Image Fusion is a data fusion technique which combines information of the two images which has varied information to form a new single image. The objective is to fuse an MR image and CT image of the same organ to obtain a single image containing as much information as possible. In this paper Wavelet Transform and Fast Curvelet Transform are highlighted to perform the image fusion of MR image an...

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 registration is a crucial step in most image processing tasks for which the final result is achieved from a combination of various resources. In general, the majority of registration methods consist of the following four steps: feature extraction, feature matching, transform modeling, and finally image resampling. As the accuracy of a registration process is highly dependent to the fe...

Motion blur can significantly degrade the quality of an image. The images become blurred due to camera movements, object movements or displacements of pixels. Deblurring of an image is done by processing an image through curvelet transform and removal of noise by median filter. Experimental results show that proposed deblurring technique and accuracy measurement using peak signal to noise ratio...

Due to the development of CT (Computed Tomography), MRI (Magnetic Resonance Imaging), PET (Positron Emission Tomography), EBCT (Electron Beam Computed Tomography), SMRI (Stereotactic Magnetic Resonance Imaging), etc. has enhanced the distinguishing rate and scanning rate of the imaging equipments. The diagnosis and the process of getting useful information from the image are got by processing t...

We propose a robust interpolation scheme for aliased regularly sampled seismic data that uses the curvelet transform. In a first pass, the curvelet transform is used to compute the curvelet coefficients of the aliased seismic data. The aforementioned coefficients are divided into two groups of scales: alias-free and alias-contaminated scales. The alias-free curvelet coefficients are upscaled to...

Barcode localization is the main challenge in developing an image-based barcode reading system. Bar codes are able to carry both explicit information and a database key, by encoding a series of characters or symbols. This paper deals with localization of European Article Number-13 (EAN-13) barcode in an image. A new approach for detecting and locating bar-codes is introduced here, which is base...

In this paper, an improved method based on Curvelet Transform using different window functions is presented for the speech enhancement. The window function is used for preprocessing of speech signals. In this method, instead of using two-dimensional (2-D) discrete Fourier Transform, Curvelet transform is employed with spectral magnitude subtraction method. General terms Spectral Substraction Me...

Texture classification has played an important role in many real life applications. Now, classification based on wavelet transform is being very popular. Wavelets are very effective in representing objects with isolated point singularities, but failed to represent line singularities. Recently, ridgelet transform which deal effectively with line singularities in 2-D is introduced. But images oft...