Contourlet

About: Contourlet is a research topic. Over the lifetime, 3533 publications have been published within this topic receiving 38980 citations.

Remote sensing image fusion method based on contourlet transform and guided filter

Abstract: The invention discloses a remote sensing image fusion method based on contourlet transform and guided filter, mainly to solve problems of image contrast reduction and unclear image edge characteristic expression caused by the existing image fusion method. The method particularly comprises steps: the same target is photographed to obtain a to-be-fused multispectral image and a to-be-fused panchromatic image for contourlet transform, and corresponding high-frequency coefficients and low-frequency coefficients are obtained; a weighted fusion method based on guided filter is applied to the high-frequency coefficients of the two source images for fusion, and high-frequency coefficients of the fused image are obtained; a region energy maximum method is applied to the low-frequency coefficients of the two source images for fusion, and low-frequency coefficients of the fused image are obtained; contourlet inverse transform is applied to the high-frequency coefficients and the low-frequency coefficients after fusion, and a fused image of the target is obtained. The method of the invention combines the contourlet transform and the guided filter, the fusion effects are obvious, the image evaluation parameters are high, and the method can be applied to aspects of image analysis and processing, surveying and mapping, geology and the like.

The remote sensing image enhancement based on nonsubsampled contourlet transform and unsharp masking

Abstract: To restrain pseudo-Gibbs phenomenon, low contrast and blurred phenomenon in the process of image enhancement, a new method based on the nonsubsampled contourlet transform and the unsharp masking is proposed in this paper. The proposed method utilizes the shift-invariance of nonsubsampled contourlet transform to restrain the pseudo-Gibbs phenomenon, and then enhance details of the image by unsharp masking. We achieved an increase in image definition by 54.5%, the mean increased by 15.6%, whereas the standard deviation increased by 54.5% compared with the unsharp masking method. To the noisy image, we achieved an increase in image definition by 35.4%, the mean increased by 2.2%, whereas the standard deviation increased by 34.9% compared with the unsharp masking method. Copyright © 2013 John Wiley & Sons, Ltd.

Digital image watermarking method against geometrical attack based on contourlet transform

Abstract: The invention discloses a contourlet-transform-based anti-geometric attack digital image watermarking method, mainly solving the problem of poor robustness of the existing similar method. The invention is technically characterized in that the method completes watermark synchronization through a geometric moment method to realize watermark embedding and extraction in a contourlet transform domain, that is, to calculate a first-order origin moment containing a watermark image I when the watermark is embedded, and reserve the first-order origin moment for the estimation of the geometric attack parameters during extraction; during watermark extraction, to estimate the geometric transformation parameters through the attacked first-order origin moment and a second-order center moment containing watermarks, and to recover the attacked watermarks through contourlet transform. The method of the invention has the advantages of strong anti-geometric attack ability, good watermark extracting effect and self-positioning watermark embedded location, which can be used for safety protection of digital multimedia product copyright.

MR image monomodal registration based on the nonsubsampled contourlet transform and mutual information

Abstract: Image registration methods based on mutual information criteria have been widely used in multimodal medical image registration and have shown hopeful results. Although they are also used in monomodal image registration, their performance is not as excellent as that in multimodal registration. In general, the majority of registration methods consist of the following four steps: feature extraction, feature matching, transformation of the models and, finally, resampling the image. It was noted that the accuracy of the registration process depends on matching a feature and control points (CP) detection. Therefore in this paper has been to rely on this feature for magnetic resonance image (MRI) monomodal registration. We have proposed to extract the salient edges and extracted a CP of medical images by using efficiency of multiresolution representation of data nonsubsampled contourlet transform (NSCT). The MR images were first decomposed using the NSCT, and then Edge and CP were extracted from bandpass directional subband of NSCT coefficients and some proposed rules. After edge and CP extraction, mutual information (MI) was adopted for the registration of feature points and translation parameters are calculated by using particle swarm optimization (PSO). We implement experiments to evaluate the performance of the NTSC and MI similarity measures for 2-D monomodal registration. The experimental results showed that the proposed method produces totally accurate performance for MR image monomodal registration.

Fingerprint Image Compression Based on Directional Filter Banks and TCQ

Abstract: A novel compression algorithm for fingerprint image is proposed. Wavelet-Based Contourlet Transform (WBCT), which is based on wavelet transform and directional filter banks (DFBs), can be capable of efficiently approximating natural images containing contours and oscillatory patterns. To reduce frequency scrambling, a new scheme based on maximally-flat filters which implements the DFBs is proposed. A quadtree sorting procedure, similar to SPIHT, is used to explicitly form classes of WBCT coefficients. The classes are encoded using arithmetic and trellis-coded quantization. The resulting encoding algorithm offers consistent improvement over SPIHT performance. Simulations show that the new encoding algorithm provides improved encoding performance over SPIHT and preserves more fingerprint image details.