Color image classification via quaternion principal component analysis network
نویسندگان
چکیده
منابع مشابه
Color image classification via quaternion principal component analysis network
The Principal Component Analysis Network (PCANet), which is one of the recently proposed deep learning architectures, achieves the state-of-the-art classification accuracy in various databases. However, the performance of PCANet may be degraded when dealing with color images. In this paper, a Quaternion Principal Component Analysis Network (QPCANet), which is an extension of PCANet, is proposed...
متن کاملQuaternion principal component analysis of color images
In this paper, we present quaternion matrix algebra techniques that can be used to process the eigen analysis of a color image. Applications of Principal Component Analysis (PCA) in image processing are numerous, and the proposed tools aim to give material for color image processing, that take into account their particular nature. For this purpose, we use the quaternion model for color images a...
متن کاملKernel principal component analysis network for image classification
Wu Dan Wu Jiasong Zeng Rui Jiang Longyu Lotfi Senhadji Shu Huazhong (1 Key Laboratory of Computer Network and Information Integration of Ministry of Education, Southeast University, Nanjing 210096, China) (2 Institut National de la Santé et de la Recherche Médicale U 1099, Rennes 35000, France) (3 Laboratoire Traitement du Signal et de l’Image, Université de Rennes 1, Rennes 35000, France) (4Ce...
متن کاملColor Image Processing Using Principal Component Analysis
It is known since 1988 that utilizing linear dimension reduction gives appropriate lower dimensional representation of homogenous swatches of color images of the nature. Though, it is common to see serious research projects, even dated 2005, which are based on the fixed color space paradigm. In this thesis, first experimental evaluations are performed to compare the principal component analysis...
متن کاملQuantum image classification using principal component analysis
We present a novel quantum algorithm for the classification of images. The algorithm is constructed using principal component analysis and von Neuman quantum measurements. In order to apply the algorithm we present a new quantum representation of grayscale images.
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: Neurocomputing
سال: 2016
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2016.08.006