Comparison of lossy image compression techniques with respect to their impact on edge detection

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.