The framework of computing Higher Order Cyclostationary Statistics (HOCS) from an incoming signal has proven useful in a variety of applications over the past half century, from Automatic Modulation Recognition (AMR) to Time Difference of Arrival (TDOA) estimation. Much more recently, a theory known as Compressive Sensing (CS) has emerged that enables the efficient acquisition of high-bandwidth...

The advent of the modern digital technology has not only brought about the prevalent use of digital images in our daily activities but also the ease of creating image forgery such as digital photomontages using publicly accessible and userfriendly image processing tools such as Adobe Photoshop. Among all operations involved in image photomontage, image splicing can be considered the most fundam...

The performance of many comm. systems could be improved if the transmission channel was estimated blindly, i.e. without training sequences. As an example, we investigate in this paper whether, on GSM conditions, the blind channel estimation method EVI (EIGENVECTOR APPROACH TO BLIND IDENTIFICATION) can compete with the non-blind least squares scheme based on the cross-correlation. For Gaussian s...

Image processing and image analysis are the main aspects for obtaining information from digital image owing to the fact that this techniques give the desired details in most of the applications generally and Non-Destructive testing specifically. This paper presents a proposed method for the automatic detection of weld defects in radiographic images. Firstly, the radiographic images were enhance...

This paper presents a new algorithm of disparity map estimation. Originality of this method lies in the process of dense disparity map estimation using the dynamic programming constrained by interest points and using Higher Order Statistics (HOS) criteria for matching noisy images. Experiments with noisy real images have validated our method and have clearly shown the improvement over the exist...

In this paper we develop a higher order statistical theory of matching models against images The basic idea is not only to take into account how much of an object can be seen in the image but also what parts of it are jointly present We show that this additional information can improve the speci city i e reduce the probability of false positive matches of a recognition algorithm We demonstrate ...