Enhancing image quality of ghost imaging by fuzzy c-means clustering method
نویسندگان
چکیده
منابع مشابه
OPTIMIZATION OF FUZZY CLUSTERING CRITERIA BY A HYBRID PSO AND FUZZY C-MEANS CLUSTERING ALGORITHM
This paper presents an efficient hybrid method, namely fuzzy particleswarm optimization (FPSO) and fuzzy c-means (FCM) algorithms, to solve the fuzzyclustering problem, especially for large sizes. When the problem becomes large, theFCM algorithm may result in uneven distribution of data, making it difficult to findan optimal solution in reasonable amount of time. The PSO algorithm does find ago...
متن کاملBilateral Weighted Fuzzy C-Means Clustering
Nowadays, the Fuzzy C-Means method has become one of the most popular clustering methods based on minimization of a criterion function. However, the performance of this clustering algorithm may be significantly degraded in the presence of noise. This paper presents a robust clustering algorithm called Bilateral Weighted Fuzzy CMeans (BWFCM). We used a new objective function that uses some k...
متن کاملFuzzy Image Segmentation using Suppressed Fuzzy C- Means Clustering (SFCM)
Clustering algorithms are highly dependent on the features used and the type of the objects in a particular image. By considering object similar surface variations (SSV) as well as the arbitrariness of the fuzzy c-means (FCM) algorithm for pixel location, a fuzzy image segmentation considering object surface similarity (FSOS) algorithm was developed, but it was unable to segment objects having ...
متن کاملFuzzy Image Segmentation using Suppressed Fuzzy C- Means Clustering
Clustering algorithms are highly dependent on the features used and the type of the objects in a particular image. By considering object similar surface variations (SSV) as well as the arbitrariness of the fuzzy c-means (FCM) algorithm for pixel location, a fuzzy image segmentation considering object surface similarity (FSOS) algorithm was developed, but it was unable to segment objects having ...
متن کاملoptimization of fuzzy clustering criteria by a hybrid pso and fuzzy c-means clustering algorithm
this paper presents an efficient hybrid method, namely fuzzy particleswarm optimization (fpso) and fuzzy c-means (fcm) algorithms, to solve the fuzzyclustering problem, especially for large sizes. when the problem becomes large, thefcm algorithm may result in uneven distribution of data, making it difficult to findan optimal solution in reasonable amount of time. the pso algorithm does find ago...
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: AIP Advances
سال: 2019
ISSN: 2158-3226
DOI: 10.1063/1.5079681