Artifacts Measurement For Compressed Remote Sensing Images And Its Application

With the increasingly large amount of satellite remote sensing data, great difficulties have been brought by the contradiction between the limited channel capacity and transmission needs. In order to efficiently transfer remote sensing data, the original remote sensing image data must be compressed with lossy mode. Lossy compression of image data will cause far-reaching impact on the application of aerospace remote sensing, because lossy compression will create image distortion inevitably. Hight compression ratio will cause great distortion which will reduce sensor imaging capability, so the sensor design, the satellite orbit design, spectral bands and spatial resolution of the design and sensor calibration processes are also affected. That is to say, lossy image compression will have a direct impact on the application of remote sensing data.The paper centered on the methods, techniques and applications of image quality evaluation of lossy compression, including the classification of image compression and image compression in the aerospace remote sensing, JPEG2000, SPIHT, JPEG-LS and other algorithms, and the sources of image distortion analysis, the interpretation evaluation of remote sensing image compression quality, geometric quality evaluation of the image compression, application analysis in surveying and mapping, etc.Based on the above research, we have proposed a compression ratio-less than 4:1 for resources satellite 3, 1m/4m high-resolution satellites, if adopted JPEG2000, SPIHT or JPEG-LS compression algorithm. From practical application of satellite remote sensing, the paper establish a system for image compression quality analysis and evaluation. This system has greatly expanded the content of the application evaluation, broken through the key technologies of image quality evaluation and realized an integration of subjective, objective and applicative assessment.