In this paper, we develop a robust image zero-watermarking algorithm based on multiple circular statistical features. First of all, detect stable feature points from the host image, and construct region partitions identified points, which contain critical information image. Second, statistics differences are calculated, both local global Third, apply discrete cosine transform (DCT) singular val...

With the spread of aerial laser bathymetry (ALB), seafloor topographies are being measured more frequently. Nevertheless, data deficiencies occur owing to seawater conditions and other factors. Conventional interpolation methods generally need produce digital elevation models (DEMs) with sufficient accuracy. If topographic features considered as a basis, DEM should be reproducible based on comb...

Protection of digital multimedia content has become an increasingly important issue for content owners and service providers. As watermarking is identified as a major technology to achieve copyright protection, the relevant literature includes several distinct approaches for embedding data into a multimedia element. Because of its growing popularity, the Discrete Wavelet Transform (DWT) is comm...

In recent years, dictionaries combined with sparse learning techniques became extremely popular in computer vision. The image denoising approaches can be categorized as spatial domain, transform domain, and dictionary learning based according to the image representation. Using machine learning, sparse representations have become a trend and are used image and vision applications. The general id...

Applications that use sparse representation are many and include compression, regularization in inverse problems, feature extraction, and more. Recent activity in this field has concentrated mainly on the study of pursuit algorithms that decompose signals with respect to a given dictionary. The K-SVD algorithm is an iterative method that alternates between sparse coding of the examples based on...

Two common problems are often encountered in analysis dictionary learning (ADL) algorithms. The first one is that the original clean signals for learning the dictionary are assumed to be known, which otherwise need to be estimated from noisy measurements. This, however, renders a computationally slow optimization process and potentially unreliable estimation (if the noise level is high), as rep...

a r t i c l e i n f o a b s t r a c t Taking into account two types of tremor, namely essential tremor (ET) and Parkinson's disease (PD), which are often misdiagnosed in clinical practice, a novel approach using singular value decomposition (SVD) to extract the features of intrinsic mode functions (IMFs) and support vector machine (SVM) is proposed to distinguish between them. The hand accelera...

We describe the Wavelet-Vaguelette Decomposition (WVD) of a linear inverse problem. It is a substitute for the singular value decomposition (SVD) of an inverse problem, and it exists for a class of special inverse problems of homogeneous type { such as numerical di erentiation, inversion of Abel-type transforms, certain convolution transforms, and the Radon Transform. We propose to solve ill-po...

With the rapid development of the multimedia,the secure of the multimedia is get more concerned. as far as we know , Digital watermarking is an effective way to protect copyright. The watermark must be generally hidden does not affect the quality of the original image. In this paper,a novel way based on discrete cosine transform(DCT) and singular value decomposition(SVD) .In the proposed way,we...