Automated classification of brain MRI is important for the analysis of tumor. In this paper magnetic resonance imaging (MRI) is considered to solve the problem of automatic classification of brain images. It presents the classification system with three stages. It consists of discrete wavelet decomposition of the image, texture feature extraction from the LH and HL sub bands and final classific...

-In this paper the technique for resolution and contrast enhancement of satellite geographical images based on discrete wavelet transform (DWT), stationary wavelet transform (SWT) and singular value decomposition (SVD) has been proposed. In this, the noise is added in the input low resolution and low contrast image. The median filter is used remove noise from the input image. This low resolutio...

This paper proposes an embedded rate scalable wavelet-based image coding algorithm. We introduce a simple and efficient approach for coding the positions and the signs of the wavelet coefficients that will be transmitted as nonzero values in an embedded scheme. This algorithm is based on recursive partitioning of the significant wavelet sub-bands (RPSWS). The proposed algorithm produces a fully...

Secret communication over network has captured the imagination of researchers for many years. Steganography and Digital watermarking techniques are used to protect copyright information, address digital rights management, and conceal secrets. Secret data hiding techniques provide an interesting challenge for digital forensic investigations. Research into steganalysis techniques aids in the disc...

This paper describes an approach for accomplishing sub-octave wavelet analysis and its discrete implementation for noise reduction and feature enhancement. Sub-octave wavelet transforms allow us to more closely characterize features within distinct frequency bands. By dividing each octave into sub-octave components, we demonstrate a superior ability to capture transient activities in a signal o...

This paper describes an approach for accomplishing sub-octave wavelet analysis and its discrete implementation for noise reduction and feature enhancement. Sub-octave wavelet transforms allow us to more closely characterize features within distinct frequency bands. By dividing each octave into sub-octave components, we demonstrate a superior ability to capture transient activities in a signal o...

This paper describes an approach for accomplishing sub-octave wavelet analysis and its discrete implementation for noise reduction and feature enhancement. Sub-octave wavelet transforms allow us to more closely characterize features within distinct frequency bands. By dividing each octave into sub-octave components, we demonstrate a superior ability to capture transient activities in a signal o...

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...

Recent years have seen tremendous increase in the generation, transmission, and storage of color images. A new lossless image compression method for progressive-resolution transmission of color images is carried out in this paper based on spatial and spectral transforms. Reversible wavelet transforms are performed across red, green, and blue color sub bands first. Then adaptive spectral transfo...

Image Fusion, a technique which combines complimentary information from different images of the same scene so that the fused image is more suitable for segmentation, feature extraction, object recognition and Human Visual System. In this paper, a simple yet efficient algorithm is presented based on contrast using wavelet packet decomposition. First, all the source images are decomposed into low...