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- The distributing characteristics of medical image wavelet coefficients have been studied in-depth and an efficient coding method, i.e.Adaptive Grouping Huffman based on wavelet transform is presented. 在对医学图像小波系数的分布特征进行深入分析的基础上,提出了一种高效的信源编码方法,即基于小波变换的自适应分组霍夫曼编码方法。
- By statistical prior model of image wavelet coefficient and iteration methods of channel capacity in the information theory,this paper derives a kind of computation method of multiply ... 通过建立小波域图像的统计先验模型和应用信息论中信道容量的迭代计算方法,给出了一类小波域图像乘性水印信道容量的数值计算方法和实验结果。
- The Application of Own Resemblance of Image Wavelet Coefficients in Image Denoising 图像小波系数的自相似性在图像去噪中的应用
- image wavelet coefficients 图像小波系数
- The obtained wavelet coefficients are used as substitution for ones of the noise image. 用所得的高频子带分别代替先前小波分解所得的高频子带。
- Then, the filter is applied to an original level with smoothed wavelet coefficients to get noise-free image. 然后,利用该滤波器对平滑小波系数进行滤波操作,去除噪声影响,得到滤波图像;
- Howto organize the wavelet coefficients effectively is pivotal to theperformance of image coding based on wavelet transform. 对于小波图像编码,如何有效地组织小波域系数是提高图像压缩效果的关键。
- The original image was decomposed into wavelet coefficients in this algorithm. Then quantize their wavelet coefficients. Finally, embed pseudo-random bit pattern. 这种算法将原始载体图像分解为小波系数,然后对小波系数进行量化,之后嵌入伪随机比特模板。
- In the first stage of Wiener filtering,the noisy image is decomposed by SWT.Then,the signal variances of wavelet coefficients are estimated in the elliptic windows. 在第一次局部维纳滤波中,用静态小波变换对含噪图像进行分解,然后利用椭圆方向窗来估计不同方向子带的各点信号的方差;
- At first, we transform the original image with wavelet function, then select the zones with rich veins to put in watermarking by analyzing the wavelet coefficients. 首先对原始二值图像做小波变换,通过分析其小波系数来寻找图像纹理及细节较丰富的区域,作为水印嵌入域。
- A multifunctional watermarking algorithm for color image is presented based on the rapport of wavelet coefficients and the choice swatch method; so robust watermark and fragile watermark exist in an image. 利用层间小波系数的关系;并结合新颖的样本选取方法提出了一种多功能彩色图像数字水印嵌入方法;使鲁棒数字水印和易碎数字水印共存于同一图像中.
- The wavelet coefficients are selected by Human Visual System (HVS) to ensure the transparence of watermarking. 同时基于人眼视觉系统,对嵌入系数进行筛选以保证水印的透明性。
- In the first step the wavelet coefficients were quantized by using a psycho-acoustic model. 在步骤1中,通过心理音响学模型对小波系数进行量化。
- The paper has researched the remote sensing image wavelet packet fusion based on the ARSIS concept. 摘要研究了基于ARSIS概念的遥感影像的小波包融合方法。
- A method is presented for decomposing the image with Haar wavelet and partitioning the image as text, picture and background based on the statistical distribution of the Haar wavelet coefficients in LH and HL high frequency bands. 用Haar小波分解图像;并基于LH和肌高频带Haar小波系数的统计分布规律将文本图像分割为文字、画面和背景.
- A novel fragile watermarking approach based on the triplet of wavelet coefficients is proposed. 提出一种新的基于三重小波系数集的易损水印算法 .
- According to wavelet coefficients energy distribution in different subbands,different thresholds are obtained in different subbands to improve reconstructed image quality significantly. 将该阈值方法和多小波变换相结合,根据多小波分解后的能量分布特性,在不同尺度的子带选择不同的最佳阈值,有效地提高了重构图像质量。
- Instantaneous abrupt change in wavelet coefficients can be used to detect the discontinuity of a signal. 小波系数的瞬态突变可以描述信号奇异性;
- Firstly form a subband pyramid and quantize all wavelet coefficients using uniform scalar quantizer. 该算法首先对小波变换系数进行一致标量量化;
- The stage 1 extracts extrema from wavelet coefficients of images after wavelet decomposition to locate face. 阶段一由分解后的小波系数取极值藉以框出初步的人脸。