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Sensors 2017, 17(4), 935; doi:10.3390/s17040935

Improved Line Tracing Methods for Removal of Bad Streaks Noise in CCD Line Array Image—A Case Study with GF-1 Images

1
College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
2
Tianjin Key Laboratory of Intelligent Information Processing in Remote Sensing, Tianjin 300301, China
3
National Ocean Technology Center, Tianjin 300112, China
*
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M. N. Passaro
Received: 24 February 2017 / Revised: 21 April 2017 / Accepted: 21 April 2017 / Published: 24 April 2017
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [2701 KB, uploaded 24 April 2017]   |  

Abstract

Remote sensing images could provide us with tremendous quantities of large-scale information. Noise artifacts (stripes), however, made the images inappropriate for vitalization and batch process. An effective restoration method would make images ready for further analysis. In this paper, a new method is proposed to correct the stripes and bad abnormal pixels in charge-coupled device (CCD) linear array images. The method involved a line tracing method, limiting the location of noise to a rectangular region, and corrected abnormal pixels with the Lagrange polynomial algorithm. The proposed detection and restoration method were applied to Gaofen-1 satellite (GF-1) images, and the performance of this method was evaluated by omission ratio and false detection ratio, which reached 0.6% and 0%, respectively. This method saved 55.9% of the time, compared with traditional method. View Full-Text
Keywords: bad streaks noise; line tracing method; DN values break; Lagrange polynomial method; DN values succession bad streaks noise; line tracing method; DN values break; Lagrange polynomial method; DN values succession
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Wang, B.; Bao, J.; Wang, S.; Wang, H.; Sheng, Q. Improved Line Tracing Methods for Removal of Bad Streaks Noise in CCD Line Array Image—A Case Study with GF-1 Images. Sensors 2017, 17, 935.

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