Article history: Available online xxxx Blocking effect caused by coefficient quantification during image compression is an annoying problem. The main effect of quantification is to eliminate high frequency component in the image. Therefore, it will lead to noticeable discontinuous leaps which causes block effect and degrade the image. A deblocking method based on Curvelet transform is proposed ...

For image processing, it is very necessary that the selection of transform. In this paper, a comparative analysis of curve let transform with other transform for image processing .In this we proposed the applications of curve let transform in the field of image Compression ,phase recognition and feature extraction. For higher compression with quality reconstruction .The Wavelets gave a differen...

Medical Image Processing is one of the critical applications of image processing that requires more accuracy than other application. The presented work is focused on the detection of infection or wound identification for skin images. The work is defined as color model based hybrid approach in which the statistical analysis is combined with curvelet decomposition to identify the effective infect...

Texture represents spatial or statistical repetition in pixel intensity and orientation. Brain tumor is an abnormal cell or tissue forms within a brain. In this paper, a model based on texture feature is useful to detect the MRI brain tumor images. There are two parts, namely; feature extraction process and classification. First, the texture features are extracted using techniques like Curvelet...

This paper presents a novel image fusion method, suitable for pan-sharpening of multispectral (MS) bands, based on multi-resolution analysis (MRA). The low-resolution MS bands are sharpened by injecting high-pass directional details extracted from the high-resolution panchromatic (Pan) image by means of the curvelet transform, which is a non-separable MRA, whose basis function are directional e...

A curvelet denoising method has been proposed to reduce the time domain noise to improve the detection performance in the distributed fiber vibration sensing system based on phase-sensitive optical time domain reflectometry. The raw Rayleigh backscattering traces are regarded as a gray image and the random noise can be eliminated by the curvelet transform; hence, the amplitude difference induce...

The widely used feature representation scheme for magnetic resonance (MR) image classification based on low-frequency subband (LFS) coefficients of wavelet transform (WT) is ineffective in presence of common MR imaging (MRI) artifacts (small rotation, low dynamic range etc.). The directional information present in the high-frequency subbands (HFSs) can be used to improve the performance. Moreov...

bstract. We perform a statistical analysis of curvelet coefficients, istinguishing between two classes of coefficients: those that conain a significant noise-free component, which we call the “signal of nterest,” and those that do not. By investigating the marginal statisics, we develop a prior model for curvelet coefficients. The analysis f the joint intraand inter-band statistics enables us t...

Image fusion has wide range of application in satellite images, general photography, medical images etc. Image fusion is the process in which we combine two or more images or some features of images to form a single image which is free from distortion and does not loses its information. Images which are taken from different angles sometimes needs to be fused together to form a single image whic...

In this paper, we present multimodal 2D +3D face recognition method using block based curvelet features. The 3D surface of face (Depth Map) is computed from the stereo face images using stereo vision technique. The statistical measures such as mean, standard deviation, variance and entropy are extracted from each block of curvelet subband for both depth and intensity images independently.In ord...