A Noise Line Detection Method Using Spatial Correlation of NOAA AVHRR Channels

Kawano, K.; Kudoh, J.

doi:10.1109/igarss.2006.615

Cited by 2 publications

(3 citation statements)

References 1 publication

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“…In hard thresholding, the decomposed wavelet coefficients below the threshold level λ are set to zero and coefficients which are above the threshold are unaltered [17]. Suppose X, Y are input and output then the hard threshold Th(Y, λ) is given in equation (3).…”

Section: Threshold Selectionmentioning

confidence: 99%

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

Rajeswari¹,

Reddy²,

Jagadamba³

2018

IJET

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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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Section: Threshold Selectionmentioning

confidence: 99%

“…that can decrease the quality and visual perception of images [3,4]. This may have an impact on the accuracy of the image analysis.…”

Section: Introductionmentioning

confidence: 99%

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

Rajeswari¹,

Reddy²,

Jagadamba³

2018

IJET

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show abstract

“…However, sometimes AVHRR data acquisition process may be affected by several factors (senor failures, imperfectly transparent atmosphere, daily and seasonal variations in the amount of solar radiation received at the surface, imperfections in scanning instruments, signal transmission and/or decoding and atmospheric effects, etc.) that can decrease the quality and visual perception of images [3,4]. This may have an impact on the accuracy of the image analysis.…”

Section: Introductionmentioning

confidence: 99%

Stationary wavelet transform based radiometric error correction technique for NOAA-AVHRR sensor data

Rajeswari¹,

Reddy²,

Jagadamba³

2018

IJET

View full text Add to dashboard Cite

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, 19 AVHRR/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 (SD) and by visual inspection. The SWT based method can remove radiometric errors 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.

show abstract

A Noise Line Detection Method Using Spatial Correlation of NOAA AVHRR Channels

Cited by 2 publications

References 1 publication

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

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

Stationary wavelet transform based radiometric error correction technique for NOAA-AVHRR sensor data

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