We propose in this paper a new deconvolution approach, which uses both the wavelet transform and the curvelet transform in order to bene2t from the advantages of each. We illustrate the results with simulations. ? 2003 Elsevier B.V. All rights reserved.

The prevalent cause of death in human being is brain tumor. A brain tumor is a mass or growth of anomalous cells in brain. The detection of brain tumor is difficult task. Image processing provides relevant techniques for efficient detection. In the proposed technique, first the features of MRI (Magnetic Resonance Imaging) images are extracted with curvelet transform, and then these features are...

In this paper, a computer-aided diagnostic (CAD) system for the diagnosis of benign and malignant liver tumors from computed tomography (CT) images is presented. Liver is segmented from abdominal CT images using adaptive threshold and morphological processing. Each suspicious tumor region is automatically extracted from the segmented liver using FCM technique and the textural information obtain...

In this paper, a novel feature extraction scheme is proposed, based on multiresolution fast discrete curvelet transform for computer-aided diagnosis of liver diseases. The liver is segmented from CT images using adaptive threshold detection and morphological processing. The suspected tumour region is extracted from the segmented liver using FCM clustering. The textural information obtained from...

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...

All the time, there is a demand of High-Resolution (HR) images in electronic imaging applications. Super-Resolution (SR) is an approach used to restore High-Resolution (HR) image from one or more Low-Resolution (LR) images. The goal of SR is to extract the independent information from each LR image in that set and combine the information into a single high resolution (HR) image. The quality of ...

Denoising of Positron Emission Tomography (PET) images is a challenging task due to the inherent low signal-to-noise ratio (SNR) of the acquired data. A pre-processing denoising step may facilitate and improve the results of further steps such as segmentation, quantification or textural features characterization. Different recent denoising techniques have been introduced and most state-of-the-a...

In real time applications Image Compression plays a major role in storage memory and transmission bandwidth. As many compression methods are existing, selection of compression methods depends upon the quality in image reconstruction. Two popular compression methods are Wavelet and Ridgelet methods. Wavelet method has affected by the blocking artifacts and Ridgelet is designed to handle only lin...

The fusion of medical images taken at the same slice/part of the body by differentmodalities is very useful technique in medical diagnosis. Medical image fusion tried withwavelet transform methods proved to be image dependent and preservation of highfrequency contents of the image by wavelets are also not satisfactory. In this work, curvelettransform is applied for fusion wi...

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...