نتایج جستجو برای: local thresholding algorithm
تعداد نتایج: 1232929 فیلتر نتایج به سال:
This paper about to reduce the noise by Adaptive time-frequency Block Thresholding procedure using discrete wavelet transform to achieve better SNR of the audio signal. Discrete-wavelet transforms based algorithms are used for audio signal denoising. The resulting algorithm is robust to variations of signal structures such as short transients and long harmonics. Analysis is done on noisy speech...
Regularization of ill-posed linear inverse problems via l1 penalization has been proposed for cases where the solution is known to be (almost) sparse. One way to obtain the minimizer of such an l1 penalized functional is via an iterative soft-thresholding algorithm. We propose an alternative implementation to l1-constraints, using a gradient method, with projection on l1-balls. The correspondin...
Modularity is a fundamental concept in systems neuroscience, referring to the formation of local cliques or modules of densely intra-connected nodes that are sparsely inter-connected with nodes in other modules. Topological modularity of brain functional networks can quantify theoretically anticipated abnormality of brain network community structure - so-called dysmodularity - in developmental ...
Evaluation of vegetation cover by using the remote sensing data can provide enhanced results with less time and expense. In this paper, we propose a new automatic algorithm for detection of vegetation and shadow regions in high-resolution satellite/aerial images. It uses only color channels of the image and involves two modeling and evaluation phases. In the modeling phase, after extracting col...
On-board magnetic resonance (MR) image guidance during radiation therapy offers the potential for more accurate treatment delivery. To utilize the real-time image information, a crucial prerequisite is the ability to successfully segment and track regions of interest (ROI). The purpose of this work is to evaluate the performance of different segmentation algorithms using motion images (4 frames...
An iris identification algorithm is proposed based on adaptive thresholding. The iris images are processed fully in the spatial domain using the distinct features (patterns) of the iris. A simple adaptive thresholding method is used to segment these patterns from the rest of an iris image. This method could possibly be utilized for partial iris recognition since it relaxes the requirement of us...
Multilevel image thresholding is an important operation in many analyses which is used in many applications. Selecting correct thresholds is a critical issue. In this paper, Bacterial Foraging (BF) algorithm based on Tsallis objective function is presented for multilevel thresholding in image segmentation. Experiments to verify the efficiency of the proposed method and comparison to Genetic Alg...
In the electroencephalography (EEG) study, eye blinks are a commonly known type of ocular artifact that appears most frequently in any EEG measurement. The can be seen as spiking electrical potentials which their time-frequency properties varied across individuals. Their presence negatively impact various medical or scientific research helpful when applying to brain-computer interface applicati...
This paper presents a novel algorithm for license plate detection and license plate character segmentation problems by using the Gabor transform in detection and local vector quantization in segmentation. As of our knowledge this is the first application of Gabor filters to license plate segmentation problem. Even though much of the research efforts are devoted to the edge or global thresholdin...
Non-local means (NLM) is a popular image denoising scheme for reducing additive Gaussian noise. It uses a patch-based approach to find similar regions within a search neighborhood and estimate the denoised pixel based on the weighted average of all the pixels in the neighborhood. All the pixels are considered for averaging, irrespective of the value of their weights. This thesis proposes an imp...
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