Glossary of Key Terms
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- Truth values: Evaluation of the reliability or likelihood of statements about sensors, data, classification, predictions, and models.
- Sensor: A transducer that transforms energy from one domain to another for data collection.
- Evaluation: Estimating the truth value or likelihood of something.
- Photons: Fundamental particles of light, carrying energy.
- Electrons: Subatomic particles with a negative charge, fundamental to electrical current and sensor interactions.
- Imaging sensors: Sensors based on arrays of cells that convert photons into electronic signals.
- Quantum efficiency: The probability of a photon being converted into a free electron in a sensor cell.
- Energy "Wells" or "buckets": In imaging sensors, regions that accumulate free electrons.
- Thermal infrared sensors: Sensors that detect thermal radiation.
- Bolometers: Cheaper sensors based on the heating effect of radiation.
- Electromagnetic resonator: A system that amplifies electromagnetic signals at a specific frequency.
- Electromagnetic (E.M.) radiation: Energy that travels in waves, consisting of oscillating electric and magnetic fields.
- Static or potential energy: Energy stored by position or state.
- Dynamic or movement energy: Energy of motion (kinetic energy).
- The E.M. swing: An analogy illustrating energy exchange in electrical circuits with capacitance and inductance.
- Resonance: Amplification of a signal at a system's natural frequency.
- Polarization angle: The orientation of the electric field vector of an electromagnetic wave.
- Frequency: The number of wave cycles that pass a point per unit time.
- Time period: The time required for one complete wave cycle.
- Wavelength: The spatial distance over which a wave's pattern repeats.
- Speed of propagation: The speed at which a wave travels through a medium.
- Spectroscopic data: Data that measures radiation intensity at different wavelengths or frequencies.
- Photon stream or photon flux: The number of photons falling on a sensor element per unit time or area.
- Potential energy of electrons (Vc): The voltage across a capacitor formed by accumulated charge from electrons.
- ADC (Analog to Digital Converter): A device that converts analog signals (like voltage) into digital values.
- Numerical output (N_e): The digital value produced by an ADC, representing the accumulated signal.
- Truth interpretation: Establishing a model to relate sensor output to physical quantities.
- Selective resonance absorption filters: Filters that absorb radiation at specific wavelengths or frequencies.
- Interference filters: Filters that use layers to create resonance paths that pass a narrow range of wavelengths.
- Measurement: The interaction between two objects in space-time that produces data about that interaction. In the case of photon sensors, the measuring device is a photon counter, and the measurement unit is the number of photons.
- Image: A visual representation of data captured by a sensor, often composed of multiple bands (e.g., RGB, infrared).
- Information: A relationship between possible questions and answers, based on data and interaction models.
- Statistical relationship: The basis of information, often described by probabilities.
- Truth-of-answer: The probability of a question being true given the data and model.
- Poisson distribution: A probability distribution often used for modelling photon counts with arrival time.
- Knowledge: Based on hypotheses and measured evidence.
- Hypothesis: A proposed explanation or statement to be tested.
- Evidence: Data or observations that support or refute a hypothesis.
- Coincidence statistics: Statistical analysis of the co-occurrence of different events or classifications.
- Radiometric properties: Properties of an object related to its interaction with electromagnetic radiation (e.g., reflectance, emittance).
- Prediction models: Models forecasting future states or properties based on current data.
- Truth value of classification: Evaluation of the accuracy of assigning data to specific categories.
- Discrete class hypotheses: Hypotheses that assign data to distinct, separate categories.
- Frequencies: The number of times something occurs within a sample.
- Prob(E_i | C_j): The probability of observing evidence E_i given class C_j.
- Prob(C_j | E_i): The probability of the class being C_j given the evidence E_i.
- Likelihood vector or array: A representation of the probabilities of different classes given the evidence.
- Maximum likelihood: A method of choosing the class that is most probable given the evidence.
- Binary approximation: Reducing multiple possibilities to two outcomes (e.g., true or false).
- Pseudo truth: A simplified or approximate representation of truth.
- Confusion matrix: A table showing the relationship between predicted and actual classifications.