Mr. Ling Ding Profile

Ling Ding

at China Earthquake Administration

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Publications (2)

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Proceedings Article | 18 December 2019 Paper

An urgent parallel processing system for multi-source small-size remote sensing images

Ling Ding, Hongyi Li, Changmiao Hu

Proceedings Volume 11338, 113382S (2019) https://doi.org/10.1117/12.2547785

KEYWORDS: Image processing, Parallel processing, Remote sensing, Computing systems, Unmanned aerial vehicles, Image acquisition

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In order to quickly deal with a large number of multi-source small-size remote sensing images produced by such as unmanned aerial vehicles (UAV) remote sensing, to meet the requirement of high performance parallel processing for earthquake emergency response. Based on analysis of various parallel processing technology of remote sensing images, OpenMP and multithreading technology are comprehensively used to parallelize the image processing algorithms at coarse and fine-grained levels. Combining with the advantages of network multicast technology, the parallel processing system for multi-source small-size remote sensing images is designed and implemented. The system has a strong expansibility in dealing with the types of the images, processing algorithms and the number of processing nodes. After the experiment on a cluster consisting of two computers, it is proved that the system has high CPU utilization and data throughput efficiency, which can provide platform support for earthquake urgent processing.

Proceedings Article | 15 November 2017 Paper

A new improved HSV image fusion method

Ling Ding, Hongyi Li

Proceedings Volume 10605, 106051N (2017) https://doi.org/10.1117/12.2291610

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A new image fusion method based on hue-saturation-value (HSV) color space is proposed, the improved HSV fuses multi-spectral (MS) and panchromatic (PAN) images to improve spatial information and preserve spectral characteristics. The main advantage of the new fusion method is a simple and efficient way which can maximize the extraction of the spatial information and eliminate the disturbance of spectral information in PAN image. the difference of the low components information between PAN and the value component is filtered from the PAN image, and then value component are replaced by the new PAN image, the new HSV color space perform reverse transform to obtain a multispectral image with the high spatial resolution.SPOT-5 and QuickBird MS and PAN images were employed to execute the existing HSV and improved HSV fusion methods. Qualitative and quantitative analyses and classification accuracy assessment were conducted to evaluate the performance of the fusion methods. The results demonstrate that the improved HSV is better than traditional HSV methods. The new fusion method can achieve a wide range of balance between high spatial resolution retention and spectral characteristic preservation.

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