This paper investigated approaches to supporting effective and efficient retrieval of image based on principle component analysis. First, it extracted the image content, texture and color. Gabor wavelet transforms wer...This paper investigated approaches to supporting effective and efficient retrieval of image based on principle component analysis. First, it extracted the image content, texture and color. Gabor wavelet transforms were used to extract texture feature of the image and the average color was used to extract the color features. The principle component of the feature vector of image can be constructed. Content based image retrieval was performed by comparing the feature vector of the query image with the projection feature vector of the image database on the principle component space of the query image. By this technique, it can reduce the dimensionality of feature vector, which in turn reduce the searching time.展开更多
In the step processing a digitalized signal,noises are generated by internal or external causes of the system.In order to eliminate these noises,various methods are researched.Among these noise elimination methods,Fou...In the step processing a digitalized signal,noises are generated by internal or external causes of the system.In order to eliminate these noises,various methods are researched.Among these noise elimination methods,Fourier fast transform(FFT)and short-time Fourier transform(STFT)are widely used.Because they are expressed as a fixed time-frequency domain,they have the disadvantage that the time information about the signal is unknown.In order to overcome these limitations,by using the wavelet transform that provides a variety of time-frequency resolution,multi-resolution analysis can be analysed and a varying noise depending on the time characteristics can be removed more efficiently.Therefore,in this paper,a denoising method of underwater vehicle using discrete wavelet transform(DWT)is proposed.展开更多
文摘This paper investigated approaches to supporting effective and efficient retrieval of image based on principle component analysis. First, it extracted the image content, texture and color. Gabor wavelet transforms were used to extract texture feature of the image and the average color was used to extract the color features. The principle component of the feature vector of image can be constructed. Content based image retrieval was performed by comparing the feature vector of the query image with the projection feature vector of the image database on the principle component space of the query image. By this technique, it can reduce the dimensionality of feature vector, which in turn reduce the searching time.
文摘In the step processing a digitalized signal,noises are generated by internal or external causes of the system.In order to eliminate these noises,various methods are researched.Among these noise elimination methods,Fourier fast transform(FFT)and short-time Fourier transform(STFT)are widely used.Because they are expressed as a fixed time-frequency domain,they have the disadvantage that the time information about the signal is unknown.In order to overcome these limitations,by using the wavelet transform that provides a variety of time-frequency resolution,multi-resolution analysis can be analysed and a varying noise depending on the time characteristics can be removed more efficiently.Therefore,in this paper,a denoising method of underwater vehicle using discrete wavelet transform(DWT)is proposed.
