This paper presents a method of compressing still images combining the powerful features of support vector machine (SVM) for machine learning with discrete wavelet transform (DWT) in image transformation. DWT, based on the ‘haar’ wavelet, has been used to transform the image and the coefficients acquired from DWT are then trained with SVM using Gaussian kernel. SVM has the property that it sele...

In many applications, old data in time series become less important as time elapses, which is a big challenge to traditional techniques for dimension reduction. To improve Discrete Wavelet Transform (DWT) for effective dimension reduction in this kind of applications, a new method, largest-latest-DWT, is designed by keeping the largest k coefficients out of the latest w coefficients at each lev...

The digital revolution has resulted in explosion of knowledge. It has encouraged and motivated digitization of the intellectual artefact. This creates issues of piracy and copyright. In this paper, the authors propose a novel logo based watermarking scheme for image copyright protection using fuzzy inference system (FIS), discrete wavelet transform (DWT) and human visual system (HVS). Wavelet t...

Edge detection improves image readability and it is an important part of images preprocessing aimed to their segmentation and automatic recognition of their contents. This paper describes selected methods of edge detection in magnetic resonance images, with the emphasis on the wavelet transform use. The first part briefly describes the mathematical background of the wavelet transform, including...

The Integer Wavelet Transform (IWT), applied to lossy image compression, yields rate-distortion performance which are generally slightly inferior to the Discrete Wavelet Transform (DWT). In this paper, we propose a simple method which, based on the analysis of the IWT signal representation mechanism, is able to raise the IWT performance up to the DWT level. The method can be pro tably employed ...

Abstract. In this paper, a modified version of the discrete wavelet transform (DWT), distinguishing itself with visibly improved space localization properties and noticeably extended potential capabilities, is proposed. The key point of this proposal is the full decorrelation of wavelet coefficients across the lower scales. This proposal can be applied to any DWT of higher orders (Le Gall, Daub...

Discrete wavelet transforms (DWTs) are mathematical tools that are useful for analyzing geophysical time series. The basic idea is to transform a time series into coefficients describing how the series varies over particular scales. One version of the DWT is the maximal overlap DWT (MODWT). The MODWT leads to two basic decompositions. The first is a scale-based analysis of variance known as the...

In this correspondence, an image resolution enhancement technique based on interpolation of the high frequency subband images obtained by discrete wavelet transform (DWT), stationary wavelet transform (SWT) and the input image has been proposed. The image quality has been enhanced by incorporating stationary wavelet transform (SWT). DWT decomposes an input image into four subbands. Out of these...

In this paper a novel invisible robust watermarking scheme for embedding and extracting a digital watermark in an image is presented. The novelty lies in determining perceptually important coefficients of transform in the host image using simple Haar Wavelet Transform (HWT) and Genetic Algorithm(GA)-Particle Swarm Optimization(PSO) based hybrid optimization. Invisible watermark is embedded such...