Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
The JPEG still picture compression standard
Communications of the ACM - Special issue on digital multimedia systems
Vector quantization and signal compression
Vector quantization and signal compression
Self-Organizing Feature Maps and Their Application to Digital Coding of Information
IWANN '91 Proceedings of the International Workshop on Artificial Neural Networks
Image compression by self-organized Kohonen map
IEEE Transactions on Neural Networks
A Fast Search Algorithm for Vector Quantization Based on Associative Memories
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Probabilistic PCA self-organizing maps
IEEE Transactions on Neural Networks
Vector Quantization Algorithm Based on Associative Memories
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
Design of an evolutionary codebook based on morphological associative memories
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
A multiple vector quantization approach to image compression
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
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The self-organizing Kohonen map is a reliable and efficient way to achieve vector quantization. Typical application of such algorithm is image compression. Moreover, Kohonen networks realize a mapping between an input and an output space that preserves topology. This feature can be used to build new compression schemes which allow to obtain better compression rate than with classical method as JPEG without reducing the image quality. Compared to JPEG, our lossy compression scheme shows better performances (in terms of PSNR) for compression rates higher than 30 [C. Amerijckx, M. Verleysen, P. Thissen and J.-D. Legat (1998). Image compression by self-organized Kohonen map. IEEE Transactions on Neural Networks, 9(3), 503-507.]. For lossless compression, this rate is about 2.7 for standard images.