Yuqing Ma
ABSTRACT
Aiming at the problem of edge feature loss caused by conventional threshold function in wavelet transform, a new adaptive threshold function denoising algorithm is proposed based on improved threshold. The algorithm takes advantages of the improved threshold functions, and takes the scale of the current wavelet decomposition as a function adjustment factor, so that the function can be adjusted by adaptive scale transformation, which is more in line with the actual distribution of noise in each scale. A few noisy remote sensing images are tested and the simulation results of MATLAB confirm the merits of the proposed denoising technique compared with other wavelet-based techniques by measuring evaluation metrics such as signal-to-noise ratio and mean square error. Furthermore, the improved threshold function can obtain better visual effects which ensures the detail features in remote sensing images are better preserved.
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Index Terms
- Wavelet Denoising of Remote Sensing Image Based on Adaptive Threshold Function
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