The Johnson-Lindenstrauss Lemma and the sphericity of some graphs
Journal of Combinatorial Theory Series A
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Digital image processing
Approximate nearest neighbors: towards removing the curse of dimensionality
STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
A semidiscrete matrix decomposition for latent semantic indexing information retrieval
ACM Transactions on Information Systems (TOIS)
Database-friendly random projections
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Random projection in dimensionality reduction: applications to image and text data
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Digital Image Compression Techniques
Digital Image Compression Techniques
Introduction to Algorithms
On generalization bounds, projection profile, and margin distribution
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Experiments with Random Projection
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
An Algorithmic Theory of Learning: Robust Concepts and Random Projection
FOCS '99 Proceedings of the 40th Annual Symposium on Foundations of Computer Science
Robust Tracking and Compression for Video Communication
RATFG-RTS '99 Proceedings of the International Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems
Hybrid KLT-SVD image compression
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 4 - Volume 4
Semi-discrete Matrix Transforms (SDD) for Image and Video Compression
DCC '02 Proceedings of the Data Compression Conference
Image Processing, Analysis, and Machine Vision
Image Processing, Analysis, and Machine Vision
Symmetric convolution and the discrete sine and cosine transforms
IEEE Transactions on Signal Processing
Medical image compression by discrete cosine transform spectral similarity strategy
IEEE Transactions on Information Technology in Biomedicine
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There exist many lossy image compression techniques, some of which are based on dimensionality reduction. In this paper, a method for lossy image compression is introduced which utilizes the dimensionality reduction technique known as Random Projection. Random Projection has proven itself as an effective technique for reducing the dimensionality of data, particularly when dimensionality d is moderately high (e.g., d