Image De-noising Using Dual-tree Complex Wavelet Transform for Satellite Applications

This paper presents a unique thanks to cut back noise introduced or exacerbated by image sweetening strategies; especially algorithms supported the random spray sampling technique, however not solely. Multi scale decomposition based on dual-tree complex wavelet transform and edge preservation is presented for SRE of the satellite images. Resolution enhancement schemes (which are not based on wavelets) suffer from the drawback of losing high frequency contents (which results in blurring). A wavelet-domain approach based on dual-tree complex wavelet transform (DT-CWT) and nonlocal means is used for RE of the satellite images. A satellite input image is decomposed by DT-CWT (which is nearly shift invariant) to obtain high-frequency sub bands. The high-frequency sub band and the lowresolution (LR) input image are interpolated using the bi-cubic interpolator. The result's a map of the directional structures gift within the non-enhanced image. Same map is then wont to shrink the coefficients of the improved image. The contracted coefficients and also the coefficients from the non-enhanced image area unit then mixed in keeping with information radial asymmetry. The simulated results will show that technique used in this process provides better accuracy rather than prior methods.