Stationary Wavelet Transform based Radiometric Error Correction Technique for NOAA-AVHRR sensor data

  • Authors

    • V Raja Rajeswari
    • S Narayana Reddy
    • P Jagadamba
    2018-04-06
    https://doi.org/10.14419/ijet.v7i2.15.12567
  • NOAA-AVHRR images, AVHRR sensor, radiometric errors, Stationary Wavelet Transform (SWT), wavelet thresholding.

  • Abstract

    Due to the inaccuracy of the sensing devices remote sensing images contain radiometric errors, which can be severe in many cases. Therefore, the preprocessing is an inevitable step in the remote sensing image analysis. This paper presents radiometric errors and evaluates methodologies to retrieve information contained in images by means of filtering in the spatial domain and wavelet domain. Among those, the wavelet techniques are more effective to reduce noise because of their ability to capture the energy of a signal in fewer wavelet coefficients. In this study, Stationary Wavelet Transform (SWT) method and its application to NOAA -18, 19AVHRR/3 channel 3 and channel 4 images to correct radiometric error is presented. Qualitative and quantitative analysis was carried to evaluate the performance of SWT method, both by measuring the Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM), mean value, standard deviation and by visual inspection. The SWT based method can remove radiometric error effectively and preserves radiometric information to a desirable amount. From the results, SWT based method is better in smoothness and accuracy than the conventional mean filter, median filter and Discrete Wavelet Transform (DWT) based method

     

     

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  • How to Cite

    Raja Rajeswari, V., Narayana Reddy, S., & Jagadamba, P. (2018). Stationary Wavelet Transform based Radiometric Error Correction Technique for NOAA-AVHRR sensor data. International Journal of Engineering & Technology, 7(2.15), 177-181. https://doi.org/10.14419/ijet.v7i2.15.12567

    Received date: 2018-05-07

    Accepted date: 2018-05-07

    Published date: 2018-04-06