共查询到20条相似文献,搜索用时 31 毫秒
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无需重构的多分辨率图像融合算法(英文) 总被引:1,自引:1,他引:0
提出了一种基于平稳小波变换的多聚焦图像融合算法。首先对待融合图像进行平稳小波分解,得到图像尺寸相同的低频分量和高频分量,然后对低频分量使用拉普拉斯能量进行清晰度判断,对于高频分量,则先计算其各个尺度,不同方向高频分量的绝对值和,进而通过能量特征判断其清晰度,最后通过比较低频分量和高频分量清晰度决策图的相同和相异性得到融合图像。计算机仿真实验表明,本文算法得到的融合图像清晰度较好,熵、平均梯度、空间频率和互信息等客观评价指标值高于平均法和传统基于小波变换的图像融合算法,互信息量比文献[3]中的方法提高了约2.4倍,是一种有效的多聚焦图像融合算法。 相似文献
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《成像科学杂志》2013,61(3):181-187
AbstractThe LL sub-band from the discrete wavelet transform in JPEG2000 is similar to a smaller image of the original in spatial domain. The proposed authentication and tamperproofing scheme is to extract and hide the entire LL sub-band into the first-level sub-bands, 1LH and 1HL. The hidden data are used later with a unique digital signature and a public key to prove the authenticity of the image. Tampered areas could be accurately detected and recovered to a quality that is visually acceptable. This scheme can be used to authenticate sensitive images, such as medical images, to prove rightful ownership and to recover images before originals are available. 相似文献
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提出了一种结合了归一化技术和全息技术的数字水印技术。首先,利用归一化技术对图像作归一化运算,同时利用全息技术将水印二值图处理为全息图;其次,取归一化后图像分块离散余弦变换的中频系数,对中频系数所组成的矩阵作离散小波变换;最后将全息图嵌入到离散小波变换的低频分量中。由于图像归一化技术具有抗仿射变换的性能,同时全息技术具有很强的抗裁切的性能,所以此数字水印技术具有很强的抗仿射变换的性能,可以广泛的用于数字作品的版权保护。 相似文献
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Image fusion makes the fused image more reliable and intelligible, and more suitable for human vision and computer detection, classification, recognition and understanding. This paper proposes a pixel-level image fusion method for merging two source images of the same scene using wavelet transform and gray-level features (GLF). First, a three-level discrete two-dimensional wavelet transform is used to decompose the two source images into low-frequency image components and horizontal, vertical, and diagonal high-frequency components. Then, the spatial frequency correlation coefficient is used to determine the pixel fusion rule to apply to each of the low-frequency images, and the correlation coefficient of the GLF is used to determine the pixel fusion rule to apply to each of the high-frequency images. Finally, the fused image is reconstructed using inverse wavelet transform. The results of the experiments conducted indicate that the proposed method is more effective than relevant conventional methods. 相似文献
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Zhi Li Zhenhong Jia Jie Yang Nikola Kasabov 《International journal of imaging systems and technology》2020,30(4):939-949
Aiming at the process of medical diagnosis, many problems such as unclear images and low contrast are often caused by noise and interference in the process of medical image acquisition and transmission. This article proposes a new image enhancement method that combines the wavelet domain with the spatial domain. First, we input two identical images (Both of the identical images are original images.) in which the first image is enhanced by histogram equalization. Then, the two images are divided into four sub-images by a two-dimensional wavelet transform. The average of the low-frequency coefficients of the low-frequency sub-images of the two images is taken as the low-frequency coefficients of the final reconstruction. Second, aiming at the problem that the contrast may be too low, the fourth high-frequency sub-image is blurred (sharpened) twice. The fourth high-frequency sub-image after blurring is denoised by median filtering. Finally, the four sub-images are fused to obtain the enhanced image. The experimental results show that the peak signal-to-noise ratio, structural similarity, and processing time of the proposed algorithm are better than those of other contrast algorithms, especially the processing time. These objective indicators show that the proposed algorithm can not only effectively suppress noise but also significantly enhance the contrast. Subjectively, compared with other algorithms, the proposed algorithm achieves a better visual effect and greatly reduces the processing time. 相似文献
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Zhancheng Zhang Jie Cui Xiaoqing Luo Qingjun You 《International journal of imaging systems and technology》2020,30(4):1066-1079
Fusing multimodal medical images into an integrated image, providing more details and rich information thereby facilitating medical diagnosis and therapy. Most of the existing multiscale-based fusion methods ignore the correlations between the decomposition coefficients and lead to incomplete fusion results. A novel contextual hidden Markov model (CHMM) is proposed to construct the statistical model of contourlet coefficients. First, the pair brain images are decomposed into multiscale, multidirectional, and anisotropic subbands with a contourlet transform. Then the low-frequency components are fused with the choose-max rule. For the high-frequency coefficients, the CHMM is learned with the EM algorithm, and incorporate with a novel fuzzy entropy-based context, building the fuzzy relationships among these coefficients. Finally, the fused brain image is obtained by using the inverse contourlet transform. Fusion experiments on several multimodal brain images show the superiority of the proposed method in terms of both visual quality and some widely used objective measures. 相似文献
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提出一种阈值改进整数小波与基于字典编码的LZW(Lempel-Ziv-Welch)算法相结合的数据压缩方法,该方法旨在减少水声数据传输量的同时尽可能地达到高保真。数据压缩过程中,先对水声数据进行整数小波变换,再对变换后的高频系数采用改进的小波阈值算法和阈值函数进行处理,提高了数据压缩倍数和信噪比,降低了误差。最后通过LZW将处理后的系数进行编码输出,进一步提升压缩效果。文中给出了相应的数据压缩算法流程。实际舰船辐射噪声数据的压缩处理结果表明,该方法能有效提高信号信噪比、减少信号失真并能获得更大的压缩倍数。 相似文献
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In the current dire situation of the corona virus COVID-19, remote
consultations were proposed to avoid cross-infection and regional differences in medical
resources. However, the safety of digital medical imaging in remote consultations has
also attracted more and more attention from the medical industry. To ensure the integrity
and security of medical images, this paper proposes a robust watermarking algorithm to
authenticate and recover from the distorted medical images based on regions of interest
(ROI) and integer wavelet transform (IWT). First, the medical image is divided into two
different parts, regions of interest and non-interest regions. Then the integrity of ROI is
verified using the hash algorithm, and the recovery data of the ROI region is calculated at
the same time. Also, binary images with the basic information of patients are processed
by logistic chaotic map encryption, and then the synthetic watermark is embedded in the
medical carrier image using IWT transform. The performance of the proposed algorithm
is tested by the simulation experiments based on the MATLAB program in CT images of
the lungs. Experimental results show that the algorithm can precisely locate the distorted
areas of an image and recover the original ROI on the basis of verifying image reliability.
The maximum peak signal to noise ratio (PSNR) value of 51.24 has been achieved, which
proves that the watermark is invisible and has strong robustness against noise,
compression, and filtering attacks. 相似文献
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针对多聚焦图像融合存在的问题,提出一种基于非下采样Contourlet变换(NSCT)的多聚焦图像融合新方法。首先,采用NSCT对多聚焦图像进行分解;然后,对低频系数采用基于改进拉普拉斯能量和(SML)的视觉特征对比度进行融合,对高频系数采用基于二维Log-Gabor能量进行融合;最后,对得到的融合系数进行重构得到融合图像。实验结果表明,无论是运用视觉的主观评价,还是基于互信息、边缘信息保留值等客观评价标准,该文所提方法都优于传统的离散小波变换、平移不变离散小波变换、NSCT等融合方法。 相似文献
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基于Curvelet变换的多聚焦图像融合方法 总被引:10,自引:0,他引:10
由于可见光成像系统的聚焦范围有限,很难获得同一场景内所有物体都清晰的图像.多聚焦图像融合技术可有效地解决这一问题.在分析了传统多聚焦图像融合方法和Curvelet变换的原理后,提出了一种基于Curvelet变换的多聚焦图像融合方法,先对不同聚焦图像分别进行Curvelet变换,采用低频系数取平均,高频系数取大的融合规则,再进行Curvelet反变换得到融合结果.仿真试验表明,基于Curvelet变换的融合方法可有效综合多聚焦图像,相比小波变换法,获得了更好的融合效果. 相似文献
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目的为了识别图像来源于相机还是其他电子设备,提出一种基于小波高阶统计量的图像来源取证方法。方法利用生成途径对图像性质的影响和数理统计方法,通过对比不同来源的数字图像的生成途径对它们各自性质的影响,从图像的多尺度分析角度,研究不同来源的图像在变换域所呈现的独有特性,提取数字图像小波域的高阶统计特征,以此判断图像的来源。结果实验结果表明,针对计算机软件、数码相机和扫描仪这3类图像的平均测试正确率达到了97.9%。结论该方法在确定图像来源上有较高的效率和准确率。 相似文献
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Image fusion is the concept to integrate multiple same scene images while drawing out maximum radiometric information from them by avoiding noise and fictional data. The main objective is to improve the radiometric quality of fused image compared to individual images of the same scene. Existing methods are found to be efficient, but if the similar radiometric information is fused into every image, it produces redundant high frequency of pixels. Therefore, to overcome this issue, in this paper a fuzzy and stationary discrete wavelet transform (FSDWT)-based image fusion technique is proposed. It decomposes Landsat image into stationary values, and then it preserves the radiometric data by using fuzzy if-then rules. In the last phase, FSDWT injects high-frequency blocks from input images and returns a single Landsat image with maximum radiometric data. Quantitative analysis has clearly demonstrated that FSDWT has better structural detail, spatial resolution and spectral information than existing methods. 相似文献
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基于边缘信息的偏振图像融合算法及评价 总被引:1,自引:1,他引:0
偏振遥感图像通常都采用强度、偏振度、偏振角来表征目标偏振特性.本文提出的基于边缘信息的偏振图像融合算法是将三幅偏振图像利用离散小波变换把图像分解成不同尺度的低频和高频部分,采用小波区域窗口和子区域窗口统计把小波系数分类成边缘和非边缘系数,通过这些方法进行有效的边缘细节信息提取.在融合处理中,低频图像的小波系数平均值作为融合后的低频系数,高频细节系数根据不同区域特征选择方法以及对应输入图像小波系数的窗口区域方差来确定融合后高频小波系数.仿真实验结果表明,这样使得融合后的图像细节更真实更丰富,图像的偏振特性体现更为充分,同时减少对源图像的预处理要求,使图像在整体上有较好的视觉效果.从而证明这种方法能够在保留图像微小细节方面获得满意的结果,且算法有效性优于其他的图像融合方法. 相似文献
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本文基于小波变换研究了分形图像压缩系统.根据小波系数的能量分布特性,给出了新的小波树定义与分类方法,并在小波域内建立了具有双伸缩因子的压缩映射.在将新的压缩映射应用于图像编码过程时,结合小波嵌入式零树编码思想给出了新的小波分形图像压缩方法.数值实验给出了本文方法与已有方法的比较. 相似文献
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基于小波变换和形态学的织物疵点边缘检测 总被引:1,自引:0,他引:1
为了精确确定织物疵点边缘,提出了一种基于小波变换和形态学的织物疵点边缘检测方法.在利用形态学实现疵点检测后,对其进行小波分解,用小波模极大值法和基于数学形态学的算法分别提取高低频子图像的疵点边缘,采用合理的融合规则将两个边缘图像进行融合.实验结果表明,该算法能有效地抑制噪声,且边缘清晰、准确,效果优于经典的边缘检测算法,具有可行性和有效性. 相似文献
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本文提出了一种基于形态学和小波域杂波抑制的微弱目标检测方法,该方法将图像序列进行形态擘tophat滤波,然后小波变换,再分别对各小波子带作平滑滤波,按各子带对滤波前后小波系数作差分运算,最后经过小波逆变换得到具有微弱目标的残差图像序列.用残差图像tophat结果估计目标潜在区域,在目标潜在域的约束下,对残差图像序列进行时空域数据融合,实现微弱运动目标的检测.仿真实验表明,该方法杂波抑制后残差图像具有很好的白高斯特性,且目标邻域信杂比(scNR)的平均增益比图像空域平滑滤波和图像频域低通滤波等典型运算的SCNR平均增益有明显改善,目标检测算法在5帧图像集成时能稳定检测出微弱运动目标轨迹. 相似文献