outage Scheme Under Imprecise Channel State Information,” IEEE Communication Letters, 17, p.127-130, 2013.
  • 2013, C. Candan, “An Upper Bound on the Capacity Loss Due to Imprecise Channel State Information for General Memoryless Fading Channels,” IEEE Communications Letters, 17, p.1348-1351, 2013.
  • 2013, C. Candan, U. Orguner, “The moment function for the ratio of correlated generalized gamma variables,” Statistics & Probability Letters, 83, p.2353-2356, 2013.
  • 2013, H. Emrah Tasli, A. Aydin Alatan, “User assisted disparity remapping for stereo images,” Signal Processing: Image Communications, 28, p.1374-1389, 2013.
  • 2013, Cevahir Cigla, A. Aydin Alatan, “Information permeability for stereo matching,” Signal Processing: Image Communications, 28, p.1072-1088, 2013.
  • 2013, O. Serdar Gedik, A. Aydin Alatan, “3-D Rigid Body Tracking Using Vision and Depth Sensors,” IEEE Transactions on Cybernetics, 43, p.1395-1405, 2013.
  • 2012, K. Granström, U. Orguner, “A PHD Filter for Tracking Multiple Extended Targets Using Random Matrices,” IEEE Transactions on Signal Processing, vol. 60, no. 11, pp. 5657-5671, Nov. 2012.
  • 2012, K. Granström, C. Lundquist, and U. Orguner, “Extended Target Tracking Using a Gaussian-Mixture PHD filter,” IEEE Transactions on Aerospace and Electronic Systems, vol. 48, no. 4, pp. 3268-3286, Oct. 2012.
  • 2012, P. Skoglar, U. Orguner, D. Törnqvist, and F. Gustafsson, “Road Target Search and Tracking with Gimballed Vision Sensor on an Unmanned Aerial Vehicle,” Remote Sensing, vol. 4, no. 7, pp. 2076-2111, Jul. 2012.
  • 2012, U. Orguner, “A Variational Measurement Update for Extended Target Tracking with Random Matrices,” IEEE Transactions on Signal Processing, vol. 60, no. 7, pp. 3827-3834, Jul. 2012.
  • 2012, P. Skoglar, U. Orguner, D. Törnqvist, and F. Gustafsson, “Pedestrian Tracking with an Infrared Sensor using Road Network Information,” EURASIP Journal on Advances in Signal Processing, vol. 2012, no. 26, 2012.
  • 2012, Ufuk Sakarya, Ziya Telatar, A. Aydin Alatan Dominant Sets Based Movie Scene Detection. “Signal Processing”, 92, p.107-119, 2012.
  • 2012, Ersin Esen, A. Aydin Alatan, Comparison of Forbidden Zone Data Hiding and Quantization Index Modulation. “Digital Signal Processing”, 22, p.181-189, 2012.
  • 2012, T. Aksoy, T. Engin Tuncer, Measurement Reduction for Mutual Coupling Calibration in DOA Estimation. “Radio Science”, 47, p.1-9, 2012.
  • 2012, B. Gurakan, C. Candan, T. Çiloğlu, “CFAR processing with switching exponential smoothers for nonhomogeneous environments,” Elsevier Digital Signal Processing, 22, p.407-416, 2012.
  • 2012, C. Candan, Y.B. Erol, “Conjugate directions based order recursive implementation of post-Doppler adaptive target detectors,” IET Radar, Sonar & Navigation, 6, p.577-586, 2012.

Posted by dsp metu on 10.01.2017 under Uncategorized