Research On Contourlet Transform And Its Application On Image Processing

Wavelets have the advantages of multiscale and multiresolution analysis, which are widely used in signal analysis and processing. The wavelet transform is optimal in capturing the one-dimensional singularities. As a result of a separable extension from 1-D bases, wavelets can not make the most of geometrical characters of the images. While the edge, contour or texture contains much information in which we are interested, wavelets are not the optimal representations in higher dimensions. Because of the limitation, a theory named Multiscale Geometry Analysis (MGA) was proposed. This theory is developing in theories and applications.The purpose of contourlet transform is to obtain sparse presentation of images, it inherets wavelets'local supporting and multiresolution property, besides it has anisotropy property. Contourlet transform decomposes images into band-pass directional subband using PDFB. Contourlet transform approximates images using contourlets. Contourlet can present edges and texture of images more effectively than wavelet transform.But contourlet has the redundancy problem, which can be solved by this article outlines of the study on wavelet-based contourlet transform. It has been very good application in two-dimensional data processing, because the wavelet-based contourlet transform is sensitive to the direction of image texture.First proposed the image denoising algorithm based on wavelet-based contourlet transform. As the experimental results show, these denoising algorithms significantly improved visual effect, PSNR value significantly improves the image by compared contourlet transform and Wavelet transform.Second deep studied the contourlet transform at the image fusion application. As the experimental results show, it significantly improved the fusion image visual effect by compared with the wavelet algorithm of image fusion.Contraposed the limitations at wavelet transform indicating 2-D image, and put forward a kind of contourlet domain of digital image watermarking algorithm based on chaos encryption. Finally analyzed and verified the robustness of the algorithm by experiments.