In this paper, we introduce a SAR images target recognition approach based on the contourlet transform and support vector machine (SVM), which takes technological advantages of both SVM and the contourlet transform for feature extraction.

Discrete Wavelet Transform (DWT) has demonstrated far superior to previous Discrete Cosine Transform (DCT) and standard JPEG in natural as well as medical image compression. Due to its localization properties both in special and transform domain, the quantization error introduced in DWT does not propagate globally as in DCT. Moreover, DWT is a global approach that avoids block artifacts as in t...

In this paper, we analyze and compare the performance of fusion methods based on four different transforms: i) wavelet transform, ii) curvelet transform, iii) contourlet transform and iv) nonsubsampled contourlet transform. Fusion framework and scheme are explained in detail, and two different sets of images are used in our experiments. Furthermore, eight different performancemetrics are adopte...

In this paper we present a lossy image coder based in multiscale and directional contourlet transform which allows edge preserving in decompressed images. The preserving task is made by capture the edge points of an image using a robust and efficient edge detector known as Smallest Univalue Segment Assimilating Nucleus (SUSAN). The resulting edges coordinates are used as a priori knowledge of t...

Image fusion combines information from multiple images of the same scene to get a composite image that is more suitable for human visual perception or further image-processing tasks. In this paper the multi source medical images like MRI (Magnetic Resonance Imaging), CT (computed tomography) & PET (positron emission tomography) are fused using different multi scale transforms. We compare variou...

In this study, we propose a new image fusion method by combining Multiwavelet with Contourlet transform. Firstly, transform the source multifocus images successively by Multiwavelet and Conotourlet. Secondly, we employ the LEM rule to fuse the lowpass coefficients and PCCN rule to fuse the hightpass coefficients. Finally, inversely transform the fused coefficients successively by Contourlet and...

Image fusion is the process of integration of two or more source images into a single fused image. The resultant fused image is used to retain the important features of the source images. Color image fusion is the process of integrating one or more color images to enhance clarity of the image. The application of color image fusion simplifies object identification and helps in better cognition. ...

In this paper we put forward an image fusion algorithm based on Wavelet Transform, Second Generation Curvelet Transform and Nonsubsampled Contourlet Transform. Here we analyze the characteristics of NSCT along with Wavelet and Curvelet Transform for simulation experiments on multi-focus images. Here it includes multiresolution analysis ability in wavelet transform, also has better direction abi...

⎯A novel and efficient speckle noise reduction algorithm based on Bayesian contourlet shrinkage using contourlet transform is proposed. First, we show the sub-band decompositions of SAR images using contourlet transforms, which provides sparse representation at both spatial and directional resolutions. Then, a Bayesian contourlet shrinkage factor is applied to the decomposed data to estimate th...

This paper presents a new approach of texture image classification based on nonsubsampled contourlet transform, Local binary patterns and Support vector machines. Nonsubsampled contourlet transform and Local binary patterns are used to extract texture features of images, Support vector machines are used to classify texture images. Nonsubsampled contourlet transform has translation invariability...