Multispectral Imagery
Multispectral Imagery - Related Videos
11:46
Decoding Auditory Imagery with Multivoxel Pattern Analysis
0 Views •
2023
Source: Laboratories of Jonas T. Kaplan and Sarah I. Gimbel—University of Southern California Imagine the sound of a bell ringing. What is happening in the brain when we conjure up a sound like this in the "mind's ear?" There is growing evidence that the brain uses the same mechanisms for imagination that it uses for perception.1 For example, when imagining visual images, the visual cortex becomes activated, and when imagining sounds, the auditory cortex is engaged. However, to what extent are...
08:40
Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging
0 Views •
Cited by 17 •
2016
Immunohistochemistry is a powerful lab technique for evaluating protein localization and expression within tissues. Current semi-automated methods for quantitation introduce subjectivity and often create irreproducible results. Herein, we describe methods for multiplexed immunohistochemistry and objective quantitation of protein expression and co-localization using multispectral imaging.
06:37
Multispectral Real-time Fluorescence Imaging for Intraoperative Detection of the Sentinel Lymph Node in Gynecologic Oncology
0 Views •
Cited by 41 •
2010
Fluorescence imaging is a promising innovative modality for image-guided surgery in surgical oncology. In this video we describe the technical procedure for detection of the sentinel lymph node using fluorescence imaging as showcased in gynecologic oncologicy. A multispectral fluorescence camera system, together with the fluorescent agent indocyanine green, is applied.
05:36
STFEEG-Tool: A Spatial-Temporal-Frequency EEG Analysis Tool for Motor Imagery Brain-Computer Interfaces
0 Views •
2026
This study presents a standardized and reproducible protocol for implementing the Spatial-Temporal-Frequency EEG analysis tool (STFEEG) for motor imagery EEG decoding, incorporating configurable spatial-temporal-frequency segmentation, Common Spatial Patterns (CSP)-based feature extraction, multiple classification algorithms, and visualization capabilities.
09:55
Use of a Psychophysiological Script-driven Imagery Experiment to Study Trauma-related Dissociation in Borderline Personality Disorder
0 Views •
Cited by 6 •
2018
We present a protocol of personalized script-driven trauma-related imagery and clinical assessments within a comparison design for investigating peritraumatic dissociation (PD), psychophysiological reactions, i.e. heart rate (HR) and skin conductance (SC), and psychological features of often severely traumatized individuals with borderline personality disorder (BPD).
FAQs
The key signal is the pattern of energy measured across bands, not simply the appearance of a surface in one image. Materials and surface conditions produce different spectral responses, so comparing those responses helps separate land-cover types and characterize environmental conditions. This makes band information useful for classification and mapping.
Near-infrared bands extend observation beyond visible wavelengths and add another way to compare surfaces. In environmental work, that extra spectral response supports vegetation mapping and helps characterize conditions that may not be distinguished as clearly using visible information alone. The value comes from combining band responses rather than treating each wavelength as an isolated picture.
Multispectral imagery can use either reflected or emitted energy, and these represent different kinds of surface signals. Treating them as interchangeable could obscure what a measurement indicates. Keeping the signal type in view helps researchers interpret spectral responses appropriately when characterizing vegetation, soil, water, or land cover and when comparing observations from different sensing situations.
A practical workflow begins by selecting a sensor platform suited to the study area, such as a satellite, aircraft, or drone. The collected bands are then compared to identify spectral differences, classify land cover, or characterize surface conditions. For environmental monitoring, repeating this workflow creates observations that can be compared over time to detect change.
Researchers can apply the imagery at several environmental scales. Vegetation mapping, crop and forest monitoring, water-quality assessment, soil analysis, and land-cover classification address different management questions while using the same multispectral information. The appropriate application depends on whether the goal is to describe ecosystems, evaluate a resource, or distinguish surface categories across an area.
Repeated observations are especially valuable when the objective is environmental change detection rather than a one-time inventory. Comparing imagery across dates can reveal patterns associated with drought, wildfire, pollution, erosion, or urban expansion. Those results give researchers and resource managers evidence for assessing ecosystem change and informing conservation decisions.