TY - JOUR
T1 - Impact of lossy compression on mapping crop areas from remote sensing
AU - Zabala, Alaitz
AU - Pons, Xavier
PY - 2013/1/1
Y1 - 2013/1/1
N2 - This study measures the effect of lossy image compression (JPEG 2000 and JPG) on the digital classification of crop areas. The results provide new insights into the influence of compression on the quality of the cartography produced. Both a multitemporal and a single-date classification approach were analysed. With the multitemporal approach, it is possible to use high compression ratios (CRs), up to 20:1 or even 100:1, and the overall accuracy of the classification is similar to that obtained with the original images. Moreover, the classified area is similar or even greater (fewer pixels are uncertain). For a single-date approach, it is only advisable to use 3D-JPEG 2000 at CRs up to 20:1. The optimum CR is also affected by landscape fragmentation (fragmented images tolerate less compression) and the classification method (hybrid classifiers are affected less than the maximum likelihood and minimum distance classifiers). Finally, classifications from compressed images have less 'salt and pepper' effect than those obtained from the originals, especially when JPEG 2000 (3D or not) is used. © 2013 Copyright Taylor and Francis Group, LLC.
AB - This study measures the effect of lossy image compression (JPEG 2000 and JPG) on the digital classification of crop areas. The results provide new insights into the influence of compression on the quality of the cartography produced. Both a multitemporal and a single-date classification approach were analysed. With the multitemporal approach, it is possible to use high compression ratios (CRs), up to 20:1 or even 100:1, and the overall accuracy of the classification is similar to that obtained with the original images. Moreover, the classified area is similar or even greater (fewer pixels are uncertain). For a single-date approach, it is only advisable to use 3D-JPEG 2000 at CRs up to 20:1. The optimum CR is also affected by landscape fragmentation (fragmented images tolerate less compression) and the classification method (hybrid classifiers are affected less than the maximum likelihood and minimum distance classifiers). Finally, classifications from compressed images have less 'salt and pepper' effect than those obtained from the originals, especially when JPEG 2000 (3D or not) is used. © 2013 Copyright Taylor and Francis Group, LLC.
U2 - 10.1080/01431161.2012.750772
DO - 10.1080/01431161.2012.750772
M3 - Article
SN - 0143-1161
VL - 34
SP - 2796
EP - 2813
JO - International Journal of Remote Sensing
JF - International Journal of Remote Sensing
ER -