نتایج جستجو برای: keywords principal component analysis pca transform
تعداد نتایج: 4916949 فیلتر نتایج به سال:
an ideal fusion method preserves the spectral information in fused image without spatial distortion. the pca is believed to be a well-known pan-sharpening approach and being widely used for its efficiency and high spatial resolution. however, it can distort the spectral characteristics of multispectral images. the current paper tries to present a new fusion method based on the same concept. in ...
In this paper, we have proposed a novel method for two-dimensional shape object recognition and retrieval. The proposed method is based on Ridgelet Principal Component Analysis (Ridgelet PCA). In our proposed approach we first use the ridgelet transform to extract line singularity features and point singularity features by applying the radon and wavelet transform respectively and then applying ...
این تحقیق با استفاده آنالیز چند متغیره بر روی عکس های ذخیره شده بوسیله یک دوربین دیجیتال راه حلی را برای مسئله همپوشانی پیک ها که یکی از مسائل مهم در کروماتوگرافی لایه نازک است ارائه میدهد. ما برای اولین بار اندازه گیری همزمان چند گونه بر روی کاغذ کروماتوگرافی لایه نازک را با استفاده از آنالیز چند متغیره عکس مورد مطالعه قرار دادیم. سیستم عکسبرداری متشکل از یک کابینت، یک دوربین دیجیتال و یک بر...
This paper proposes Transform Domain Fusion Rule (TDFR) via high pass modulation using Local Magnitude Ratio (LMR) in Fast Discrete Contour let Transform (FDCT) domain. Contour let transform method uses low resolution multispectral image and Cartosat-1 Panchromatic (PAN) of spatial resolution 2.5m is used as high resolution panchromatic image. This both images are up sampled in order to resize ...
This Paper proposes a new facial feature extraction approach, Wash-Hadamard Transform (WHT). This approach is based on correlation between local pixels of the face image. Its primary advantage is the simplicity of its computation. The paper compares the proposed approach, WHT, which was traditionally used in data compression with two other known approaches: the Principal Component Analysis (PCA...
Image fusion is a technique that integrate complimentary details from multiple input images such that the new image give more information and more suitable for the purpose of human visual perception. This paper presents a review on some of the image fusion techniques (simple average, simple minimum, simple maximum, PCA, DWT). Comparison of all the techniques concludes the better approach for it...
Image fusion is a technique that integrate complimentary details from multiple input images such that the new image give more information and more suitable for the purpose of human visual perception. This paper presents a review on some of the image fusion techniques (simple average, simple minimum, simple maximum, PCA, DWT). Comparison of all the techniques concludes the better approach for it...
The study of the electrical signals produced by neural activities of human brain is called Electroencephalography. In this paper, we propose an automatic and efficient EEG signal classification approach. The proposed approach is used to classify the EEG signal into two classes: epileptic seizure or not. In the proposed approach, we start with extracting the features by applying Discrete Wavelet...
Face recognition has advantages over other biometric methods. Principal Component Analysis (PCA) has been widely used for the face recognition algorithm. PCA has limitations such as poor discriminatory power and large computational load. Due to these limitations of the existing PCA based approach, we used a method of applying PCA on wavelet subband of the face image and two methods are proposed...
background: fetal electrocardiography is a developing field that provides valuable information on the fetal health during pregnancy. by early diagnosis and treatment of fetal heart problems, more survival chance is given to the infant. objective: here, we extract fetal ecg from maternal abdominal recordings and detect r-peaks in order to recognize fetal heart rate. on the next step, we find a b...
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