Lossy compression techniques provide far
greater compression ratios than lossless and are, therefore, usually preferred in image
processing applications. However, as more and more applications of digital image
processing have to combine image compression and highly automated image analysis, it
becomes of critical importance to study the interrelations existing between image
compression and feature extraction.
In this contribution we present a clear and systematic comparison of contemporary general
purpose lossy image compression techniques with respect to fundamental features, namely
lines and edges detected in images. To this end, a representative set of benchmark edge
detection and line extraction operators is applied to original and compressed images. The
effects are studied in detail, delivering clear guidelines which combination of
compression technique and edge detection algorithm is best used for specific applications.