Digital Imaging, Speech and Signal Processing

04  Hands-on Characterization of Solid-State Image Sensors
CMOS image sensors are becoming more and more complicated. In the mid nineties the devices were simple image sensors, but over the recent years they have become complete camera systems. Characterization and evaluation of these highly sophisticated SoC's (system-on-chip) is no longer straightforward. Furthermore the pixels of the sensors are becoming extremely small and their limited size can have negative effects on dynamic range, light sensitivity, noise and speed. In the context of further optimization of the imaging functionality, it is of great importance to have a good understanding of performance-limiting parameters of the system. These can only be revealed by performing dedicated measurements on the image sensors and/or on the complete camera systems. That is what this course is all about: learning to characterize an imaging system by means of hands-on experience. 
11  Digital Signal Analysis Techniques: Time, Frequency, and Spatial Algorithms
Conventional tools for analyzing and extracting the feature content of signals are filters (time content), Fourier transforms (frequency content) and beamforming (spatial content). Alternative tools to these conventional techniques are able to produce signal analysis results with finer temporal detail and higher spectral and spatial resolution. This course goes beyond available textbooks and extends these signal analysis tools to higher dimensions and multiple sensor channels. 
13  Digital Imaging: Image Capturing, Image Sensors - Technologies and Applications
If “A picture tells more than a thousand words”, then imaging will be the language of the future. In today’s emerging markets of electronic equipment, imaging plays a very important role. The digital photography market has completely replaced the classical silver-halide film. Video-conferencing, desktop video cameras and still-picture capturing means are standard products as computer add-ons. Imaging is added to cars, mobile phones, and other devices. Very soon we will see the first cameras popping up in watches.
Solid-state image sensors replaced the classical tubes in the broadcast world and are doing the same in other professional application areas. Also in the medical world, new surgery techniques become possible thanks to the powerful characteristics of the image sensors. New developments in CMOS semiconductor technology, next to the outstanding imaging performance of CCDs, open up new applications in the imaging arena. It is just a matter of time and then we will be able to detect single photons with solid-state image sensors.
14  Digital Camera Systems
Digital cameras are an essential part of our daily life, e.g. in mobile phones, camcorders, digital photography, cars, and in imaging applications for medical, industrial and broadcasting industries. All these camera applications rely on the solid-state image sensors. 
However, if consumers were forced to choose a digital camera on the basis of the raw data produced by the imager, it would be very doubtful that anyone of us would buy a digital camera. The data produced by a solid-state image sensor is contaminated by various noise sources, by defects, by inconsistencies, and many other error sources. To make matters worse, the solid-state image sensors do not themselves produce a coloured image. It is the data processing that must correct all these potential errors and even regenerate the colour information in the post-processing stage. So, what a person actually sees on a display or hard copy is absolutely not the same as what the imager has captured. Luckily - "What you see is not what you got!” 

As we can foresee that our homes, offices and cars soon will be fully equipped with cameras to make life safer and more enjoyable and to reduce our workload, we can recognize the digital camera technique as a forefront technology. Even today, for many applications imaging is in the embryo stage of its development. 

 
20  Advanced Course on Image Sensor Technology
Highly sophisticated CMOS image sensors are key components of modern cameras. Technology as well as device architectures are optimized to obtain peak performance of the image sensor and the camera system. The most advanced CMOS image sensors show pixel sizes close to 1 µm. The imagers demonstrate a light sensitivity comparable to that of the human eye. 
Another feature, the back-side illumination, is no longer limited to high-end professional applications. In addition, the modern camera systems can present a dynamic range of 100 dB or more. The equivalent noise level is in the range of sub-electron noise. Even if all these incredible features cannot be combined in one single CMOS image sensor simultaneously, they will allow for new technology breakthroughs and new imaging applications. 

Furthermore, the image sensor fabrication technology is not yet pushed to its ultimate limits. Image sensors make use of CMOS technologies that are lagging 2 or 3 generations behind those of digital integrated circuits or solid-state memories. Even more interesting developments can thus be expected in the near future. Will imagers ever outperform the human eye as far as light sensitivity is concerned? 
50  HD Voice Communication - Coding and Enhancement
The focus of this course is on speech-audio coding and advanced signal processing algorithms for GSM, UMTS or LTE mobile phones, digital hearing aids, and human-machine interfaces. Within the evolution of these systems, the improvement of the speech-audio quality will remain one of the most important objectives to mitigate physical constraints and technological limitations. A comprehensive understanding of fundamental algorithms, standards, applications, and trends is provided. Conditions and solutions are presented with regards to audio-bandwidth limitation, bit-rate restrictions, interference by acoustic background noise, reverberation, acoustic echo signals, and residual transmission errors. 
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