BACKGROUND Compressed sensing(CS) has been well applied to speed up imaging by exploring image sparsity over predefined basis functions or learnt dictionary. Firstly, the sparse representation is generally obtained in a single transform domain by using wavelet-like methods, which cannot produce optimal sparsity considering sparsity, data adaptivity and computational complexity. Secondly, most s...

Abstract—Digital Watermarking is a procedure to prevent the unauthorized access and modification of personal data. It assures that the communication between two parties remains secure and their communication should be undetected. This paper investigates the consequence of the watermark strength of the grayscale image using a Discrete Wavelet Transformation (DWT) additive technique. In this meth...

This paper presents an approach for automatic classification of pulsed Terahertz (THz), or T-ray, signals highlighting their potential in biomedical, pharmaceutical and security applications. T-ray classification systems supply a wealth of information about test samples and make possible the discrimination of heterogeneous layers within an object. In this paper, a novel technique involving the ...

The description of 3D shapes using features that possess descriptive power and are invariant under similarity transformations is one of the most challenging issues in contentbased 3D model retrieval. Spherical harmonics-based descriptors have been proposed for obtaining rotation invariant representations. However, spherical harmonic analysis is based on a latitude-longitude parameterization of ...

Over the past two decades, wavelet theory has been used for the processing of biomedical signals for feature extraction, compression and de-noising applications. However the question as to which wavelet family is the most suitable for analysis of non-stationary bio-signals is still prevalent among researchers. This paper attempts to find the most useful wavelet function among the existing membe...

Discrete wavelet transforms are extensively preferred in biomedical signal processing for denoising, feature extraction, and compression. This paper presents a new denoising method based on the modeling of discrete wavelet coefficients of ECG in selected sub-bands with Kernel density estimation. The modeling provides a statistical distribution of information and noise. A Gaussian kernel with bo...

In this paper, we introduce a family of novel edge preserving image coding techniques based on the discrete wavelet transform (DWT). These techniques utilize the edge map (which not necessarily contains closed curves) of the processed image or its subbands in the way that no ltering over edges is performed. This results in a reduction of power in the higher frequency bands. The achievable savin...

This paper presents a unique thanks to cut back noise introduced or exacerbated by image sweetening strategies; especially algorithms supported the random spray sampling technique, however not solely. Multi scale decomposition based on dual-tree complex wavelet transform and edge preservation is presented for SRE of the satellite images. Resolution enhancement schemes (which are not based on wa...

Watermarking techniques are mainly used for protecting intellectual property right. This paper proposes a new hybrid nonblind video watermarking technique using wavelet contourlet transform and nonnegative matrix factorization Wavelet transform processed images are losing edge information. The Contourlet transform has good approximation properties for smooth 2D functions and finds a direct disc...

Convolutional Neural Networks (CNNs) have recently been proposed as a solution in texture and material classification computer vision. However, inside CNNs, the internal layers of pooling often cause loss information and, therefore, is detrimental to learning architecture. Moreover, when considering images with repetitive essential patterns, this affects performance subsequent stages, such feat...