The document discusses lossy compression techniques such as quantization and transform coding. It explains that lossy compression achieves higher compression rates by introducing some loss or distortion to the reconstructed data compared to the original. It describes various distortion measures used to evaluate the quality of lossy compression, including mean squared error and peak signal-to-noise ratio. It also discusses the discrete cosine transform, a widely used transform coding technique that decomposes images or signals into different frequency components for more efficient compression.

1. Lossy Compression CIS 658 Fall 2005

10. Uniform Scalar Quantization

15. Quantization Error

31. Basis Functions

32. DCT Examples

38. DCT Examples

43. Graphical Illustration of 2D DCT Basis Functions