Effects of lossy compression on remote sensing image classification of forest areas

Lossy compression is being increasingly used in remote sensing; however, its effects on classification have scarcely been studied. This paper studies the implications of JPEG (JPG) and JPEG 2000 (J2K) lossy compression for image classification of forests in Mediterranean areas. Results explore the impact of the compression on the images themselves as well as on the obtained classification. The results indicate that classifications made with previously compressed radiometrically corrected images and topoclimatic variables are not negatively affected by compression, even at quite high compression ratios. Indeed, JPG compression can be applied to images at a compression ratio (CR, ratio between the size of the original file and the size of the compressed file) of 10:1 or even 20:1 (for both JPG and J2K). Nevertheless, the fragmentation of the study area must be taken into account: in less fragmented zones, high CR are possible for both JPG and J2K, but in fragmented zones, JPG is not advisable, and when J2K is used, only a medium CR is recommended (3.33:1 to 5:1). Taking into account that J2K produces fewer artefacts at higher CR, the study not only contributes with optimum CR recommendations, but also found that the J2K compression standard (ISO 15444-1) is better than the JPG (ISO 10918-1) when applied to image classification. Although J2K is computationally more expensive, this is no longer a critical issue with current computer technology. © 2010 Elsevier B.V.