The paper discusses several techniques for performance evaluation of passive digital imaging systems. The principal approach of these techniques is a comparison of the output signals from a real imaging system and from the idealized one. The first technique applies the normalized least-square error called fidelity as an absolute measure of the output signal difference. The second technique uses the correlation coefficient that reflects the difference between linear combinations of the output signals as an estimation of performance. The third technique is based on evaluation of the information rate of the output signals.
Proc. SPIE. 4035, Laser Radar Technology and Applications V
KEYWORDS: Thermography, Digital signal processing, Imaging systems, Spatial frequencies, Signal attenuation, Interference (communication), Temporal resolution, Spatial resolution, Analog electronics, Minimum resolvable temperature difference
There are several techniques for performance evaluation of an imaging system (IS). The first is the classical one: performance is considered as a characteristics called minimum resolvable temperature difference (MRTD). The second one is fidelity which is a parameter based on the least-square error between output signals of the idealized IS and an investigated one. The least-square error takes into account noise and distortions introduced by high spatial frequencies suppression. The third technique is defined via correlation coefficient between output signals of the idealized IS and a definite one. The paper discusses the application of the mentioned approaches for performance evaluation.
The paper represents the approach for residual non- uniformity evaluation after two-points linear non-uniformity correction. The approach takes into consideration parameters of an imaging system, reference source, non-linearity and noise of multi-element photodetector.
The paper presents an approach for performance evaluation and parametric optimization of imaging system design. This approach is based on calculation and minimization of image distortion. It applies the criterion based on minimization of normalized least-square image error. The proposed mathematical apparatus makes possible evaluation of the performance and calculation of optimal parameters that reduces image distortion caused by spatial filtering and noise. The paper illustrates the application of the proposed technique for performance analysis of a scanning system.
Proc. SPIE. 3904, Fourth International Conference on Correlation Optics
KEYWORDS: Signal to noise ratio, Infrared imaging, Imaging systems, Interference (communication), Image quality, Information technology, Modulation transfer functions, Spatial resolution, Minimum resolvable temperature difference, Astatine
The paper describes an approach to optimization of passive infrared imaging systems based on maximization of the correlation between output signals of an idealized imaging system and a real one. This approach guarantees the optimal balance between temperature and spatial resolutions of the imaging system for any given test object. The paper represents a mathematical apparatus that binds a coefficient of correlation between the output signals with parameters of an imaging system such as focal distance, aperture diameter, dimensions of photosensitive element and etc. This apparatus allows to evaluate the performance and to get a merit function for optimization. Results of optimization and problems of identification of the best relationships between spatial temperature and resolutions are discussed.
The paper presents an approach for performance evaluation and parametric optimization for IR imagin system design. This approach is based on calculations and minimization of image distortion. It applies the criterion like minimization of normalized least-square image error. The proposed mathematical apparatus makes possible evaluation of the performance and calculation of optimal parameters that reduces image distortion caused by spatial filtering and noise. The paper illustrates the application of the posed techniques for scanning system performance analysis and design.
The paper describes an approach to parametric optimization of an IR imaging system. This approach is based on minimization of image distortion of a multi-bar test object. The quality of imaging system is defined by a probability of correct pixel classification. This probability characterizes an error of image binarization. The paper represents the mathematical model that binds the probability of correct pixel classification with parameters of an imaging system such as focal length, aperture diameter, dimensions of photosensitive element, integration time and etc. It allows to get the merit function for parametric optimization and to identify the optimal relationship between spatial resolution and temperature resolution.