This paper describes an efficient edge-preserved regularization algorithm for downward continuation of magnetic data in detection of unexploded ordnance (UXO). The magnetic anomalies arising from multi-source UXO can overlap at a height over the ground surface, while causative sources may not be readily separated due to low level of signal-to-noise ratio of the observed data. To effectively the...

External noise paradigms have been widely used to probe different levels of visual processing (Pelli & Farell, 1999). A basic assumption of this paradigm is that the processing strategy is noise-invariant, remaining the same in low and high external noise. We tested this assumption by examining crowding in a detection task where traditionally crowding has no effect. In the first experiment, we ...

wireless communication is the major form of connection nowadays. in most cases it exploits the benefits of the spread spectrum techniques to overcome channel introduced corruptions like doppler residual frequency, noise, interference and jamming. these techniques also enhance the security and quality of the link. using long spreading pseudo-noise codes provides further security for the link tho...

In this paper, a new algorithm for edge detection based on fuzzyconcept is suggested. The proposed approach defines dynamic membershipfunctions for different groups of pixels in a 3 by 3 neighborhood of the centralpixel. Then, fuzzy distance and -cut theory are applied to detect the edgemap by following a simple heuristic thresholding rule to produce a thin edgeimage. A large number of experime...

Stereoscopic corrugation detection in the presence of horizontal- and vertical- additive disparity noise was examined using a signal detection paradigm. Random-dot stereograms either represented a 3-D square-wave surface with various amounts of Gaussian-distributed additive disparity noise or had the same disparity values randomly redistributed. Stereoscopic detection of 2 arcmin peak amplitude...

This paper describes a method for reducing sudden noise using noise detection and classification methods, and noise power estimation. Sudden noise detection and classification have been dealt with in our previous study. In this paper, noise classification is improved to classify more kinds of noises based on k-means clustering, and GMM-based noise reduction is performed using the detection and ...

Image preprocessing and image segmentation are two important and broad research areas. Image denoising is one of the research fields in the research area of image preprocessing which is used to remove noise from the images. This paper proposed a method to identify the best filter and best edge detection algorithm for digital x-ray bone images. Comparisons of various filters such as Mean, Median...

Adaptive median filter has been an efficient algorithm for salt and pepper noise removal. But, if the noise percentage are very high, adaptive median filter may still remain noise regions in result image. So a Particle swarm optimization based novel and modified adaptive median filter (PSOMF) is proposed. The Proposed filter works in two stages: Noise detection stage and noise filtering stage. ...

Adding noise to inputs of some suboptimal detectors or estimators can improve their performance under certain conditions. In the literature, noise benefits have been studied for detection and estimation systems separately. In this study, noise benefits are investigated for joint detection and estimation systems. The analysis is performed under the Neyman–Pearson (NP) and Bayesian detection fram...

Camera-captured document images usually contain two main types of marginal noise: textual noise (coming from neighboring pages) and non-textual noise (resulting from the page surrounding and/or binarization process). These types of marginal noise degrade the performance of the preprocessing (dewarping) of camera-captured document images and subsequent document digitization/recognition processes...