An Image denoising method combining dt-cwt and Fourth-order PDE
Abstract
I It is proved that image gray level tends to be piecewise constant in the low order partial differ Ential
equation denosing model. Considering the applications of wavelet multi-scale decomposition in image processing, a kind of remote sensing image Deno Ising model combining dual tree complex wavelet transform and fouth order
partial differential equation are put forward. Firstly, the noise images are multiscalely decomposted by
DT-CWT. Then The low frequency components are reserved and noise in high frequency components of other
layer are removed by th E Fourth order PDE model. Finally, the high and low frequency components of the the
corresponding layer are reconstructed the final IMA Ge. According to the denoising experiments results of the
ZY-3 satellite images which have different noise intensities proved that's average PSNR of results by proposed
model increases 1~2 DB and the structural similarity increases as. The denoising model proposed can effectively
preserve the image details while removing noise.
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