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Wang Rongbin, Zeng Chao, Jiang Wan, Li Pingxiang. Terra MODIS band 5th stripe noise detection and correction using MAP-based algorithm[J]. Infrared and Laser Engineering, 2013, 42(1): 273-277.
Citation: Wang Rongbin, Zeng Chao, Jiang Wan, Li Pingxiang. Terra MODIS band 5th stripe noise detection and correction using MAP-based algorithm[J]. Infrared and Laser Engineering, 2013, 42(1): 273-277.

Terra MODIS band 5th stripe noise detection and correction using MAP-based algorithm

  • Received Date: 2012-05-22
  • Rev Recd Date: 2012-06-19
  • Publish Date: 2013-01-25
  • Since 1 of the 20 detectors in Terra MODIS band 5 (1.230-1.250 m) are noisy, there are sharp and repetitive stripe noise over the entire image. As for MODIS geolocated data, the stripe noise are irregular and sometimes uncontinuous, it brings a difficult problem to the image retrieving process. A detection method was presented to extract the stripe noise, and a maximum a posteriori (MAP) based algorithm was applied to correct the contaminated pixels. A local gradient based method was used to detect the abnormal pixels. In the MAP method, the likelihood probability density function (PDF) was proposed based on a linear image noise model, and a Huber-Markov model was employed as the prior PDF. The gradient descent optimization method was used to receive the destriped image. The proposed algorithm had been tested using a Terra MODIS band 5 geolocated image. The recovered images demonstrate that the proposed algorithm can remove the irregular stripes effectively. The power spectrum also shows a satisfactory result.
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Terra MODIS band 5th stripe noise detection and correction using MAP-based algorithm

  • 1. The State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430079,China;
  • 2. Chinese Land Surveying and Planning Institute,Ministry of Land Resources,Beijing 100035,China;
  • 3. School of Resource and Environmental Science,Wuhan University,Wuhan 430079,China

Abstract: Since 1 of the 20 detectors in Terra MODIS band 5 (1.230-1.250 m) are noisy, there are sharp and repetitive stripe noise over the entire image. As for MODIS geolocated data, the stripe noise are irregular and sometimes uncontinuous, it brings a difficult problem to the image retrieving process. A detection method was presented to extract the stripe noise, and a maximum a posteriori (MAP) based algorithm was applied to correct the contaminated pixels. A local gradient based method was used to detect the abnormal pixels. In the MAP method, the likelihood probability density function (PDF) was proposed based on a linear image noise model, and a Huber-Markov model was employed as the prior PDF. The gradient descent optimization method was used to receive the destriped image. The proposed algorithm had been tested using a Terra MODIS band 5 geolocated image. The recovered images demonstrate that the proposed algorithm can remove the irregular stripes effectively. The power spectrum also shows a satisfactory result.

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