The purpose of this investigation is to apply 3D wavelet denoising to resolve spatial, as well as spectral, data in Landsat images. The use of multiple thresholds will be extended to achieve image classification. Wavelet denoising has been shown to be effective for noise reduction in 1D signals and 2D images. 3D wavelet transforms have the potential for multi-resolution surface reconstruction from volume data. 3D wavelet denoising will be applied to spatial potential for multi-resolution surface reconstruction form volume data. 3D wavelet denoising will be applied to spatial and spectral data. Landsat images were produced from a multispectral scanner on Landsat satellites. Wavelet have been used to achieve some level of image classification. Finer classification can be achieved in agricultural areas because of temporal difference between crops and because of spectral difference sin transmission spectra. Varying threshold should achieve image classification based on spectral difference between crops. 3D wavelet data processing is expected to offer greater potential for improving resolution of volume data. Use of multi threshold for spectral resolution might be usefully applied to images generated by nonvisible wavelengths: radar, IR and laser radar.