Single Image Superresolution Based on Support Vector Regression

At recently, the most of the digital images are stored and transferred in their compressed format using discrete cosine transform (DCT)-based compression technique. DCT is one of the most important data compression technique due to the efforts from Joint Photographic Experts Group(JPEG). Blind steganalysis means how to detect the presence of the messages that are hidden using different types of steganography algorithms and has the ability to detect new unknown steganography algorithms. This paper presents blind steganalysis technique that can reliably detect the existence of messages hidden in JPEG files. In order to save the computation and memory cost, it is desirable to have image processing operations implemented directly in the DCT domain. The proposed method is based on extracting features directly from DCT domain through the analysis of differences between DCT coefficients before and after cropping. The extracted features are prepared as input to Support Vector Machine (SVM) to classify the image as stego (image that contain secret message) or clean (image that does not contain secret message). The experiments performed show that the proposed method yields better classification accuracy compared with other related works.

Many effective watermarking algorithms have been proposed and implemented for digital images and digital video. However, a few algorithms have been proposed for audio watermarking. This is due to the fact that, human auditory system (HAS) is far more complex and sensitive than human visual system (HVS). In this research work, a new method of embedding image data into the audio signal and additive audio watermarking algorithm based on Discrete Cosine Transformation (DCT) domain is proposed. First, the original audio is transformed into DCT domain. The DCT coefficients are divided into a fixed number of subsections and the energy of each subsection is calculated. Next, watermark is generated from image by image processing algorithm. Watermarks are then embedded into selected peaks of highest energy subsection. Experimental results demonstrate that the watermark is inaudible and this algorithm is robust to common operations of digital audio signal processing, such as noise addition, re-sampling, requantization and so on. To evaluate the performance of the proposed audio watermarking method, subjective and objective quality tests including Bit Error Rate (BER) and Signal to Noise ratio (SNR) are conducted.

디지털 워터마킹은 저작권 보호와 멀티미디어 데이터 인증의 수단으로 사용되어 왔다. 기존의 공간영역에서의 CRT 기반 워터마킹 방법은 JPEG 압축에 취약하여, JPEG 압축에서 잘 동작하는 DCT 영역에서의 CRT 기반 워터마킹이 제안되었다. 본 논문에서는 DCT 영역에서의 향상된 CRT 기반 워터마킹 방법을 제안한다. 제안한 방법은 DCT 변환시 발생되는 rounding 오류 또는 여러 가지 공격에도 나머지들의 차에 대한 절대값의 변화를 감소시켜 견고성을 향상시킨다. 실험을 통하여 제안한 방법이 기존의 DCT 영역에서의 CRT 기반 워터마킹 방법보다 여러 가지 공격에 대하여 견고성이 향상되는 것을 확인하였다. Digital watermarking techniques have been used as one of the means for copyright protection and authentication of multimedia data. Conventional Chinese Remainder Theorem(CRT)-based spatial domain watermarking techniques do not perform well under JPEG compression. However, it is seen that the CRT-based watermarking technique in Discrete Cosine Transform(DCT) domain performs well for JPEG compression. In this paper, an improved CRT-based image watermarking method in the DCT domain is proposed. The proposed method provides better robustness which decreases changes of absolute difference of residues against rounding errors due to DCT conversion and various attacks. Experimental results show that the proposed method has a good robustness against various attacks compared with the conventional CRT-based watermarking in DCT domain.

Presented is an efficient watermarking scheme using Particle Swarm Optimization (PSO) to watermark host fingerprint images with their corresponding facial images in the Discrete Cosine Transform (DCT) domain. PSO is used to find the best DCT coefficients’ locations in the host image where the facial image data can be embedded, so that the distortion produced in the host image is minimum. The objective function for PSO is formulated in terms of the Structural Similarity Index (SSIM) and the Orientation Certainty Level Index (OCL) so as to base it on the simple visual effect of the human visual perception capability and correct minutia prediction ability. The results exhibit better watermarked image quality while retaining the feature set of the original fingerprint. Moreover, the proposed technique is robust so that the extraction of watermark is possible even after the watermarked image is exposed to attacks. As a result, at the receiver’s end, the watermarked fingerprint image and the extracted facial image can be verified for a secure and accurate biometric based personal authentication.

With the wide use of various image altering tools, digital image manipulation becomes very convenient and easy, which makes the detection of image originality and authenticity significant. Among various image tampering detection tools, double JPEG image compression detector, which is not sensitive to specific image tampering operation, has received large attention. In this paper, we propose an improved double JPEG compression detection method based on noise-free DCT (Discrete Cosine Transform) coefficients mixture histogram model. Specifically, we first extract the block-wise DCT coefficients histogram and eliminate the quantization noise which introduced by rounding and truncation operations. Then, for each DCT frequency, a posterior probability can be obtained by solving the DCT coefficients mixture histogram with a simplified model. Finally, the probabilities from all the DCT frequencies are accumulated to give the posterior probability of a DCT block being authentic or tampered. Extensive experimental results in both quantitative and qualitative terms prove the superiority of our proposed method when compared with the state-of-the-art methods.

This paper presents new fast full search motion estimation (ME) algorithms using discrete cosine transform (DCT) coefficients as a gradient magnitude. The proposed algorithms use intra DCT coefficients to arrange the matching scan order. The proposed algorithm 1 uses some of DCT coefficients based on the relationship between gradient magnitude and DCT coefficients, and the proposed algorithm 2 uses all of DCT alternating current (AC) coefficients in order to predict the fluctuation of a block. The proposed algorithms significantly reduce the computational complexity of the conventional algorithm while maintaining the visual quality of video.

This paper presents an efficient hybrid watermarking scheme for securing fingerprint images in the Discrete Cosine Transform (DCT) domain. The proposed method uses a NN-PSO (Neural Network-Particle Swarm Optimization) based hybrid approach to watermark host gray scale fingerprint images with their corresponding facial images in order to secure them. The algorithm divides the input image into blocks and uses a feed forward NN to determine the number of secret bits to be embedded in each block depending on the blocks' features. The output of the NN is then used as input by the PSO module to find the best DCT coefficients' locations in that block where the secret facial image data can be embedded, so that the distortion produced in the host image is minimum and the minutia predicting ability remains unaffected. The experimental results have been analyzed and compared with existing PSO based and NN based approaches. The proposed NN-PSO based hybrid approach has been found to exhibit better watermarked image quality and better robustness to possible attacks to the watermarked image. Moreover, as the proposed technique retains the feature set of the original fingerprint, the extracted facial image and the cover fingerprint image can be correctly verified at the receiver's end leading to a more secure and accurate biometric based personal authentication.

In this paper, a new block matching criterion is proposed for motion estimation in video coding. The new criterion is based on a comparison between the discrete cosine transform (DCT) coefficients of two blocks to be matched. Since the spectrum of DCT statistically concentrates on the neighborhood of the dc component and the number of non-zero coefficients is quite small, only few coefficients need to be considered when matching blocks according to the new criterion. Almost in all the video coding standards, DCT is a necessary step for spatial redundancy reduction. Thus the generated DCT coefficients can be utilized in the new criterion. However, there are still some blocks whose DCT coefficients are not available. Several algorithms of calculating DCT coefficients of these blocks are given. When this new criterion is combined with the logarithm search, promising results are produced.

With the wide application of support vector machine(SVM), the algorithm of using online learning for realizing regression had been developed furtherly. After the mathematical mode of direct support vector machine (DSVM) for regression was introduced which was of the learning capacity that was similar to least squares support vector machine but less complexity of computation, according to Cholesky factorization, the algorithm of incremental learning and decremental learning were designed for DSVM in this paper, through them online learning that based on time window for regression was realized. Experimental results of simulation through Mackey-Glass chaotic time series and pseudo periodic synthetic time series data set all indicate the feasibility of the learning algorithm which will be beneficial for SVM's application in depth.

It is already known that a curve estimated via the discrete cosine transform (DCT) always passes through all the measured points without using imaginary numbers in the DCT coefficients, unlike the discrete Fourier transform. Moreover, owing to its character, the DCT can be used instead of the nonlinear least-squares method to express various theoretical curves. Because the DCT is a kind of Fourier transform, there is a possibility that the DCT could be employed to draw electron density distribution maps of crystals. If so, the probability that the DCT could be used to investigate the internal structure of materials by analysing the theoretical curves would increase. This article reports an attempt to draw the electron density distribution maps of the Mg3BN3 low-pressure phase [Mg3BN3(L)] by using the DCT in order to confirm the utility of the DCT for analysing the internal structure of materials. It is found that the DCT can provide mirror-symmetric electron density distribution projection maps and a modified DCT can be used to calculate whole standard electron density distribution projection maps for the surface plane of the unit cell. Moreover, a real crystal structure that has a centre of symmetry can be determined by the DCT by transforming a 1/4 part of the mirror-symmetric electron density distribution projection map.

The performance and effectiveness of CBIR scheme are directly associated with construction of small dimensional as well as salient image features respectively. So, in this paper, we have carried out the image retrieval process with small dimensional salient Image components or features as compare to the original image size and the imaze retrieval accuracy has been improved due to the consideration of local information rather than global information of Image data. Initially, the Image data is exploited in block level by discrete cosine transformation (DCT) and subsequently, some significant DCT coefficients are selected from each block as salient image components. However, all the DCT coefficients are not equally important in terms of visual perception and their dimension is also not negligible even in Image retrieval process. Later, selected AC coefficients are divided into four different groups. Later, some statistical parameters are computed from each group. Each statistical value is placed at a particular matrix. So, from each group, the number of matrices constructed is equal to the number of statistical parameters evaluated and one more matrix for DC coefficients is considered. Further, for construction of small dimensional feature vectors, gray level co-occurrence matrix (GLCM) is employed on all constructed matrices to derive the feature vector for a color component. The same procedure is employed on all three components and all feature vectors are combined toaether to form the final feature vector. The proposed CBIR structure is tested on three standard Image database i.e. Corel-lK, GHIM-10K and Olivia database and the experimental results demonstrate satisfactorily image retrieval and performance outperform other state-of-art schemes in many instances with respect to their precision values.

Integer Discrete Cosine Transform (DCT) reduces hardware complexity by eliminating floating point multiplication. Multiplier less multiple constant multiplication (MCM) is used to further optimize integer multiplication by replacing it with shifters and adders. As N-point DCT takes 25% of hardware complexity in high efficiency video coding (HEVC), further optimizing DCT in terms speed and power remains critical. Lately, an alternate real-valued DCT coefficients were proposed which reduced the amount of scaling used in Integer DCT coefficients. It achieved the low dynamic range, high speed and low power at same degree of approximation for DCT coefficients. In this paper, an effort is made to further approximate real-valued DCT coefficients of N-point DCT so that critical path due to MCM is reduced. Proposed approximate real-valued DCT coefficients has relatively good PSNR with optimized hardware compared to existing real-valued DCT coefficients. FPGA implementation of 1D-DCT architecture for 32-point DCT with approximate real-valued coefficients shows the reduction of 35% and 24% in area-delay product and power respectively.

This paper presents an efficient image cipher based on applying the chaotic Baker Map (BM) in the Discrete Cosine Transform (DCT). The encryption module of the proposed DCT-based BM image cipher employs a DCT on the original plain-image then, the DCT coefficients of the plain-image are shuffled with the BM. Finally, the inverse DCT is applied to the shuffled plain-image DCT coefficients to obtain the final cipher-image. The decryption module of the proposed DCT-based BM image cipher employs a DCT on the input cipher-image then, the DCT coefficients of the cipher-image are inversely shuffled with the BM. Finally, the inverse DCT is applied to the inversely shuffled cipher-image DCT coefficients to obtain the original plain-image. A set of experimental tests are performed to test the validity of the proposed DCT-based BM image cipher and the performed tests demonstrated the superiority of the proposed DCT-based BM image cipher in terms of statistical, differential, sensitivity and noise immunity.

-With developing of computer networks and digital techniques, the electronic image are easily created, edited, reproduced and distributed. Unfortunately, illegal copy and malicious tamper are also facilitated. At present, fragile watermark is researched greatly to authenticate the veracity and integrity of electronic contents. In this paper, a chaotic watermarking scheme for authentication of popular JPEG images is proposed. The quantized DCT ( Discrete Cosine Transform ) coefficients after entropy decoding are mapped to the initial values of the chaotic system, then the generated watermark information by chaotic iteration is embedded into JPEG compressed domain. Thanks to the high sensitivity on initial values of the chaotic mapping, the very accurate localization is realized for the malicious tampers to JPEG images. Because we directly modify the DCT coefficients after quantization for embedding the watermark, the proposed method can prevent the invalidation of tamper detection by JPEG re-quantization. Furthermore, because the proposed scheme avoids a large of computation on full decoding and re-encoding process, the low complexity and a high extracting speed are obtained. Simulation results show the proposed scheme can directly localize the tampers happened on the watermarked JPEG images. Furthermore, the ability of tamper localization is very sensitivity. So the proposed scheme is very fit for the integrity authentication of the electronic image in Internet.

An outdoor time scenes simulation scheme based on support vector regression with radial basis function on DCT domain