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Curricular information is subject to change
1. Understand basic principles of light-matter interaction at different wavelength ranges and spatial scales.
2. Understand concept of hyperspectral image acquisition & distinction between different modalities
3. Understand basic chemometric techniques, pretreatments and image analysis required in HSI– why and when to use them
4. Ability to take HSI data from multiple samples, analyse the data to give meaningful results (i.e. quantification, interpretation)
5. Ability to code analysis for dataset of multiple HSI images in MATLAB
|Student Effort Type||Hours|
|Autonomous Student Learning||
Basic knowledge of Matlab or R software.
|Description||Timing||Component Scale||% of Final Grade|
|Assignment: Report based on application of the techniques learned during the course to a set of hyperspectral images||Week 9||n/a||Graded||No||
|Continuous Assessment: Tasks requiring student to apply data analysis methods to hyperspectral images.||Varies over the Trimester||n/a||Graded||No||
|Remediation Type||Remediation Timing|
|In-Module Resit||Prior to relevant Programme Exam Board|
• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
Pre- and post feedback on assignments will be provided throughout the semester for group and individual assessments.
|Lecture||Offering 1||Week(s) - 2||Wed 13:00 - 14:50|
|Lecture||Offering 1||Week(s) - 4, 6, 8, 10, 12||Wed 13:00 - 14:50|
|Laboratory||Offering 1||Week(s) - Autumn: Even Weeks||Wed 15:00 - 16:50|