Images are very important documents nowadays. To work with them in some applications they need to be compressed, more or less depending on the purpose of the application. To reduce transmission cost and storage requirements, competent image compression schemes without humiliation of image quality are required. Several image coding techniques were developed so far for both lossless and lossy ima...

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.

This technical report is a companion to [4]. We prove that Fourier Integral Operators admit ‘optimally’ sparse representations in curvelet frames. We give all the necessary definitions and notations for the discussion to be self-contained.

The Image fusion is a data fusion innovation which keeps images as main research substance which refers to the strategies that integrate multi-images of the same scene from multiple image sensor data or integrate multi images of the same scene at different times from single image sensor. In this paper we describes a novel image fusion method, is suitable for pan-sharpening of multispectral (MS)...

The large numbers of images has posed increasing challenges to computer systems to store and manage data effectively and efficiently. This paper implements a CBIR system using different feature of images through four different methods, two were based on analysis of color feature and other two were based on analysis of combined color and texture feature using wavelet coefficients of an image. To...

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...

In RBIR, texture features are crucial in determining the class a region belongs to since they can overcome the limitations of color and shape features. Two robust approaches to model texture features are Gabor and curvelet features. Although both features are close to human visual perception, sufficient information needs to be extracted from their sub-bands for effective texture classification....

The clarity of medical image, which is directly acquired from the scanning machine, is very less. Image enhancement is one of the best and efficient techniques to increase the quality of image. A combined approach of different techniques such as Wavelet, Curvelet and Multiple Kernel Fuzzy C-Means algorithm was carry out in this paper. Wavelet and Curvelet transforms are used for denoising purpo...

We present a multi-frame information involved image denoising approach through spatiotemporal GSM (Gaussian Mixture Scales Modeling) of image Curvelet statistics both considering of the innerframe and inter-frame statistics. By using the Bayes inference based least square estimation, we construct a Bayesian Least Squared GSM (BLS-GSM) based image denoising model for single image noise cancellat...