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It is difficult to get high compression ratio and good reconstructed image by conventional methods; we give a new method of compression on medical image. It is to decompose and reconstruct the medical image by wavelet packet. Before the construction the image, use neural network in place of other coding method to code the coefficients in the wavelet packet domain. By using the Kohonen's neural network...
The objective of this paper is to implement the concept of wavelet based image compression to gray scale images using different techniques. The techniques involved in the comparison process are EZW and WDR. These techniques are more efficient and provide a better quality in the image. In compression, wavelets have shown a good adaptability to a wide range of data, while being of reasonable complexity...
In this paper, a new rate adaptive control algorithm is proposed based on study of JPEG2000 rate control algorithm, in order to reduce the amount of bits sent to the arithmetic coder, without any significant changes into the standard architecture and without loosing performance. After wavelet transform, the coefficient is modeled as Gaussian distribution, but remove the offspring of the lowest frequency...
Recently, Blind Source Separate (BSS) technique has been extended to digital watermarking field. Slowly Feature Analysis (SFA)-a kind of BSS technique-is a new unsupervised learning algorithm to learn nonlinear functions that extract slowly varying signals out of the input data. It expediently can be used to extract image feature and separate the mixed signals. Making use of the advantages of SFA,...
Wavelet analysis is internationally recognized up to the minute tools for time-frequency. It gets an unprecedented development based on Fourier analysis and plays an important role in the signal processing especially in image compression. By analyzing the relations of the coefficients between each son block and the whole image, we can find the index position of the sub-band of each son block in the...
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