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Y. Alp Aslandogan
Researcher at University of Texas at Arlington
Publications - 14
Citations - 786
Y. Alp Aslandogan is an academic researcher from University of Texas at Arlington. The author has contributed to research in topics: Filter (signal processing) & Salt-and-pepper noise. The author has an hindex of 6, co-authored 14 publications receiving 698 citations. Previous affiliations of Y. Alp Aslandogan include Prairie View A&M University.
Papers
More filters
Journal ArticleDOI
A Methodological Approach to the Classification of Dermoscopy Images
M. Emre Celebi,Hassan A. Kingravi,Bakhtiyar Uddin,Hitoshi Iyatomi,Y. Alp Aslandogan,William V. Stoecker,Randy Hays Moss +6 more
TL;DR: A methodological approach to the classification of pigmented skin lesions in dermoscopy images is presented and the issue of class imbalance is addressed using various sampling strategies and the classifier generalization error is estimated using Monte Carlo cross validation.
Journal ArticleDOI
Nonlinear Vector Filtering for Impulsive Noise Removal from Color Images
TL;DR: A comprehensive survey of 48 filters for impulsive noise removal from color images is presented and suggestions are provided on how to choose a filter given certain requirements.
Proceedings ArticleDOI
Detection of blue-white veil areas in dermoscopy images using machine learning techniques
TL;DR: In this preliminary study, a machine learning approach to the detection of blue-white veil areas in dermoscopy images is presented and involves pixel classification based on relative and absolute color features using a decision tree classifier.
Journal ArticleDOI
A Fast Switching Filter for Impulsive Noise Removal from Color Images
TL;DR: In this article, a fast switching filter for impulsive noise removal from color images is proposed, which exploits the HSL color space and is based on the peer group concept, which allows for the fast detection of noise in a neighborhood without resorting to pairwise distance computations between each pixel.
Journal ArticleDOI
Fast switching filter for impulsive noise removal from color images
TL;DR: In this paper, a fast switching filter for impulsive noise removal from color images is presented, which exploits the hue, saturation, and lightness color space and is based on the peer group concept, allowing for the fast detection of noise in a neighborhood without resorting to pairwise distance computations between each pixel.