A Novel Adaptive Non-Local Means-Based Nonlinear Fitting for Visibility Improving
نویسندگان
چکیده
منابع مشابه
Adaptive K-Means Clustering For Improving Non- Local Means Filtering
Recording devices whether analog or digital, have traits which make them susceptible to noise. In selecting a noise reduction algorithm, one must weigh several factors. Image denoising is defined as a method to recover a true image from an observed noisy image and is applied in display systems to improve the quality of image. One of the popular denoising methods, NLM, produces the quality of im...
متن کاملNon-local Means using Adaptive Weight Thresholding
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 estimates the denoised pixel based on the weighted average of all pixels in the neighborhood. All weights are considered for averaging, irrespective of the value of the weights. This paper proposes an improved var...
متن کاملAdaptive Non-local Means Using Weight Thresholding
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...
متن کاملAn Energy Based Adaptive Pushover Analysis for Nonlinear Static Procedures
Nonlinear static procedure (NSP) is a common technique to predict seismic demands on various building structures by subjecting a monotonically increasing horizontal loading (pushover) to the structure. Therefore, the pushover analysis is an important part of each NSP. Accordingly, the current paper aims at investigating the efficiencyof various algorithms of lateral load patterns applied to the...
متن کاملA novel local search method for microaggregation
In this paper, we propose an effective microaggregation algorithm to produce a more useful protected data for publishing. Microaggregation is mapped to a clustering problem with known minimum and maximum group size constraints. In this scheme, the goal is to cluster n records into groups of at least k and at most 2k_1 records, such that the sum of the within-group squ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Symmetry
سال: 2018
ISSN: 2073-8994
DOI: 10.3390/sym10120741