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 ...

The recognition of a person based on biological features are efficient compared with traditional knowledge based recognition system. In this paper we propose Face Recognition using Wrapping Curvelet Transform (FRWCT). The Wrapping Curvelet Transform (WCT) is applied on face images of database and test images to derive coefficients. The obtained coefficient matrix is rearranged to form WCT featu...

In recent years, Curvelet Transform is the most preferred technique for image compression. It is proposed that an efficient and fast image compression scheme based on all level curvelet coefficients with SPIHT (Set Partitioning in Hierarchical Trees).After many passes of coding with SPIHT, it degrades the coding performance.There was a need of a transform that handles two dimensional singularit...

The curvelet transform is a recently introduced non-adaptive multi-scale transform that have gained popularity in the image processing field. In this paper, we study the effect of customized tiling of frequency content in the curvelet transform. Specifically, we investigate the effect of the size of the coarsest level and its relationship to denoising performance. Based on the observed behavior...

A new image denoising method based on curvelet transform is proposed. The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. Here, we pursue "true" two-dimensional transform that can capture the intrinsic geometrical structure that is key in visual information. Deno...

Continuity along reflectors in seismic images is used via Curvelet representation to stabilize the convolution operator inversion. The Curvelet transform is a new multiscale transform that provides sparse representations for images that comprise smooth objects separated by piece-wise smooth discontinuities (e.g. seismic images). Our iterative Curvelet-regularized deconvolution algorithm combine...

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. ...

A new method which is suitable for enhancing the color microscopic image quality based on HSV color space and curvelet transform is presented in this paper. The color microscopic image is firstly divided into hue, saturation and value components from RGB color space to HSV color space through the color space conversion. The value component is decomposed by the curvelet transform. A modulus squa...

A flexible multiscale and directional representation for images is proposed. The scheme combines directional filter banks with the Laplacian pyramid to provides a sparse representation for twodimensional piecewise smooth signals resembling images. The underlying expansion is a frame and can be designed to be a tight frame. Pyramidal directional filter banks provide an effective method to implem...

A flexible multiscale and directional representation for images is proposed. The scheme combines directional filter banks with the Laplacian pyramid to provides a sparse representation for twodimensional piecewise smooth signals resembling images. The underlying expansion is a frame and can be designed to be a tight frame. Pyramidal directional filter banks provide an effective method to implem...