Compression is useful because it helps reduce the consumption of expensive resources, such as hard disk space or transmission bandwidth. On the downside, compressed data must be decompressed to be used, and this extra processing may be detrimental to some applications. For instance, a compression scheme for video may require expensive hardware for the video to be decompressed fast enough to be viewed as it is being decompressed (the option of decompressing the video in full before watching it may be inconvenient, and requires storage space for the decompressed video). The design of data compression schemes therefore involves trade-offs among various factors, including the degree of compression, the amount of distortion introduced (if using a lossy compression scheme), and the computational resources required to compress and uncompress the data.
Possible topics include, but are not limited to, the following:
- Signal generation and modelling
- Analog signal processing
- Digital signal processing
- Adaptive filtering algorithm
- Image compression applications
- Data compression applications
- Image reconstruction
- Speech and audio compression
- Wavelets applications in image compression
- Image and video coding
- Fractal image compression
- Colour image compression
- Soft computing applications for image compression
- Image clustering, classification and recognition
- Classification tools for image-based diagnosis
Submission deadline: 15 February, 2011
First decision notification: 30 March, 2011
Submission of revised papers: 15 April, 2011
Final decision notification: 30 May, 2011
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