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This paper aims to study the removal of wide-stripe noise in hyperspectral remote sensing images. There is a great deal of stripe noises in short-wave infrared hyperspectral remote sensing image, especially wide-stripe noise, which brings great challenge to the interpretation and application of hyperspectral images.

To remove the noise and to reduce the impact based on in-depth study of the mechanism of the stripe noise generation and its distribution characteristics, this paper proposed two statistical local processing and moment matching algorithms for the elimination of wide-stripe noise, namely, the gradient mean moment matching (GMMM) algorithm and the gradient interpolation moment matching (GIMM) algorithm.

The experiments were carried out with the practical short-wave infrared hyperspectral image data and good experiment results were obtained. Experiments show that both can reduce the impact of wide-stripe noise, and the filtering effect and the application range of the GIMM algorithm is better than that of the GMMM algorithm.

Using new methods to deal with the hyperspectral remote sensing images, it can effectively improve the quality of hyperspectral images and improve their utilization efficiency and value.

The Giant MagnetoResistance (GMR) effect, discovered in France in 1988, has already been applied in magnetic sensors and has promise in other applications. The rapid acceptance of this technology is due to GMR’s unique characteristics such as high sensitivity, good temperature stability, and excellent linearity over a wide sensing range. In this article GMR materials are described as are their application in magnetic field sensors. New GMR structures utilizing spin valves and spin dependent tunneling (SDT) will offer even more potential for expanding the horizon of solid state magnetic sensing. Comparisons are made to sensors using conventional technology. Integrated GMR sensors that have signal conditioning and output electronics monolithically integrated with the sensor offer further uses of this new technology. Beyond the sensor itself, other control system functions have the potential for using the same GMR materials to make magnetic isolators and nonvolatile memories.

This study aims to examine the observer’s role in “infant psychophysics”. Infant psychophysics was developed because the diagnosis of perceptual deficits should be done as early in a patient’s life as possible, to provide efficacious treatment and thereby reduce potential long-term costs. Infants, however, cannot report their perceptions. Hence, the intensity of a stimulus at which the infant can detect it, the “threshold”, must be inferred from the infant’s behavior, as judged by observers (watchers). But whose abilities are actually being inferred? The answer affects all behavior-based conclusions about infants’ perceptions, including the well-proselytized notion that auditory stimulus-detection thresholds improve rapidly during infancy.

In total, 55 years of infant psychophysics is scrutinized, starting with seminal studies in infant vision, followed by the studies that they inspired in infant hearing.

The inferred stimulus-detection thresholds are those of the infant-plus-watcher and, more broadly, the entire laboratory. The thresholds are therefore tenuous, because infants’ actions may differ with stimulus intensity; expressiveness may differ between infants; different watchers may judge infants differently; etc. Particularly, the watcher’s ability to “read” the infant may improve with the infant’s age, confounding any interpretation of perceptual maturation. Further, the infant’s gaze duration, an assumed cue to stimulus detection, may lengthen or shorten nonlinearly with infant age.

Infant psychophysics investigators have neglected the role of the observer, resulting in an accumulation of data that requires substantial re-interpretation. Altogether, infant psychophysics has proven far too resilient for its own good.

Infant psychophysics is examined for the first time through second-order cybernetics. The approach reveals serious unresolved issues.