Image signals are always disturbed by noise during their transmission, such as in mobile or network communication. The received image quality is significantly influenced by noise. Thus, image signal denoising is an indispensable step during image processing. As we all know, most commonly used methods of image denoising is Bayesian wavelet transform estimators. The Performance of various estimat...

The Resolution enhancement (RE) schemes (which are not based on wavelets) has one major drawback of losing high frequency contents (which results in blurring). The discrete wavelettransform-based (DWT) RE scheme generates artifacts (due to a DWT shift-variant property). A wavelet-domain approach based on dual-tree complex wavelet transform (DT-CWT) and nonlocal means (NLM) is proposed for RE of...

This paper discusses iris recognition, which is accepted as one of the best biometric methods for identifying an individual. A comparative analysis is done for eight algorithms, namely DCWT, FWT, SWT, CWT, DB, Complex dual tree, Haar wavelet and Wavelet packet for extracting the feature from iris image. Extracting the iris features of the image is still inconceivable as the existing algorithms ...

In modern technology, A wavelet-domain approach based on dual-tree complex wavelet transform (DTCWT) and nonlocal means (NLM) is proposed for RE of the satellite images.A satellite input image is processed by DTCWT (which is nearly shift invariant) to obtain high-frequency subbands. Lanczos interpolator is used between highfrequency subbands and the low-resolution (LR) input.The subbands other ...

We introduce a fast simple method for computing the real continuous wavelet transform (CWT). The approach achieves O N ( ) complexity per scale and the filter coefficients can be analytically obtained by a simple integration. Our method is to use P wavelets per octave and to approximate them with their oblique projection onto a space defined by a compact scaling function. The wavelet templates ...

The properties of Wavelet Transform can be successfully applied for analysis and processing of non stationary signals e.g., speech and image processing, data compression and communications. Due to the growing number of applications in various areas, it is necessary to explore the hardware implementation options of the Discrete Wavelet Transform (DWT). The Wavelet Series is just a sampled versio...

Tensor product real-valued wavelets have been employed in many applications such as image processing with impressive performance. Edge singularities are ubiquitous and play a fundamental role in image processing and many other two-dimensional problems. Tensor product real-valued wavelets are known to be only suboptimal since they can only capture edges well along the coordinate axis directions ...

Accurate estimation of seismocardiographic (SCG) signal features can help successful signal characterization and classification in health and disease. This may lead to new methods for diagnosing and monitoring heart function. Time-frequency distributions (TFD) were often used to estimate the spectrotemporal signal features. In this study, the performance of different TFDs (e.g., short-time Four...

Electroencephalography (EEG) is widely used in clinical settings to investigate neuropathology. Since EEG signals contain a wealth of information about brain functions, there are many approaches to analyzing EEG signals with spectral techniques. In this study, the short-time Fourier transform (STFT) and wavelet transform (WT) were applied to EEG signals obtained from a normal child and from a c...

In this paper a new robust digital image watermarking algorithm based on the Complex Wavelet Transform is proposed. This technique embeds different parts of a watermark into different blocks of an image under the complex wavelet domain. To increase security of the method, two chaotic maps are employed, one map is used to determine the blocks of the host image for watermark embedding, and anothe...