We present a general purpose blind image quality assessment (IQA) method using the statistical independence hidden in the joint distributions of divisive normalization transform (DNT) representations for natural images. The DNT simulates the redundancy reduction process of the human visual system and has good statistical independence for natural undistorted images; meanwhile, this statistical independence changes as the images suffer from distortion. Inspired by this, we investigate the changes in statistical independence between neighboring DNT outputs across the space and scale for distorted images and propose an independence uncertainty index as a blind IQA (BIQA) feature to measure the image changes. The extracted features are then fed into a regression model to predict the image quality. The proposed BIQA metric is called statistical independence (STAIND). We evaluated STAIND on five public databases: LIVE, CSIQ, TID2013, IRCCyN/IVC Art IQA, and intentionally blurred background images. The performances are relatively high for both single- and cross-database experiments. When compared with the state-of-the-art BIQA algorithms, as well as representative full-reference IQA metrics, such as SSIM, STAIND shows fairly good performance in terms of quality prediction accuracy, stability, robustness, and computational costs.
State of the art blind image quality assessment (IQA) methods generally extract perceptual features from the training
images, and send them into support vector machine (SVM) to learn the regression model, which could be used to further
predict the quality scores of the testing images. However, these methods need complicated training and learning, and the
evaluation results are sensitive to image contents and learning strategies. In this paper, two novel blind IQA metrics
without training and learning are firstly proposed.
The new methods extract perceptual features, i.e., the shape consistency of conditional histograms, from the joint
histograms of neighboring divisive normalization transform coefficients of distorted images, and then compare the length
attribute of the extracted features with that of the reference images and degraded images in the LIVE database. For the
first method, a cluster center is found in the feature attribute space of the natural reference images, and the distance
between the feature attribute of the distorted image and the cluster center is adopted as the quality label. The second
method utilizes the feature attributes and subjective scores of all the images in the LIVE database to construct a
dictionary, and the final quality score is calculated by interpolating the subjective scores of nearby words in the
Unlike the traditional SVM based blind IQA methods, the proposed metrics have explicit expressions, which reflect the
relationships of the perceptual features and the image quality well. Experiment results in the publicly available databases
such as LIVE, CSIQ and TID2008 had shown the effectiveness of the proposed methods, and the performances are fairly
We recently proposed a natural scene statistics based image quality assessment (IQA) metric named STAIND, which
extracts nearly independent components from natural image, i.e., the divisive normalization transform (DNT)
coefficients, and evaluates perceptual quality of distortion image by measuring the degree of dependency between
neighboring DNT coefficients. To improve the performance of STAIND, its feature selection strategy is thoroughly
analyzed in this paper.
The basic neighbor relationships in STAIND include scale, orientation and space. By analyzing the joint histograms of
different neighborships and comparing the IQA model performances of diverse feature combination schemes on the
publicly available databases such as LIVE, CSIQ and TID2008, we draw the following conclusions: 1) Spatial neighbor
relationship contributes most to the model design, scale neighborship takes second place, and orientation neighbors
might introduce negative effects; 2) In spatial domain, second order spatial neighbors are beneficial supplements to first
order spatial neighbors; 3) The combined neighborship between the scales, spaces and the introduced spatial parents is
very efficient for blind IQA metrics design.
An improved second generation digital image watermarking scheme is proposed. This scheme exploits the region feature instead of point or line feature. The region features are retrieved by watershed transform, which allows watermark recovery after common attacks. The experiments have shown that this proposed scheme is robust against compression, noise intrinsically and more robust against geometrical attacks and JPEG compression compared with Kutter's method. The watermark capacity is improved because the robustness of region feature is more than point or line feature.
A self-synchronization blind image watermarking technique based on wavelet transform is proposed in this paper. Synchronization is a serious problem to any watermarking schemes while many existed watermarking did not mention it. Image manipulations such as geometric distortions, even by slight amount, can cause the self-synchronization between watermark embedding and detection process so to make the detector disable. So for any watermark detector, synchronization is the precondition of correct detection. In this approach, a new way to estimate the asynchronous distortion parameters by using the one or two characteristics of the host image is proposed to make the re-synchronization of watermarking technique. The characteristics can be used as private key of detector to enhance the safety of watermark. Independent Component Analyze is adopted by detector so that the detector can extract not merely detect the watermarks blindly without using any information about the host image, watermark and any other embedding and attack information. The time tag is also used in watermark to resolve the problem of the multi-embedded watermark deadlock. That is, the detector can extract all embedded watermarks and determine who embeds his watermark first. Experimental results demonstrated that the proposed watermarking technique is robust against watermark attacks produced by Stirmark-the popular watermark test software, such as JPEG compression, scaling, translation, rotation, shearing, filtering.
In this paper, an improved second generation digital image watermarking scheme is proposed. This scheme exploits the region feature instead of point or line feature. The region features are retrieved by watershed transform, which allows watermark recovery after common attacks. The experiments have shown that this proposed scheme is robust against compression, noise intrinsically and more robust against geometrical attacks and JPEG compression compared with
Kutter’s method. The watermark capacity is improved because the robustness of region feature is more than point or line feature.
Independent Components Analysis (ICA) is an effective approach of blind source separation and has been received much more attention because of its potential application in signal processing such as telecommunication and image processing. Feature extraction of images has been also focused as one of prominent applications of ICA. Nine Stroke Density (NSD) feature extraction method will provide sufficient information to the recognition engine. Several other feature extraction methods are discussed and compared to stroke density method in detail. ICA extracts the underlying statistically independent components from a mixture of the NSD feature vectors. These independent components are feed into the neural netowrk for the recognition purpose. The experiment results show that ICA performs well for feature extraction and this proposed method is more effective in recognizing handwriting character than merely using neural networks directly.
Multiple digital watermarking is attracting more and more researchers because it is more valuable in the practical applications than single watermarking. In this paper, a multiple watermarking algorithm based on 1-D and 2-D chaotic sequences is proposed. The chaotic sequences have the advantages of massive, high security, and weakest correlation. The massive and independent digital watermark signals are generated through 1-D chaotic maps, which are determined by different initial conditions and parameters. The chaotic digital watermark signals effectively resolve the construction of massive watermarks with good performance. The embedding of multiple watermakrs is more complex than the single watermarking scheme. In this paper, each watermark is added to the middle frequency coefficients of wavelet domain randomly by exploiting 2-D chaotic system, so the embedding and extracting of each watermark would not disturb each other. Considering the parameters of 2-D chaotic systsem as the key to embedding procedure can prevent the watermarks to be removed maliciously, therefore the performance of security is better. The capacity of the multiple watermarking is also analyzed in this paper. The experimental results demonstrate that this proposed watermarking algorithm is robust to many common attacks and it is a reliable copyright protection for multiple legal owners.
Image watermarking has become a popular technique for authentication and copyright protection with the development of Internet and computer. However, current image watermarking approaches especially blind techniques are not strongly robust with respect to attacks or combinations of several attacks. In this paper a new intelligent second generation blind image watermarking technique is proposed, which adopts independent component analysis (ICA) for watermarking process. The characteristics of the human visual system (HVS) are incorporated into the watermark embedding, so that the watermark can be adaptive to the protected image. The edge of original image which extracted by Sobel operator is used as watermark in this paper. The watermark is rearranged by chaotic before watermark embedding in order to enhance the robustness of watermarking and the embedding process can be performed in any image domain, including spatial and transform domain. Watermark can be extracted correctly not merely be detected without any information about the original image and original watermark, and the accuracy of watermark extraction depends on the statistical independence between the original image, original watermark and the key. This proposed intelligent system can also extract multiple watermarks embedded in the test image one by one. Experimental results demonstrate that the proposed intelligent second generation watermarking technique based on ICA is robust with respect to attacks produced by popular watermark test software - Stirmark, including rotation, scaling, translation, skew, cropping, filtering, image compression, and combined attacks.
Most digital watermarking algorithms are not robust against geometric attacks. In this paper several improvements of watermarking algorithms are proposed. It may present additional advantages in terms of detection and recovery from geometric attacks by exploiting chaotic spread spectrum and synchronization techniques. These improvements come from three aspects. First, based on the randomness, noise like and extreme sensitivity to initial conditions of chaotic signal, chaotic sequence is exploited as spread spectrum code in the watermarking algorithms. The code spread from chaotic sequence has better performance than pseudo random code because it is massive, arbitrary length and high security. The robustness of the watermarking is improved greatly due to the original watermarking signal is modulated in broadband chaotic signal. Second, a synchronization code generated from chaotic sequence is inserted into the watermarking signal at specified intervals. A watermark cannot be detected correctly after geometric attacks because the synchronization information is lost in watermarking extracting. By locating the synchronization code, re-synchronization can be achieved. Hence, the watermark can be recovered furthest from geometric attacks. Third, the extracted watermark will be post processed with noise reduction filter in order to improve the accuracy of watermarking verification. Based on the characteristics of chaotic sequence, the noise signal can be separated from chaotic background by exploiting wavelet multi-scaling decomposition method. These improvements, which take full advantage of the characteristic of chaotic sequences, are feasible to resist geometric attacks. Experiment results demonstrate its effectiveness.
Multiple digital watermarking technique can resolve the problems of multiple copyright claim and keep the traces of digital products in the different phase of publishing, selling and using. In this paper, a multiple digital watermarking algorithm based on chaotic sequences is proposed. The chaotic sequences have the advantages of massive, high security, and weakest correlation. The massive and independent digital watermark signals are generated through 1-D chaotic maps, which are determined by different initial conditions and parameters. The chaotic digital watermark signals effectively resolve the construction of massive watermarks with good performance. The capacity of the multiple watermarking is also analyzed in this paper. The length of the watermark can be selected adaptively according to the number of the watermarks. Multiple digital watermarking algorithm is more complex than the single watermarking algorithm in the embedding method. The principal problem is how to ensure that the late-coming watermark will not damage the embedded watermarks. Each watermark is added to the middle frequency coefficients of wavelet domain randomly by exploiting 2-D chaotic system, so the embedding and extracting of each watermark does not disturbed each other. Thinking of the parameters of 2-D chaotic system as the key to embedding procedure can prevent the watermarks to be removed malevolently, therefore the performance of security is better. The embedding algorithm based on noise analysis and wavelet transform is also exploited in this paper. To meet the transparence and robustness of the watermark, the watermark strength is adapted to the noise strength within the tolerance of wavelet coefficients. The experimental results demonstrate that this proposed algorithm is robust to many common attacks and the performance can satisfy the requirements in the application.
In this paper, a scheme which following the second generation watermarking paradigm is proposed. The goal of this proposed scheme is basically to increase the robustness against geometric attacks. The host image is decomposed with the wavelet packet. The bit stream of binary watermark is coded into several patterns with salient feature. The circular feature is used in this paper, because: (a) the computational complexity of the method grows rapidly with more complex shapes. (b) circle is rotation-invariant and partially scale-invariant. (c) circular feature can be detected by Hough transform effectively. These patterns are embedded into wavelet packet coefficients according to human perceptual characteristics. A new HVS mask based on wavelet transform is proposed with consideration of local texture characteristics. The introduction of HVS characteristics boosts the performance of the whole scheme. For the detection of watermark, the geometric distortion is calibrated for the contaminated watermarked image. Hough transform is used to detect the circular features in the WP Coefficients. This scheme has the following characteristics: (a) robustness against the common geometric attacks(rotation, scaling, cropping, and etc) is improved significantly. (b) human perceptual characteristics is taken into consideration, so the tradeoff between invisibility and robustness is improved. Results of extensive experiments indicate that this proposed scheme is significantly effective in resisting various geometric attacks such as rotation, scaling, JPEG compression, adding noise, etc.
This paper represents a new spatial domain digital watermarking method, which can trade off between spatial domain and frequency domain approaches. This technique produces a watermarked image that closely retains the quality of the original host image while concurrently surviving various image processing operations such as lowpass/highpass filtering, lossy JPEG compression, and cropping. This image watermarking algorithm takes full advantage of permutation and 2-D barcode, which is PDF417 coding. The actual watermark embedding in spatial domain is followed using permutated image for improving the resistance to image cropping. Much higher robustness of watermark is obtainable via forward error correction (FEC) technique, which is the main feature of PDF417 codes. Additional features of this technique include the easy determination of the existence of the watermark and that the watermark verification procedure does not need the original host image.
This paper presents techniques for constructing full view panoramic mosaics from sequences of images. The goal of this work is to remove too many limitations for pure panning motion. The best reference block is critical for the block- matching method for improving the robustness and performance. It is automatically selected in the high- frequency image, which always contains the plenty visible features. In order to reduce accumulated registration errors, the global registration using the phase-correlation matching method with rotation adjustment is applied to the whole sequence of images, which results in an optimal image mosaic with resolving translational or rotational motion. The local registration using the Levenberg-Marquardt iterative non-linear minimization algorithm is applied to compensate for small amounts of motion parallax introduced by translations of the camera and other unmodeled distortions, when minimize the discrepancy after applying the global registration. The accumulated misregistration errors may cause a visible gap between the two images. A smoothing filter is introduced, derived from Marr's computer vision theory for removing the visible artifact. By combining both global and local registration, together with artifact smoothing, the quality of the image mosaics is significantly improved, thereby enabling the creation of full view panoramic mosaics with hand-held cameras.