PCA and LDA in DCT domain

نویسندگان

  • Weilong Chen
  • Meng Joo Er
  • Shiqian Wu
چکیده

In this paper, we prove that the principal component analysis (PCA) and the linear discriminant analysis (LDA) can be directly implemented in the discrete cosine transform (DCT) domain and the results are exactly the same as the one obtained from the spatial domain. In some applications, compressed images are desirable to reduce the storage requirement. For images compressed using the DCT, e.g., in JPEG or MPEG standard, the PCA and LDA can be directly implemented in the DCT domain such that the inverse DCT transform can be skipped and the dimensionality of the original data can be initially reduced to cut down computational cost. 2005 Elsevier B.V. All rights reserved.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Multi-Focus Image Fusion in DCT Domain using Variance and Energy of Laplacian and Correlation Coefficient for Visual Sensor Networks

The purpose of multi-focus image fusion is gathering the essential information and the focused parts from the input multi-focus images into a single image. These multi-focus images are captured with different depths of focus of cameras. A lot of multi-focus image fusion techniques have been introduced using considering the focus measurement in the spatial domain. However, the multi-focus image ...

متن کامل

Dct-based Reduced Face for Face Recognition

In this paper, face recognition technique using Discrete Cosine Transform (DCT) is proposed. The local information of the face is extracted using block-based (DCT). The coefficients selected in each DCT block are fused to generate the feature image. This feature image is used for classification process. The face, recognition is then performed using Mahalanobis distance. The advantage of this te...

متن کامل

Face Recognition using Canonical Correlation Analysis

Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are well known techniques for face recognition. Both PCA and LDA by themselves have good recognition rates. We propose Canonical Correlation Analysis (CCA) for combining two feature extractors to improve the performance of the system, by obtaining the advantages of both. CCA finds the transformation for each extractor dat...

متن کامل

A Robust Approach for Image Compression Using PCA and DCT Algorithms

ISSN: 2347-8578 www.ijcstjournal.org Page 117 A Robust Approach for Image Compression Using PCA and DCT Algorithms Yashodha Devi Under the guidance of Er. Priyanka Mehta Assistant Professor (CSE) Universal Institute of Engineering and Technology, Lalru India ABSTRACT The basic goal of image data compression is to reduce the bit rate for transmission and storage while either maintaining the orig...

متن کامل

Resampling LDA/QR and PCA+LDA for Face Recognition

Principal Component Analysis (PCA) plus Linear Discriminant Analysis (LDA) (PCA+LDA) and LDA/QR are both two-stage methods that deal with the small sample size (SSS) problem in traditional LDA. When applied to face recognition under varying lighting conditions and different facial expressions, neither method may work robustly due to limited number of training samples for each class in the train...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Pattern Recognition Letters

دوره 26  شماره 

صفحات  -

تاریخ انتشار 2005