Ms. Chuanjie Zhou Profile

Chuanjie Zhou

at Beijing Institute of Remote Sensing Information

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Proceedings Article | 12 March 2021 Paper

Super-solution technology for low light level imaging in the field of remote sensing

Chao Zhang, Bin Bai, Chuanjie Zhou, Shaoning Wei

Proceedings Volume 11763, 117637T (2021) https://doi.org/10.1117/12.2587484

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We have designed the super-solution technology for low light level imaging in the field of remote sensing. Low light level image super-resolution is realized with a method of super-resolution processing based on worked example learning and the information of high-resolution visible image. Multi-frame image and single-frame image of the super-resolution algorithms are combined to apply in the low light level imaging in the field of remote sensing. With the ground targets as the reference, the results illustrate that the higher resolution images are obtained and a number of image data are satisfactory. This technology has impressive potential for improving the efficiency of low light level remote sensing.

Proceedings Article | 12 March 2021 Paper

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

Zhuo Chen, Chuanjie Zhou, Zhongke Yin

Proceedings Volume 11763, 117635V (2021) https://doi.org/10.1117/12.2587282

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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.

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