Scene-based nonuniformity correction with video sequences and registration.

We describe a new, to our knowledge, scene-based nonuniformity correction algorithm for array detectors. The algorithm relies on the ability to register a sequence of observed frames in the presence of the fixed-pattern noise caused by pixel-to-pixel nonuniformity. In low-to-moderate levels of nonuniformity, sufficiently accurate registration may be possible with standard scene-based registration techniques. If the registration is accurate, and motion exists between the frames, then groups of independent detectors can be identified that observe the same irradiance (or true scene value). These detector outputs are averaged to generate estimates of the true scene values. With these scene estimates, and the corresponding observed values through a given detector, a curve-fitting procedure is used to estimate the individual detector response parameters. These can then be used to correct for detector nonuniformity. The strength of the algorithm lies in its simplicity and low computational complexity. Experimental results, to illustrate the performance of the algorithm, include the use of visible-range imagery with simulated nonuniformity and infrared imagery with real nonuniformity.

Statistical algorithm for nonuniformity correction in focal-plane arrays.

A statistical algorithm has been developed to compensate for the fixed-pattern noise associated with spatial nonuniformity and temporal drift in the response of focal-plane array infrared imaging systems. The algorithm uses initial scene data to generate initial estimates of the gain, the offset, and the variance of the additive electronic noise of each detector element. The algorithm then updates these parameters by use of subsequent frames and uses the updated parameters to restore the true image by use of a least-mean-square error finite-impulse-response filter. The algorithm is applied to infrared data, and the restored images compare favorably with those restored by use of a multiple-point calibration technique.

Fast registration and reconstruction of aliased low-resolution frames by use of a modified maximum-likelihood approach.

During the process of microscanning a controlled vibrating mirror typically is used to produce subpixel shifts in a sequence of forward-looking infrared (FLIR) images. If the FLIR is mounted on a moving platform, such as an aircraft, uncontrolled random vibrations associated with the platform can be used to generate the shifts. Iterative techniques such as the expectation-maximization (EM) approach by means of the maximum-likelihood algorithm can be used to generate high-resolution images from multiple randomly shifted aliased frames. In the maximum-likelihood approach the data are considered to be Poisson random variables and an EM algorithm is developed that iteratively estimates an unaliased image that is compensated for known imager-system blur while it simultaneously estimates the translational shifts. Although this algorithm yields high-resolution images from a sequence of randomly shifted frames, it requires significant computation time and cannot be implemented for real-time applications that use the currently available high-performance processors. The new image shifts are iteratively calculated by evaluation of a cost function that compares the shifted and interlaced data frames with the corresponding values in the algorithm's latest estimate of the high-resolution image. We present a registration algorithm that estimates the shifts in one step. The shift parameters provided by the new algorithm are accurate enough to eliminate the need for iterative recalculation of translational shifts. Using this shift information, we apply a simplified version of the EM algorithm to estimate a high-resolution image from a given sequence of video frames. The proposed modified EM algorithm has been found to reduce significantly the computational burden when compared with the original EM algorithm, thus making it more attractive for practical implementation. Both simulation and experimental results are presented to verify the effectiveness of the proposed technique.

The inhibitory effect of lysozyme on the glomerular basement membrane thickening in spontaneous diabetic mice (NSY mice).

Currently, there is no effective treatment for diabetic microangiopathy. We have been examining, therefore, the effects of lysozyme on the renal conditions of spontaneous diabetic mice (NSY mice). We assessed the changes in glomerulus following the administration of lysozyme, using the thickness of the glomerular capillary basement membrane as an indicator. Littermate, male F19 NSY mice were divided into two groups. One of the groups (Group L) was treated with lysozyme; the other control group (Group C) with physiological saline. Group L received a daily intramuscular injection of lysozyme solution for 4 or 8 weeks. The thickness of the glomerular capillary basement membrane was measured in order to assess the effect of lysozyme administration. In the 4-week series, the thickness was 4783 +/- 1760 A in Group C and 3266 +/- 777 A in Group L, while in the 8-week series it was 6011 +/- 2043 A in Group C and 3540 +/- 431 A in Group L. In both series of Group L, a distinct inhibitory effect on the basement membrane thickening was found. The present findings suggest that lysozyme may be effective in human diabetic nephropathy. However its clinical usefulness must be confirmed in future studies.

New experimental congenital diabetic mice (N.S.Y. mice).

New experimental congenital diabetic mice were obtained in the descendants of streptozotocin-induced diabetic mice. Diabetes was developed by the administration of strepotozotocin in normal adult I.C.R. mice, and then these mice were mated to obtain the F1 mice. The F1 mice with impaired glucose tolerance were mated within the siblings. The same process was repeated over several generations. The diabetic features of the spontaneously diabetic mice thus obtained were as follows: 1) The mice did not show a tendency toward obesity. 2) Glucose tolerance of these mice, especially after the F6 generation, was remarkably impaired. However, the elevation of the fasting blood glucose level was slight throughout the generations. We propose to designate the congenital diabetic mice as the N.S.Y. (Nagoya, Shibata, Yasuda) mice. The N.S.Y. mice are considered to be useful models for human diabetes.