Registration of Translated and Rotated Images Using Finite Fourier Transforms
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Analog Integrated Circuit for Continuous-Time Gain andOffset Calibration of Sensor Arrays
Analog Integrated Circuits and Signal Processing
An FFT-based technique for translation, rotation, and scale-invariant image registration
IEEE Transactions on Image Processing
Fast gradient methods based on global motion estimation for video compression
IEEE Transactions on Circuits and Systems for Video Technology
Extended Recursive Filtering Estimation of Detector Offset Nonuniformity in Infrared Imaging Systems
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Improved Infrared Face Identification Performance Using Nonuniformity Correction Techniques
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Face Recognition with LWIR Imagery Using Local Binary Patterns
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Minimum Variance Gain Nonuniformity Estimation in Infrared Focal Plane Array Sensors
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Joint bias and gain nonuniformity correction of infrared videos using tensorial-RLS technique
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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Thermal array detectors, also known as focal-plane arrays (FPA), are a rapidly developing technology and are used in a variety of civil, medical and military applications. The detectors, which are sensitive to radiation in the infrared band, output a high resolution low noise thermal picture. The existence of non-uniformities in the responsitivity of the element array is a severe problem typical to FPA. These non-uniformities result in a fixed pattern ''curtain''-like feature that appear in the image. One of the most common methods to correct non-uniformity is the use of a uniform reference target. This type of non-uniformity correction has a number of disadvantages. The work presented in this paper proposes a new method to calibrate a thermal detector. The proposed correction method is scene based, relying only on the camera's captured video sequence. The algorithm utilizes redundant information achieved from the thermal camera's high sample rate, combined with the camera's motion. The proposed correction algorithm contains two steps: (1) Application of frame registration that compensates for the camera motion. The registration process matches two consecutive frames and produces a residual (difference) frame. Here, we use well-known techniques. (2) Definition of the calibration parameters as a system of linear equations that is solved with the use of a Kalman filter. The Kalman filter tracks the value of each element specific responsitivity value (unknown) through time. Extensive experimental results demonstrate the success of the proposed scheme. The proposed algorithm necessitates modest computational power (ran on a PC with a Pentium III 550MHz processor) due to the sparsity of the involved matrices.