Multiple color-image fusion and watermarking based on optical interference and wavelet transform

A novel multiple color-image fusion and watermarking using optical interference and wavelet transform is proposed. In this method, each secret color image is encoded into three phase-only masks (POMs). One POM is constructed as user identity key and the other two POMs are generated as user identity key modulated by corresponding secret color image in gyrator transform domain without using any time-consuming iterative computations or post-processing of the POMs to remove inherent silhouette problem. The R, G, and B channels of different user identity keys POM are then individually multiplied to get three multiplex POMs, which are exploited as encrypted images. Similarly the R, G, and B channels of other two POMs are independently multiplied to obtain two sets of three multiplex POMs. The encrypted images are fused with gray-level cover image to produce the final encrypted image as watermarked image. The secret color images are shielded by encrypted images (which have no information about secret images) as well as cover image (which reveals no information about encrypted images). These two remarkable features of the proposed system drastically reduce the probability of the encrypted images to be searched and attacked. Each individual user has an identity key and two phase-only keys as three decryption keys besides transformation angles regarded as additional keys. Theoretical analysis and numerical simulation results validate the feasibility of the proposed method.     

Image encryption with fractional wavelet packet method

We introduce a new method called fractional wavelet packet transform to encrypt images in this paper, in which fractional orders and wavelet packet filter are its two series of keys. Fractional orders are additional keys in this method compared to wavelet packet encryptions. Selected image encryption is also proposed in this paper, and it is quite more flexible and effective than wavelet, fractional wavelet or wavelet packet encryptions. The possible optical implementation and digital computation are proposed. Computer simulations prove its feasibility.     

Optical image encryption with redefined fractional Hartley transform

A new method for optical image encryption is introduced on the basis of two-dimensional (2-D) generalization of 1-D fractional Hartley transform that has been redefined recently in search of its inverse transform. We encrypt the image by two fractional orders and random phase codes. It has an advantage over Hartley transform, for its fractional orders can also be used as additional keys, and that, of course, strengthens image security. Only when all of these keys are correct, can the image be well decrypted. The optical realization is then proposed and computer simulations are also performed to confirm the possibility of the proposed method.     

Extended fractional wavelet joint transform correlator

An extended fractional wavelet joint transform correlator is implemented for real-time target recognition applications. The real-time input scene captured using a charge-coupled device camera along with the reference image is fractional Fourier transformed. The obtained joint power spectrum is multiplied by an appropriately scaled wavelet filter and the resultant function is differentiated. The application of wavelet filter enhances the correlation outputs and differential processing of wavelet-filtered joint power spectrum improves the detection efficiency by reducing the zero-order spectra. Targets with Gaussian and speckle noise have also been used to check the correlation output. The performance metrics: correlation peak intensity, peak-to-correlation energy, peak-to-sidelobe ratio and signal to clutter ratio have been calculated. The experimental results are presented in support of the proposed idea.     

基于小波变换和数据融合技术的弱小目标检测

 鉴于弱小目标检测所固有的难点及常用的单一分辨率下的检测方法还不能准确稳定地检测出目标，提出了一种弱小目标检测新方法。考虑到实际应用中的复杂背景和大量干扰噪声，运用数据融合技术，先对图像进行小波多分辨率分解，然后将不同分辨率下的子图进行最优加权平均融合来检测弱小目标。用实地拍摄的空中弱小目标红外和可见光图像分别进行实验验证，实验图像取256×256像素点阵大小，其中目标占10×10像素左右。结果表明该方法能够准确稳定地检测弱小目标，为后续的跟踪作了很好的铺垫。     

Asymmetric multiple-image hiding using phase retrieval technique based on amplitude- and phase-truncation in fractional Fourier domain

We propose a multiple-image hiding scheme based on the amplitude- and phase-truncation approach, and phase retrieval iterative algorithm in the fractional Fourier domain. The proposed scheme offers multiple levels of security with asymmetric keys. Multiple input images multiplied with random phase masks are independently fractional Fourier transformed with different orders. The individual keys and common keys are generated by using phase and amplitude truncation of fractional spectrum. After using two fractional Fourier transform, the resultant encrypted image is hided in a host image with phase retrieval iterative algorithm. Using the correct universal keys, individual keys, and fractional orders, one can recover the original image successfully. Computer simulation results with four gray-scale images support the proposed method. To measure the validity of the scheme, we calculated the mean square error between the original and the decrypted images. In this scheme, the encryption process and generation of decryption keys are complicated and should be realized using computer. For decryption, an optoelectronic setup has been suggested.     

Performance analysis of multi-spectral and panchromatic image fusion techniques based on two wavelet discrete approaches

During the past few years, many fusion algorithms have been proposed to combine a high-resolution panchromatic image with a low-resolution multi-spectral image to generate a high-resolution multi-spectral image. Among them, the wavelet-based algorithm has gained its popularity due to its ability of multi-resolution decomposition. More specifically, the wavelet transform is first applied to images. The wavelet coefficients are then combined based on a certain rule to produce the fused image. In this paper, we evaluated the performances of both the wavelet transform discrete approaches and the coefficient combination methods when they are applied to fuse multi-spectral and panchromatic images. For the discrete approaches of the wavelet transform, Mallat and “à trous” algorithms are chosen. For the coefficient combination, the additive wavelet method, the additive wavelet intensity method and the additive wavelet principal component method are selected. To evaluate the spectral quality of the fused images, correlation coefficient and Q_avg index are used as a local and global measure, respectively. Meanwhile, average gradient and standard deviation are used to evaluate the spatial quality. Our experiments show that keeping the combination method the same, the “à trous” algorithm works better than the Mallat algorithm for the fusion purpose. In addition, if keeping the wavelet discrete algorithm the same, the combination methods mentioned above are found to have different advantages between the spatial resolution improvement and the spectral quality preservation.     

Image fusion scheme using a novel dual-channel PCNN in lifting stationary wavelet domain

This paper presents a new multi-source image fusion scheme based on lifting stationary wavelet transform (LSWT) and a novel dual-channel pulse-coupled neural network (PCNN). By using LSWT, we can calculate a flexible multiscale and shift-invariant representation of registered images. After decomposing the original images using LSWT, a new dual-channel pulse coupled neural network, which can overcome some shortcomings of original PCNN for image fusion and putout the fusion image directly, is proposed and used for the fusion of sub-band coefficients of LSWT. In this fusion scheme, a new sum-modified-laplacian(NSML) of the low frequency sub-band image, which represent the edge-feature of the low frequency sub-band image in SLWT domain, is presented and input to motivate the dual-channel PCNN. For the fusion of high frequency sub-band coefficients, a novel local neighborhood modified-laplacian (LNML) measurement is developed and used as external stimulus to motivate the dual-channel PCNN. This fusion scheme is verified on several sets of multi-source images, and the experiments show that the algorithms proposed in the paper can significantly improve image fusion performance, compared with the fusion algorithms such as traditional wavelet, LSWT, and LSWT-PCNN in terms of objective criteria and visual appearance.     

Optical image encryption using fractional Fourier transform and chaos

We propose a new method for image encryption using fractional Fourier transform and chaos theory. Random phase masks are generated using iterative chaos functions. The input image is combined with the first random phase mask at the object plane and is then transformed using the fractional Fourier transform. After the first fractional Fourier transform, the second random phase mask, again generated by using the chaos functions, is used at the fractional plane. The second fractional Fourier transform operation is then carried out to obtain the encrypted image. Three types of chaos functions have been used: the logistic map, the tent map and the Kaplan–Yorke map. The mean square error and the signal-to-noise ratio between the decrypted image and the input image for the correct order and the incorrect order of the fractional Fourier transform have been calculated. The computer simulations are presented to verify the validity of the proposed technique.     

Multifocus image fusion scheme using focused region detection and multiresolution

To solve the fusion problem of the multifocus images of the same scene, a novel algorithm based on focused region detection and multiresolution is proposed. In order to integrate the advantages of spatial domain-based fusion methods and transformed domain-based fusion methods, we use a technique of focused region detection and a new fusion method of multiscale transform (MST) to guide pixel combination. Firstly, the initial fused image is acquired with a novel multiresolution image fusion method. The pixels of the original images, which are similar to the corresponding initial fused image pixels, are considered to be located in the sharply focused regions. By this method, the initial focused regions can be determined, and the techniques of morphological opening and closing are employed for post-processing. Then the pixels within the focused regions in each source image are selected as the pixels of the fused image; meanwhile, the initial fused image pixels which are located at the focused border regions are retained as the pixels of the final fused image. The fused image is then obtained. The experimental results show that the proposed fusion approach is effective and performs better in fusing multi-focus images than some current methods.     

Image encryption and decryption using fractional Fourier transform and radial Hilbert transform

A technique for image encryption using fractional Fourier transform (FRT) and radial Hilbert transform (RHT) is proposed. The spatial frequency spectrum of the image to be encrypted is first segregated into two parts/channels using RHT, and image subtraction technique. Each of these channels is encrypted independently using double random phase encoding in the FRT domain. The different fractional orders and random phase masks used during the process of encryption and decryption are the keys to enhance the security of the proposed system. The algorithms to implement the proposed encryption and decryption scheme are discussed, and results of digital simulation are presented.     

一种自适应的多光谱图像与全光图像融合新方法

对于不同多光谱图像与全光图像的融合,目前一些融合算法在光谱信息和分辨率上不能同时得到较好的融合效果.针对这一问题,提出一种新的自适应图像融合方法.实验结果表明,该方法不仅能够较好地保留融合图像的光谱信息和提高空间分辨率,而且具有较强的自适应性.     

Image encryption based on extended fractional Fourier transform and digital holography technique

We present a new optical image encryption algorithm that is based on extended fractional Fourier transform (FRT) and digital holography technique. We can perform the encryption and decryption with more parameters compared with earlier similar methods in FRT domain. In the extended FRT encryption system, the input data to be encrypted is extended fractional Fourier transformed two times and random phase mask is placed at the output plane of the first extended FRT. By use of an interference with a wave from another random phase mask, the encrypted data is stored as a digital hologram. The data retrieval is operated by all-digital means. Computer simulations are presented to verify its validity and efficiency.     

Reversible authentication and cross-recovery of images using (t, n)-threshold and modified-RCM watermarking

This paper presents an image authentication scheme for digital images. The proposed scheme protects a group of n images mutually. It designs a block matching procedure to generate the recovery data for each image, and applies a (t, n − 1), 2 ≤ t < n, threshold mechanism to encode each recovery data in n − 1 shares. The recovery shares are cross-embedded in the n images using a modified reversible contrast mapping watermarking scheme. A signature-based authentication code is finally generated and stamped to provide evidence for integrity of each image. The scheme not only can detect the tampering activities, but also can locate and recover the invalid regions of the tampered image if t or more watermarked images in the same group were intact. A nice characteristic of the proposed scheme is that the original images can be reconstructed lossless if no watermarked image was tampered, making the technique feasible in the application of protecting very sensitive images such as military or medical images. Experimental results show that the proposed scheme successfully detects various kinds of image alterations such as filtering, cropping, and replacement, and the corrupted images are properly recovered using the cross-recovery scheme.     

Color image encryption and decryption using fractional Fourier transform

We propose the encryption of color images using fractional Fourier transform (FRT). The image to be encrypted is first segregated into three color channels: red, green, and blue. Each of these channels is encrypted independently using double random phase encoding in the FRT domain. The different fractional orders and random phase masks used during the process of encryption and decryption are the keys to enhance the security of the proposed system. The algorithms to implement the proposed encryption and decryption scheme are discussed, and results of digital simulation are presented. The technique is shown to be a powerful one for colored text encryption. We also outline the implementation of the algorithm and examine its sensitiveness to changes in the fractional order during decryption.     

Signal separation using linear canonical and fractional Fourier transforms

Signal separation is an important operation in many areas such as communications, geophysics, and optics including optical signal processing. In this article, the issue of signal separation based on the linear canonical transform (LCT) and the fractional Fourier transform (FRFT) is considered. An iterative algorithm for signal separation in the 2-ray ground reflected model using the FRFT is also presented along with the simulation results.     

基于小波变换和数据融合技术的弱小目标检测

鉴于弱小目标检测所固有的难点及常用的单一分辨率下的检测方法还不能准确稳定地检测出目标,提出了一种弱小目标检测新方法。考虑到实际应用中的复杂背景和大量干扰噪声,运用数据融合技术,先对图像进行小波多分辨率分解,然后将不同分辨率下的子图进行最优加权平均融合来检测弱小目标。用实地拍摄的空中弱小目标红外和可见光图像分别进行实验验证,实验图像取256×256像素点阵大小,其中目标占10×10像素左右。结果表明该方法能够准确稳定地检测弱小目标,为后续的跟踪作了很好的铺垫。     

一种基于小波变换的多尺度多算子图像融合方法

图像融合技术以其综合多传感器信息的优越性日益受到诸多领域的重视。为了使其应用在医学、遥感、计算机视觉、气象预报、军事目标识别等方面更迅速、深入地开展,有效、实用的融合算法是至关重要的。本文在小波变换金字塔结构的基础上,提出了一种多尺度多算子融合方法,对热红外图像和可见光图像的融合进行了研究。结果融合效果很好,目标和背景区别显著,而且边缘不突兀。由于这种方法对小波分解的层数要求不高,因此计算量不大,便于并行处理及硬件实时化实现,具有广阔的应用前景。     

An improved fusion algorithm for infrared and visible images based on multi-scale transform

In this paper, an improved fusion algorithm for infrared and visible images based on multi-scale transform is proposed. First of all, Morphology-Hat transform is used for an infrared image and a visible image separately. Then two images were decomposed into high-frequency and low-frequency images by contourlet transform (CT). The fusion strategy of high-frequency images is based on mean gradient and the fusion strategy of low-frequency images is based on Principal Component Analysis (PCA). Finally, the final fused image is obtained by using the inverse contourlet transform (ICT). The experiments and results demonstrate that the proposed method can significantly improve image fusion performance, accomplish notable target information and high contrast and preserve rich details information at the same time.