Image quality evaluation method for compressed satellite remote sensing images with high quantization bits

Zhuo Chen; Chuanjie Zhou; Zhongke Yin

doi:10.1117/12.2587282

12 March 2021 Image quality evaluation method for compressed satellite remote sensing images with high quantization bits

Zhuo Chen, Chuanjie Zhou, Zhongke Yin

Author Affiliations +

Proceedings Volume 11763, Seventh Symposium on Novel Photoelectronic Detection Technology and Applications; 117635V (2021) https://doi.org/10.1117/12.2587282
Event: Seventh Symposium on Novel Photoelectronic Detection Technology and Application 2020, 2020, Kunming, China

Abstract

The quality of remote sensing images is directly influenced by the quantization bits of the CCD camera in the satellite. The images with higher quantization bits can contain more feature details of ground objects, therefore, are considered to be of higher quality. But high quantization bits also mean large amounts of data, and the images acquired by the CCD camera need to be compressed to shorten the satellite-to-ground transmission time. The existed compressed image quality evaluation model can hardly assess the loss degree of images with high quantization bits effectively. This article briefly described the main process of evaluation of compressed remote sensing images. And a new evaluation method with both subjective and objective factors was set up for the compressed images with high quantization bits and tested with actual satellite remote sensing images. The results show that the proposed evaluation method is consistent with the human eye subjective feeling and can provide quantitative reference for the comprehensive evaluation of the remote sensing satellite.

Citation Download Citation

Zhuo Chen, Chuanjie Zhou, and Zhongke Yin "Image quality evaluation method for compressed satellite remote sensing images with high quantization bits", Proc. SPIE 11763, Seventh Symposium on Novel Photoelectronic Detection Technology and Applications, 117635V (12 March 2021); https://doi.org/10.1117/12.2587282

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