Joint Source Channel Coding for Image Transmission

Contact: Harm Cronie
Room: BC150
Tel: 021 6936793
Email: harm [dot] cronie [at] epfl [dot] ch

In this assignment we consider the efficient transmission of images over a noisy channel. On one hand we would like to represent the image with as less bits as possible. This is done by image compression methods such as jpeg compression. On the other hand we need some redundancy in the form of an error-correcting code to ensure reliable transmission over the channel. Traditionally, these two tasks are solved separately. One of the disadvantages of this approach is that a few residual errors after decoding the error-correcting code usually lead to a very large error in image reconstruction.

Joint source channel coding methods can provide a finer trade-off between the image reconstruction quality and the amount of noise the system can deal with. In this assignment you will implement signal processing algorithms to represent an image efficiently. These methods include image transforms such as the discrete cosine transform and quantization. After this signal processing stage, a Raptor code can be applied to allow for reliable transmission over the channel. The goal is to reconstruct the image at the receiver side with as less distortion as possible given the signal to noise ratio of the channel.