In this paper, a new algorithm for content− based image indexing and retrieval is presented. The proposed method is based on a combination of multiresolution analysis and color correlation histogram of the image. According to the new algorithm, wavelet coefficients of the image are computed first using Daubechies wavelets. A quantization step is then applied before computing horizontal and vert...

Mel-frequency cepstral coefficients (MFCCs) are efficient audio descriptors providing spectral energy measurements over short time windows of length 23 ms. These measurements, however, lose non-stationary spectral information such as transients or time-varying structures. It is shown that this information can be recovered as spectral co-occurrence coefficients. Scattering operators compute thes...

This paper presents a wavelet-based linear minimum mean square-error estimation (LMMSE) scheme to exploit the strong wavelet interscale dependencies for image denoising. Using overcomplete wavelet expansion (OWE), we group the wavelet coefficients with the same spatial orientation at adjacent scales as a vector. The LMMSE algorithm is then applied to the vector variable. This scheme exploits th...

The focus of this work is on the problem of feature selection and classification for on-road vehicle detection. In particular, we propose using quantized Haar wavelet features and Support Vector Machines (SVMs) for rear-view vehicle detection. Wavelet features are particularly attractive for vehicle detection because they form a compact representation, encode edge information, capture informati...

Dual tree complex wavelet transform(DTCWT) is a form of discrete wavelet transform, which generates complex coefficients by using a dual tree of wavelet filters to obtain their real and imaginary parts. The purposes of de-noising are reducing noise level and improving signal to noise ratio (SNR) without distorting the signal or image. This paper proposes a method for removing white Gaussian noi...

We introduce a new form of nonlinear approximation called restricted approximation. It is a generalization of n-term wavelet approximation in which a weight function is used to control the terms in the wavelet expansion of the approximant. This form of approximation occurs in statistical estimation and in the characterization of interpolation spaces for certain pairs of L p and Besov spaces. We...

This paper suggests an upside-down tree-based orthogonal matching pursuit UDT-OMP compressive sampling signal reconstruction method in wavelet domain. An upside-down tree for the wavelet coefficients of signal is constructed, and an improved version of orthogonal matching pursuit is presented. The proposed algorithm reconstructs compressive sampling signal by exploiting the upside-down tree str...

A new wavelet-based L∞ -constrained embedded image coding technique is proposed in this paper. For any desired distortion bound, the embedded bit stream can be truncated at a corresponding bit-rate, for which the required upper bound on the individual elements of the reconstruction error signal is guaranteed. A lifting-based wavelet transform is employed and exact relations are established betw...

Smooth regions and edges are very self similar and can be coded efficiently by fractal coders. One problem of fractal image coding is to achieve a high quality or a lossless representation of an image. This can be overcome by a hybrid coding approach as proposed by the authors in [3]. An extension to 3-D fractal video coding is described in [4]. Due to the block based algorithm, however, blocki...