An adaptive reconstruction system for spatially correlatedmultispectral multitemporal images

An adaptive image reconstruction system has been developed to analyze sequential images observed at regular time intervals. A least-squares linear prediction with escalator structure has been implemented in this system. Using the predictor, estimates of missing data or bad (possibly cloud-covered) data and spatial parameters at a specified time can be obtained from previous history. This algorithm recovers from observations which are contaminated due to blurring and correlated noise by using temporally adapted spatial parameters     

An efficient Re-indexing algorithm for color-mapped images

The efficiency of lossless compression algorithms for fixed-palette images (indexed images) may change if a different indexing scheme is adopted. Many lossless compression algorithms adopt a differential-predictive approach. Hence, if the spatial distribution of the indexes over the image is smooth, greater compression ratios may be obtained. Because of this, finding an indexing scheme that realizes such a smooth distribution is a relevant issue. Obtaining an optimal re-indexing scheme is suspected to be a hard problem and only approximate solutions have been provided in literature. In this paper, we restate the re-indexing problem as a graph optimization problem: an optimal re-indexing corresponds to the heaviest Hamiltonian path in a weighted graph. It follows that any algorithm which finds a good approximate solution to this graph-theoretical problem also provides a good re-indexing. We propose a simple and easy-to-implement approximation algorithm to find such a path. The proposed technique compares favorably with most of the algorithms proposed in literature, both in terms of computational complexity and of compression ratio.     

An orthogonal wavelet representation of multivalued images

A new orthogonal wavelet representation of multivalued images is presented. The idea for this representation is based on the concept of maximal gradient of multivalued images. This concept is generalized from gradients toward linear vector operators in the image plane with equal components along rows and columns. Using this generalization, the pyramidal dyadic wavelet transform algorithm using quadrature mirror filters is modified to be applied to multivalued images. This results in a representation of a single image, containing multiscale detail information from all component images involved. This representation leads to multiple applications ranging from multispectral image fusion to color and multivalued image enhancement, denoising and segmentation. In this paper, the representation is applied for fusion of images. More in particular, we introduce a scheme to merge high spatial resolution greylevel images with low spatial resolution multivalued images to improve spatial resolution of the latter while preserving spectral resolution. Two applications are studied: demosaicing of color images and merging of multispectral remote sensing images.     

Binary partition tree as an efficient representation for imageprocessing, segmentation, and information retrieval

This paper discusses the interest of binary partition trees as a region-oriented image representation. Binary partition trees concentrate in a compact and structured representation a set of meaningful regions that can be extracted from an image. They offer a multiscale representation of the image and define a translation invariant 2-connectivity rule among regions. As shown in this paper, this representation can be used for a large number of processing goals such as filtering, segmentation, information retrieval and visual browsing. Furthermore, the processing of the tree representation leads to very efficient algorithms. Finally, for some applications, it may be interesting to compute the binary partition tree once and to store it for subsequent use for various applications. In this context, the paper shows that the amount of bits necessary to encode a binary partition tree remains moderate.     

An efficient and effective region-based image retrieval framework

An image retrieval framework that integrates efficient region-based representation in terms of storage and complexity and effective on-line learning capability is proposed. The framework consists of methods for region-based image representation and comparison, indexing using modified inverted files, relevance feedback, and learning region weighting. By exploiting a vector quantization method, both compact and sparse (vector) region-based image representations are achieved. Using the compact representation, an indexing scheme similar to the inverted file technology and an image similarity measure based on Earth Mover's Distance are presented. Moreover, the vector representation facilitates a weighted query point movement algorithm and the compact representation enables a classification-based algorithm for relevance feedback. Based on users' feedback information, a region weighting strategy is also introduced to optimally weight the regions and enable the system to self-improve. Experimental results on a database of 10,000 general-purposed images demonstrate the efficiency and effectiveness of the proposed framework.     

An efficient forward secure group signature scheme with revocation

Up to now, how to construct an efficient secure group signature scheme, which needs not to reset the system when some group members＇ signing keys are exposed, is still a difficult problem. A construction concerning revocation of group members is an ideal one if it satisfies forward security which makes it more attractive for not sacrificing the security of past signatures of deleted members. This paper analyses the problem and gives a construction in which the group manager can be untrustworthy. The scheme is efficient even when the number of revoked members is large.     

An efficient and secure cipher scheme for images confidentiality preservation

In this paper, a novel image encryption scheme based on two rounds of substitution–diffusion is proposed. Two main objectives have guided the design of this scheme: (a) robustness against the most known type of attacks (statistical, chosen/known plaintext, ciphertext-only and brute force attacks) and (b) efficiency in terms of computational complexity (i.e., execution time reduction) in order to meet recent mobiles’ applications’ requirements. First, a dynamic key, changed for every input image is generated and used as the basis to construct the substitution and diffusion processes. Then, the encryption process is performed by the transmitter based on a non-linear S-box (substitution) and a matrix multiplication (diffusion), applied on each sub-matrix of the image. At the destination side, decryption is applied in the reverse order. We have conducted several series of experiments to evaluate the effectiveness of the proposed scheme. The obtained results validated the robustness of our scheme against all considered types of attacks and showed an improvement in terms of execution time reduction compared to the recent existed image-encryption schemes.     

An efficient high-capacity reversible data hiding scheme for encrypted images

Reversible data hiding in encrypted images is an effective technique to embed information in encrypted domain, without knowing the original content of the image or the encryption key. In this paper, a high-capacity reversible data hiding scheme for encrypted images based on MSB (most significant bit) prediction is proposed. Since the prediction is not always accurate, it is necessary to identify the prediction error and store this information in the location map. The stream cipher is then used to encrypt the original image directly. During the data hiding phase, up to three MSBs of each available pixel in the encrypted image are substituted by the bits of the secret message. At the receiving end, the embedded data can be extracted without any errors and the original image can be perfectly reconstructed by utilizing MSB prediction. Experimental results show that the scheme can achieve higher embedding capacity than most related methods.     

An efficient high-dimensional indexing method for content-based retrieval in large image databases

High-dimensional indexing methods have been proved quite useful for response time improvement. Based on Euclidian distance, many of them have been proposed for applications where data vectors are high-dimensional. However, these methods do not generally support efficiently similarity search when dealing with heterogeneous data vectors. In this paper, we propose a high-dimensional indexing method (KRA⁺-Blocks) as an extension of the region approximation approach to the kernel space. KRA⁺-Blocks combines nonlinear dimensionality reduction technique (KPCA) with region approximation approach to map data vectors into a reduced feature space. The created feature space is then used, on one hand to approximate regions, and on the other hand to provide an effective kernel distances for both filtering process and similarity measurement. In this way, the proposed approach achieves high performances in response time and in precision when dealing with high-dimensional and heterogeneous vectors.     

一个高效的门限共享验证签名方案及其应用

基于离散对数问题提出一个新的门限共享验证签名方案，该方案是EIGamal签名方案和Shamir门限方案的结合。在该方案中，n个验证者中任意t个可以验证签名的有效性，而t-1个或更少的验证者不能验证签名的有效性。伪造该方案的签名等价于伪造EIGamal签名。与已有方案相比，该方案的签名效率更高。最后基于该门限共享验证签名方案提出一个新的口令共享认证方案。     

An efficient reversible authentication scheme for demosaiced images with improved detectability

The existing probability based reversible authentication schemes for demosaiced images embed authentication codes into rebuilt components of image pixels. The original demosaiced image can be totally recovered if the marked image is unaltered. Although these schemes offer the goal of pixel-wise tamper detection, the generated authentication codes are irrelevant to the image pixels, causing some undetectable intentional alterations. The proposed method pre-processes the rebuilt components of demosaiced images and hashes them to generate authentication codes. With the guide of a randomly-generated reference table, authentication codes are embedded into the rebuilt components of demosaiced images. Since the distortions of image pixels are sensitive to the embedded authentication codes, the proposed method further alters the pre-processed pixels to generate a set of authentication codes. One of the authentication codes that minimizes the distortion is embedded to generate marked demosaiced images. The results show that the proposed method offers a better image quality than prior state-of-the-art works, and is capable of detecting a variety of tampering.     

An efficient algorithm for the removal of impulse noise from corrupted images

In this letter, we propose an efficient algorithm, which can successfully remove impulse noise from corrupted images while preserving image details. It is efficient, and requires no previous training. The algorithm consists of two steps: impulse noise detection and impulse noise cancellation. Extensive experimental results show that the proposed approach significantly outperforms many other well-known techniques for image noise removal.     

Aging signature properties and an efficient signature determination tool for online monitoring

Increased reliability problems in deep sub-micron CMOS technologies have led to a dramatic decrease of lifetime of analog integrated circuits. To palliate this problem, several reliability-aware design approaches have been developed. Reconfigurable circuit design is one of those approaches, which is based on reconfiguring the circuit considering degradation in circuit performances. Sense & React (S & R) approach is the well-known reconfigurable design approach, where degradation in circuit performances are sensed and a pre-established recovery operation is applied to heal the circuit. In practice, indirect measurements are preferred during sense operation, in which electrical quantities are measured in order to determine time to recovery. Determination of the time to recover is the most critical part of a S & R system. One or more circuit variables are selected out of all measurable circuit quantities. The selected signature should have some attributes to be used as the aging signature to reduce the measurement cost. However, efficient aging signature properties have not been defined in the literature yet. Moreover, the designer determines the aging signature manually by performing an iterative search and evaluation on aging simulation results, and there is no tool to ease this time consuming process. This paper clearly describes the aging signature properties and proposes an automatic signature selection tool that determines the most efficient signature for sense operation.     

Similarity retrieval of trademark images

The Artisan system retrieves abstract trademark images by shape similarity. It analyzes each image to characterize key shape components, grouping image regions into families that potentially mirror human image perception, and then derives characteristic indexing features from these families and from the image as a whole. We have evaluated the retrieval effectiveness of our prototype system on more than 10,000 images from the UK Trade Marks Registry     

一种有效的序列农作物图像360度自动拼接方法

提出了一种基于加速鲁棒特征（SURF：Speeded-Up Robust Features）和K最近邻算法（K-Nearest Neighbor Search,K-NNS,K=2）的序列农作物图像360度拼接方法。首先利用SURF算法进行特征点提取。然后使用K最近邻算法对特征点进行匹配,保存最优的匹配置信度。利用改进的算法避免了手动设置置信度阈值的弊端,对序列农作物图像进行正确排序。对排序后的图像进行照相机参数估计,粗略估计出旋转参数,利用光束平差法对旋转参数进行精确估算。对全景图进行立体映射,最后对图像进行拼接和多频段融合。实验表明,此算法不但可以高效的实现农作物序列图像的自动拼接,与原有算法相比更具鲁棒性。而且拼成的全景图更具完整性和视觉一致性,具有较高的实用价值,有利于对农田的全面观测。     

Recursive algorithm for efficient representation of ECG signals

A method is presented for representing signals made up of discrete component waves separated by iso-electric regions such as electrocardiogram (EGG), respiratory and blood pressure signals. The computational complexity is minimised by treating the discrete cosine transform of a group of component waves to be the sum of a finite number of biphasic rational functions