Keywords: Noise mapping Grid refinement Uncertainty Interpolation GIS Noise maps are usually represented as contour or isolines maps describing the sound levels in a region. Using this kind of representation the user can easily find the noise level assigned to every location in the map. But the acoustic calculations behind the map are not performed for every single location on it; they are only...

Various common error sources affect the quality of a map, e.g., salt and pepper noise and other forms of noise that are more or less uniformly distributed over the map. But there also exist errors that only occur very rarely in the mapping process but that have severe effects on the final result. They influence not only the local accuracy but also the whole spatial layout of the map. Examples o...

We present preliminary results connrming the importance of radiometric correction in multicamera applications. Although, in this paper we compensate for systematic noise only, we review all noise sources in the video sensor (systematic and random). We use a simple model for radiometric correction of digital images. The correction procedure is tested on the disparity map computation in stereo ma...

Detecting determinism in univariate and multivariate time series is difficult if the underlying process is nonlinear, and the noise level is high. In a previous paper, the authors proposed a method based on observable ordinal patterns. This method exploits the robustness of admissible ordinal patterns against observational noise, and the super-exponential growth of forbidden ordinal patterns wi...

Traffic noise mapping of cities requires large computer calculation times. This originates from the large number of point-to-point sound propagation calculations that must be performed. In this article it is demonstrated that noise mapping calculation times can be reduced considerably by the use of parallel computation on the Graphics Processing Unit (GPU) of a personal computer. Comparisons ar...

We present a theoretical analysis of Maximum a Posteriori (MAP) sequence estimation for binary symmetric hidden Markov processes. We reduce the MAP estimation to the energy minimization of an appropriately defined Ising spin model, and focus on the performance of MAP as characterized by its accuracy and the number of solutions corresponding to a typical observed sequence. It is shown that for a...

For producing a single high dynamic range image (HDRI), multiple low dynamic range images (LDRIs) are captured with different exposures and combined. In high dynamic range (HDR) imaging, local motion of objects and noise in a set of LDRIs can influence a final HDRI: local motion of objects causes the ghost artifact and LDRIs, especially captured with under-exposure, make the final HDRI noisy. I...

Magnetic resonance imaging (MRI) is an outstanding medical imaging modality but the quality often suffers from noise pollution during image acquisition and transmission. The purpose of this study is to enhance image quality using feature-preserving denoising method. In current literature, most existing MRI denoising methods did not simultaneously take the global image prior and local image feat...

Introduction: The position estimation in gamma detection system will have constant misplacements which can be corrected in the calibration procedure. In the pixelated crystal uniformly irradiation of detector will produce irregular shape due to position estimation errors. This image is called flood field image and is used to calibrate the position estimation. In this work we pr...

Machines and equipment or work processes that make noise. Evaluation of noise intensity is carried out by making a map describes the distribution pattern from 278 measurement points then processed with surfer software, which becomes basic information to protect workers risk hearing loss. After measuring analyzing data, level ranged lowest 41.0 dBA, highest 101.9 dBA. From map, it can be seen ma...