Evaluation of Lossy Compressed Mosaic for SPOT-6/7 Remote Sensing Data in SPACeMAP

Abstract

SPACeMAP is a remote-sensing data portal system owned by LAPAN used to distribute mosaic data of Medium-Resolution to Very-High-Resolution for Provincial Governments. The frequently arising problem is that mosaic images have very large data size, especially for SPOT-6/7 mosaic images. The increasing number of data and users may affect the data loading process on the portal so that mosaic data compression can be considered. SPACeMAP has the Image Compressor feature using the Tile and Line algorithms with a compression ratio (target rate) recommended for optics (15 to 20). This study aims to determine the best algorithm and target rate to get compressed mosaic SPOT-6/7 imagery. The comparison method was done qualitatively through visual comparison and quantitatively by using Compression Ratio (CR), Bit per Pixel (BPP), and Peak Signal to Noise Ratio (PSNR). Results of the experiment show that, quantitatively, both Tile and Line algorithms give a different performance, depends on the zoom level and land cover characteristics. In terms of the qualitative result, the Tile algorithm gives better overall results compare to the Line algorithm. Quantitatively, both algorithms show good performance in the homogenous area. The target rate difference on the testing range does not affect process duration, nevertheless, the Line algorithm has a long process duration compare to the Tile algorithm. However, compression mosaics with lower or higher resolution remote sensing data may provide different results. Hence, this need be addressed on further studies.