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Impact of CCSDS‐IDC and JPEG 2000 Compression on Image Quality and Classification

2012; Hindawi Publishing Corporation; Volume: 2012; Issue: 1 Linguagem: Inglês

10.1155/2012/761067

2090-0155

Alaitz Zabala, Raffaele Vitulli, Xavier Pons,

Remote-Sensing Image Classification

This study measures the impact of both on‐board and user‐side lossy image compression (CCSDS‐IDC and JPEG 2000) on image quality and classification. The Sentinel‐2 Image Performance Simulator was modified to include these compression algorithms in order to produce Sentinel‐2 simulated images with on‐board lossy compression. A multitemporal set of Landsat images was used for the user‐side compression scenario in order to study a crop area. The performance of several compressors was evaluated by computing the Signal‐to‐Noise Ratio (SNR) of the compressed images. The overall accuracy of land‐cover classifications of these images was also evaluated. The results show that on‐board CCSDS performs better than JPEG 2000 in terms of compression fidelity, especially at lower compression ratios (from CR 2:1 up to CR 4:1, i.e., 8 to 4 bpppb). The effect of compression on land cover classification follows the same trends, but compression fidelity may not be enough to assess the impact of compression on end‐user applications. If compression is applied by end‐users, the results show that 3D‐JPEG 2000 obtains higher compression fidelity than CCSDS and JPEG 2000 with other parameterizations. This is due to the high dynamic range of the images (representing reflectances * 10000), which JPEG 2000 is able to exploit better.