CS4302 Signal Processing: Sound, Image, Video

2023 to 2024 Semester 1

Curricular information may be subject to change

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

The Scottish Credit Accumulation and Transfer (SCOTCAT) system allows credits gained in Scotland to be transferred between institutions. The number of credits associated with a module gives an indication of the amount of learning effort required by the learner. European Credit Transfer System (ECTS) credits are half the value of SCOTCAT credits.

SCQF level

SCQF level 10

The Scottish Credit and Qualifications Framework (SCQF) provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.

Availability restrictions

Not automatically available to General Degree students

Planned timetable

To be arranged.

This information is given as indicative. Timetable may change at short notice depending on room availability.

Module Staff

TBC Module coordinator(s): Honours Coordinator - Computer Science (hons-coord-cs@st-andrews.ac.uk)

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module description

This module covers the fundamentals of signal processing and perception: investigating how sounds, images and videos can be processed and analysed alongside the fundamentals of how the human auditory and visual perception system functions (e.g., how your eyes and ears work with your brain). Concepts such as data encoding and compression are provided with practical application of understanding signals in terms of their frequency components, relating to their time and spatial components (e.g., audio frequency components or the spatial frequency of an image). Using a programming language regularly used in image and signal processing, students will gain practical skills in applying concepts to real-world problems, including using Fourier transforms, to calculate the frequency distribution in audio files, and undertake tasks such as reducing noise from signals. This module is useful for those wanting to move into the fields of computer vision or data analysis.

Assessment pattern

3-hour Examination = 40%, Coursework = 60%

Re-assessment

3-hour Examination = 40%, Coursework = 60%

Learning and teaching methods and delivery

Weekly contact

2 hr x 10 weeks lectures, 1 hr x 5 weeks exercise/discussion.

Scheduled learning hours

The number of compulsory student:staff contact hours over the period of the module.

Guided independent study hours

125

The number of hours that students are expected to invest in independent study over the period of the module.