Digitized images have replaced analog images as photographs or x-rays in many different fields. In their raw form, digital images require a tremendous memory capacity for storage and large amount of bandwidth for transmission. In the last two decades, many researchers have been devoted to develop new techniques for image compression. More recently, wavelets have become a cutting edge technology...

Orthonormal M-band wavelet bases have been constructed and applied by several authors. This paper makes three main contributions. First, it generalizes the minimal length Kregular 2-band wavelets of Daubechies to the M-band case by deriving explicit formulas for K-regular M-band scaling filters. Several equivalent characterizations of K-regularity are given and their significance explained. Sec...

Abstract. – Recently, we have developed a method based on discrete wavelets to characterize the correlation and scaling properties of non-stationary time series. This approach is local in nature and it makes use of wavelets from the Daubechies family for detrending purpose. The natural built-in variable windows in wavelet transform makes this procedure well suited for the non-stationary data. W...

This paper introduces anovel class of length-4N orthonormal scalar wavelets, and presents the theory, implementational issues, and their applications to image compression. We first give the necessary and sufficient conditions for the existence of this class. The parameterized representation of filters with different lengths are then given. Next, we derive new and efficient decomposition and rec...

Recent studies suggest that multicarrier systems using wavelets outperform conventional OFDM systems using the FFT, in that they have well-contained side lobes, improved spectral efficiency and BER performance, and they do not require a cyclic prefix. Here we study the wavelet packet and discrete wavelet transforms, comparing the BER performance of wavelet transform-based multicarrier systems a...

We describe bases of smooth wavelets where the coe cients are obtained by integration against ( nite combinations of) boxcar kernels rather than against traditional smooth wavelets. Bases of this type were rst developed in work of Tchamitchian and of Cohen, Daubechies, and Feauveau. Our approach emphasizes the idea of average-interpolation { synthesizing a smooth function on the line having pre...

In this paper, we describe a method to represent and classify unvoiced sounds using the concept of super wavelets. Super wavelet is a linear combination of wavelets that itself can be treated as a wavelet. Since unvoiced sounds are high frequency and noise like, we use Daubechies' wavelet of order three to generate the super wavelet. The parameters of the wavelet for representation and classiic...

Cervical cancer is one of most common cancers among women in the world caused by human papilloma virus infection. It develops in the tissue of cervix which connects upper body of the uterus to the vagina. The types of cancer are squamous cell carcinoma, adeno carcinoma and adeno squamous carcinoma based on location of cervix where cancer develops. In this paper, an automatic detection of squamo...

Wavelets are powerful mechanisms for analyzing and processing digital signals. The wavelet transform translates the time-amplitude representation of a signal to a time-frequency representation that is encapsulated as a set of wavelet coefficients. These wavelet coefficients can be manipulated in a frequency-dependent manner to achieve various digital signal processing effects. The inverse wavel...

AbstractPerformance of Orthogonal Frequency Division Multiplexing (OFDM) systems using Fast Fourier Transforms (FFT) and Discrete Wavelet Transform (DWT) are analyzed in this paper. The performance of DWT-OFDM is assessed by various parameters such as BER, eye diagram and constellation diagram. BER is the ratio of the no. of bits with error to the total no. of bits transmitted through the chann...