Wiener filter suppresses noise efficiently. However, it makes the out image blurred. Curvelet preserves the edges of natural images perfectly, but, it produces visual distortion artifacts and fuzzy edges to the restored image, especially in homogeneous regions of images. In this paper, a new image denoising framework based on Curvelet transform and wiener filter is proposed, which can stop nois...

We develop an efficient MRI denoising algorithm based on sparse representation and curvelet transform with variance stabilizing transformation framework. By using sparse representation, a MR image is decomposed into a sparsest coefficients matrix with more no of zeros. Curvelet transform is directional in nature and it preserves the important edge and texture details of MR images. In order to g...

As a latest multiresolution analysis method, curvelet transform has improved directional elements with anisotropy and better ability to represent sparsely edges and other singularities along curves. To reduce the dimensionality of facial image and improve the recognition rate, a face recognition system based on curvelet transform and Least Square Support Vector Machine (LS-SVM) has been develop...

In this paper, we proposed a technique for facial expression representation based on combination of Curvelet Transform and Complete Local Binary Pattern (CLBP). The curvelet transform offers improved directional capability, better ability to represent edges and other singularities along curves as compared to other traditional multiscale transforms. Hence, we transform original face images to fr...

Resolution enhancement(RE) methods that are independent of wavelets i.e. interpolation methods leads to blurring as high frequency components are lost.RE scheme based on Discrete wavelet transform(DWT) leads to artifacts due to shift variant property. A complex wavelet-domain image resolution enhancement algorithm based on dual-tree complex wavelet transform (DT-CWT) with non local means(NLM) a...

Edge detection is an important assignment in image processing, as it is used as a primary tool for pattern recognition, image segmentation and scene analysis. Simply put, an edge detector is a high-pass filter that can be applied for extracting the edge points within an image. Edge detection in the spatial domain is accomplished through convolution with a set of directional derivative masks in ...

In this paper, a denoising and binarization scheme of document images corrupted by white Gaussian noise and Impulse noise is presented using Curvelet Transform. The ability of sparse representation and edge preservation of Curvelet transform is utilized. Impulse noise gets added during document scanning or after binarization of scanned document images. White Gaussian noise corrupts the document...

The work being presented here describes a novel approach for human emotion recognition based on curvelet transform. Our approach of the emotion recognition is motivated by the fact that emotions expressed more obviously by the facial curves, hence the technique proficient in capturing the edge singularity as well as the curve singularities shall yield the better results i.e. curvelets. Curvelet...