Image and signal processing affect our daily lives in an ever-increasing way. Participate in designing this fascinating technology and shape IT‘s future function in business and society. Today‘s networked devices for image and signal generation provide a historically unmatched volume of raw data for automated decision making and control systems. The demands are high: How can we design new tools and software in order to best distil useful information? A lot of interesting research and development projects in the private and the public sectors are calling for your expertise. Alternatively, this degree will open career tracks in universities and research labs.
The international Joint Degree Master Programme„Applied Image and Signal Processing“ is conducted in English. The standard period of study is four semesters. The full program is worth a total of 120 points according to the ECTS (European Credit Transfer and Accumulation System). The academic degree of „Master of Science in Engineering“ (MSc) will be awarded upon successful completion of the programme.
From Theory to Practice (Curriculum)
The first semester is devoted to a concise study of the theoretical basis, the mathematical models and the algorithms used in image and signal processing. The second semester additionally focuses on geometric modelling, audio processing and digital media formats. Starting with the third semester, specific application scenarios are discussed and corresponding technologies are investigated in a number of elective courses.
Choose your Elective Courses
The elective courses comprise medical imaging, platform specific signal processing, data science, biometric systems, media security, computational geometry and machine learning.
Apply your Scientific Knowledge
In the third semester, students also start research on their master thesis and acquire profound IT-project management skills. The fourth semester is dedicated to the completion of the master thesis. An accompanying master seminar provides a forum for presenting and defending one‘s approach to a solution and the results obtained, i.e., for scientific discourse with faculty and peers.
Modules & Competences
This Joint Degree Master Programme is designed to provide students with an in-depth professional and scientific training. Based on appropriate prior bachelor studies, this programme offers a thorough technical training in conjunction with research-driven teaching. It will make the participants familiar with introductory and advanced-level topics in the fields of image and signal processing, their formal and methodical basics, and with diverse fields of application. The sound knowledge and skills acquired in this programme qualify the alumni for diverse practical challenges in their professional work and empower them to contribute to future innovations in image and signal processing. A master thesis serves as a documentary proof of the student‘s ability to tackle scientific problems successfully on his or her own and to come up with a result that is correct with regards to contents and methodology. Furthermore the publication of Master Thesis is intended. Thus, this programme also paves the road to subsequent work in science and technology.
This programme provides graduates and working professionals with a broad training in signal processing and communications. It is suitable for recent graduates who wish to develop the specialist knowledge and skills relevant to this industry and is also suitable as advanced study in preparation for research work in an academic or industrial environment or in a specialist consultancy organisation.
Engineers or other professionals wishing to participate in the MSc programme may do so on a part-time basis.
Our students gain a thorough understanding of theoretical foundations as well as advanced topics at the cutting edge of research in signal processing and communications, including compressive sensing, deep neural networks, wireless communication theory, and numerical Bayesian methods.
The MSc project provides a good opportunity for students to work on state-of-the-art research problems in signal processing and communications.
This programme is run over 12 months, with two semesters of taught courses followed by a research project leading to a masters thesis.
Semester 1 courses
Semester 2 courses
With our excellent employability record and internationally respected reputation, the University of Edinburgh is a reliable choice for developing your engineering career.
This programme will appeal to graduates who wish to pursue a career in an industry such as communications, radar, medical imaging or anywhere else signal processing is applied.
This degree provides in-depth training for students interested in a career in industry or in research-oriented institutions focused on image and video analysis, and deep learning.
State-of-the-art computer-vision and machine-learning approaches for image and video analysis are covered in the course, as well as low-level image processing methods.
Students also have the chance to substantially expand their programming skills through projects they undertake.
Read about the experience of a previous student on this course, Gianmarco Addari.
This programme is studied full-time over 12 months and part-time from 24 to 60 months. It consists of eight taught modules and a standard project.
Example module listing
The following modules are indicative, reflecting the information available at the time of publication. Please note that not all modules described are compulsory and may be subject to teaching availability and/or student demand.
This programme in Computer Vision, Robotics and Machine Learning aims to provide a high-quality advanced training in aspects of computer vision for extracting information from image and video content or enhancing its visual quality using machine learning codes.
Computer vision technology uses sophisticated signal processing and data analysis methods to support access to visual information, whether it is for business, security, personal use or entertainment.
The core modules cover the fundamentals of how to represent image and video information digitally, including processing, filtering and feature extraction techniques.
An important aspect of the programme is the software implementation of such processes. Students will be able to tailor their learning experience through selection of elective modules to suit their career aspirations.
Key to the programme is cross-linking between core methods and systems for image and video analysis applications. The programme has strong links to current research in the Department of Electronic Engineering’s Centre for Vision, Speech and Signal Processing.
To support your learning, we hold regular MSc group meetings where any aspect of the programme, technical or non-technical, can be discussed in an informal atmosphere. This allows you to raise any problems that you would like to have addressed and encourages peer-based learning and general group discussion.
We provide computing support with any specialised software required during the programme, for example, Matlab. The Faculty’s student common room is also covered by the University’s open-access wireless network, which makes it a very popular location for individual and group work using laptops and mobile devices.
Specialist experimental and research facilities, for computationally demanding projects or those requiring specialist equipment, are provided by the Centre for Vision, Speech and Signal Processing (CVSSP).
Computer vision specialists are be valuable in all industries that require intelligent processing and interpretation of image and video. This includes industries in directly related fields such as:
Studying for Msc degree in Computer Vision offers variety, challenge and stimulation. It is not just the introduction to a rewarding career, but also offers an intellectually demanding and exciting opportunity to break through boundaries in research.
Many of the most remarkable advancements in the past 60 years have only been possible through the curiosity and ingenuity of engineers. Our graduates have a consistently strong record of gaining employment with leading companies.
Employers value the skills and experience that enable our graduates to make a positive contribution in their jobs from day one.
We draw on our industry experience to inform and enrich our teaching, bringing theoretical subjects to life. Our industrial collaborations include:
This course gives an excellent preparation for continuing onto PhD studies in computer vision related domains.
We often give our students the opportunity to acquire international experience during their degrees by taking advantage of our exchange agreements with overseas universities.
In addition to the hugely enjoyable and satisfying experience, time spent abroad adds a distinctive element to your CV.
The Institute for Digital Communications (IDCOM) is the UK's leading research institute in signal processing and communications and is home to the Li-Fi research and development centre. We have three major centres of activity; signal processing, communications systems and tomographic imaging. Our programme of research delivers world leading research in signal and image processing and communications from fundamental theoretical and algorithmic work through to its translation to specific audio, imaging, radar/sonar, and communications applications.
The Institute has excellent research facilities, including state-of-the-art computing systems and laboratories for agile tomography, and audio signal processing, as well as the Li-Fi research and development centre for visible light communications. Internationally recognised for our research on communications systems and signal processing, we offer research topics including: green radio; visible light communications; cognitive radio; compressive sensing; distributed sensor signal processing; and agile tomography.
IDCOM holds the only UK Research Council platform award in sensor signal processing, in collaboration with the joint research institute in signal and image processing and Heriot-Watt University, recognising our world leading research status.
The development of transferable skills is a vital part of postgraduate training and a vibrant, interdisciplinary training programme is offered to all research students by the University’s Institute for Academic Development (IAD). The programme concentrates on the professional development of postgraduates, providing courses directly linked to postgraduate study.
Courses run by the IAD are free and have been designed to be as flexible as possible so that you can tailor the content and timing to your own requirements.
Our researchers are strongly encouraged to present their research at conferences and in journal during the course of their PhD.
Every year, the Graduate School organises a Postgraduate Research Conference to showcase the research carried out by students across the Research Institutes
Our researchers are also encouraged and supported to attend transferable skills courses provided by organisations such as the Engineering and Physical Sciences Research Council (EPSRC).
The Institute has excellent research facilities, including state-of-the-art computing systems and laboratories for usability engineering, audio signal processing and visible light communications.
This programme is structured around topics in systems and signal processing, with specialisms in control and systems theory, image processing and machine learning. Skills developed are sought after by industry (biotech, financial services, systems engineering, medical imaging, etc) and the academic research community. The modules have a high mathematical content and much of the material is computationally based, developing strong transferable skills in algorithmic development and programming.
Semester one: Signal Processing; Control System Design; Machine Learning; Computer Vision.
Semester two: Advanced Systems and Signal Processing; Digital Control System Design; Applied Control Systems; Biological Inspired Robotics; Advanced Computer Vision; Image Processing; Advanced Machine Learning; Computational Finance; Computational Biology; Biometrics.
Plus three-month independent research project culminating in a dissertation.