Dr. Xifang Zhu Profile

Dr. Xifang Zhu

at Changzhou Institute of Technology

SPIE Involvement:

Author

Publications (9)

Proceedings Article | 10 October 2020 Presentation + Paper

Human-computer interactive system development for cloud removal from single images

Feng Wu, Xifang Zhu, Ruxi Xiang, Qingquan Xu, Yang Xu, Qingcheng Sun

Proceedings Volume 11552, 115520U (2020) https://doi.org/10.1117/12.2573654

KEYWORDS: Clouds, Remote sensing, Human-computer interaction, Algorithm development, Human-machine interfaces, Image resolution, Wavelet transforms, Cameras, Video, Image acquisition

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Remote sensing imaging is disturbed by clouds frequently and produces images with low contrast and poor resolution. Algorithms removing clouds from single remote sensing images are expected to improve their qualities and aroused worldwide interests. Compared with multi-image methods, cloud removal algorithms from single images reduce the demands for weather and improve the image collecting flexibility. In this paper, a human-computer interactive system for cloud removal from single images was developed according to the proposed cloud removal algorithm. Firstly, the distributions of clouds and sceneries in the contaminated remote sensing images were discussed. Features of the dual tree complex wavelet transform (DTCWT) to split image frequencies were investigated after the principle of DTCWT was analyzed. By combining the frequency features of DTCWT sub-bands and the frequency distributions of the remote sensing images, the cloud removal algorithm based on DTCWT was proposed, and its procedures were described completed. Then, a human-computer interactive system for cloud removal was developed in order to improve the cloud removal processing conveniences and achieve the best performance. The development schemes were introduced. The system structures were illustrated. The design methods of the camera driver and video signal output program were described. Communication streams between modules and human-computer interaction interfaces were designed further according to the cloud removal algorithm based on DTCWT. The system has a very good flexibility which permits the input of most parameters from users and is expect to achieve a best performance. Finally, the device of the system was completed and tested. Image acquisition and cloud removal processing experiments were implemented by applying the human-computer interactive system. Cloud removal effects by adjusting parameters through the human-computer interaction interfaces were compared and evaluated. It proved that the designed system has a pleasant human-computer interaction ability and satisfactory cloud removal performance.

Proceedings Article | 12 November 2019 Paper

Image fusion with guided saliency

Ruxi Xiang, Xifang Zhu, Feng Wu, Qingquan Xu

Proceedings Volume 11197, 111970Z (2019) https://doi.org/10.1117/12.2542788

KEYWORDS: Image fusion

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SPIE Journal Paper | 28 June 2017

Guided filter based on multikernel fusion

Ruxi Xiang, Xifang Zhu, Feng Wu, Xiaoyan Jiang, Qingquan Xu

JEI, Vol. 26, Issue 03, 033027, (June 2017) https://doi.org/10.1117/12.10.1117/1.JEI.26.3.033027

KEYWORDS: Image filtering, Linear filtering, Image fusion, Image quality, Image enhancement, Visualization, Air contamination, Denoising

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Proceedings Article | 31 December 2013 Paper

Study on method of simulating Golay3 MMT by external programming

Xifang Zhu, Feng Wu, Quanying Wu, Lin Qian

Proceedings Volume 9042, 90420X (2013) https://doi.org/10.1117/12.2035372

KEYWORDS: Mirrors, Device simulation, Space telescopes, Modulation transfer functions, Computer programming, Zemax, Spherical lenses, Telescopes, James Webb Space Telescope, Point spread functions

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Proceedings Article | 20 December 2013 Paper

Design and application of star map simulation system for star sensors

Feng Wu, Weimin Shen, Xifang Zhu, Yuheng Chen, Qinquan Xu

Proceedings Volume 9044, 90440R (2013) https://doi.org/10.1117/12.2035465

KEYWORDS: Stars, Star sensors, Zemax, Optical design, Monte Carlo methods, Computer simulations, Algorithm development, Computer programming, Calibration, Ray tracing

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Proceedings Article | 30 November 2012 Paper

A fast star image extraction algorithm for autonomous star sensors

Xifang Zhu, Feng Wu, Qingquan Xu

Proceedings Volume 8558, 855821 (2012) https://doi.org/10.1117/12.999641

KEYWORDS: Stars, Feature extraction, Detection and tracking algorithms, Image sensors, Sensors, Star sensors, Image processing, Cameras, Time metrology, Space operations

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Star sensors have been developed to acquire accurate orientation information in recent decades superior to other attitude measuring instruments. A star camera takes photos of the night sky to obtain star maps. An important step to acquire attitude knowledge is to compare the features of the observed stars in the maps with those of the cataloged stars using star identification algorithms. To calculate centroids of the star images before this step, they are required to be extracted from the star maps in advance. However, some large or ultra large imaging detectors are applied to acquire star maps for star sensors with the development of electronic imaging devices. Therefore, star image extraction occupies more and more portions of the whole attitude measurement period of time. It is required to shorten star image extraction time in order to achieve higher response rate. In this paper, a novel star image extraction algorithm is proposed which fulfill the tasks efficiently. By scanning star map, the pixels brighter than the gray threshold are found and their coordinates and brightness are stored in a cross-linked list. Data of these pixels are linked by pointers, while other pixels are neglected. Therefore, region growing algorithm can be used by choosing the first element in the list as a starting seed. New seeds are founded if the neighboring pixels are brighter than the threshold, and the last seed is deleted from the list. Next search continues until no neighboring pixels are in the list. At that time, one star image is extracted, and its centroid is calculated. Likely, other star images may be extracted, and then the examined seeds are deleted which are never considered again. A new star image search always begins from the first element for avoiding unnecessary scanning. The experiments have proved that for a 1024×1024 star map, the image extraction takes nearly 16 milliseconds. When CMOS APS is utilized to transfer image data, the real-time extraction can be almost achieved.

Proceedings Article | 29 November 2011 Paper

Research on removing cloud from optical images

Xifang Zhu, Feng Wu

Proceedings Volume 8200, 82000R (2011) https://doi.org/10.1117/12.903444

KEYWORDS: Clouds, Wavelets, Image processing, Linear filtering, Remote sensing, Image filtering, Curium, Image enhancement, Reconstruction algorithms, Image resolution

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Proceedings Article | 25 November 2009 Paper

Image restoration for sparse aperture systems based on wavelet-Wiener algorithm

Xifang Zhu, Feng Wu

Proceedings Volume 7513, 75131B (2009) https://doi.org/10.1117/12.837680

KEYWORDS: Image restoration, Electronic filtering, Image filtering, Signal to noise ratio, Image processing, Wavelets, Image quality, Imaging systems, Image enhancement, Optical transfer functions

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Proceedings Article | 28 January 2009 Paper

A new method of remote sensing image recovery based on WWC

Xifang Zhu, Feng Wu, ChunKan Tao

Proceedings Volume 7156, 71561P (2009) https://doi.org/10.1117/12.806585

KEYWORDS: Clouds, Fiber optic gyroscopes, Wavelets, Remote sensing, Image restoration, Linear filtering, Wavelet transforms, Image processing, Digital imaging, Image filtering

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Showing 5 of 9 publications

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