Discrete Cosine Transform Domain Research Articles

Efficient multi-level security for robust 3D color-plus-depth HEVC

This paper presents two robust hybrid watermarking techniques for securing the Three-Dimensional High Efficiency Video Coding (3D-HEVC). The first watermarking technique is the homomorphic-transform-based Singular Value Decomposition (SVD) in Discrete Wavelet Transform (DWT) domain. The second watermarking technique is the three-level Discrete Stationary Wavelet Transform (DSWT) in Discrete Cosine Transform (DCT) domain. The objective of the two proposed hybrid watermarking techniques is to increase the immunity of the watermarked 3D-HEVC streams to attacks. Also, we propose a wavelet-based fusion technique to combine two depth watermark frames into one fused depth watermark frame. Then, the resultant fused depth watermark is encrypted using chaotic Baker map to increase the level of security. After that, the resultant chaotic encrypted fused depth watermark is embedded in the 3D-HEVC color frames using the proposed hybrid watermarking techniques to produce the watermarked 3D-HEVC streams. In addition to achieving multi-level security in the transmitted 3D-HEVC streams, the proposed hybrid techniques reduce the required bit rate for transmitting the color-plus-depth 3D-HEVC data over limited-bandwidth networks. The performance of the proposed hybrid techniques is compared with those of the state-of-the-art techniques. Extensive simulation results on standard 3D video sequences have been conducted in the presence of attacks. The obtained results confirm that the proposed hybrid fusion-encryption-watermarking techniques achieve not only a good perceptual quality with high Peak Signal-to-Noise Ratio (PSNR) values and less bit rate, but also high correlation coefficient values between the original and extracted watermarks in the presence of attacks. Furthermore, the proposed hybrid techniques improve the capacity of information embedding and the robustness without affecting the perceptual quality of the original 3D-HEVC frames. Indeed, the extraction of the encrypted, fused, primary, and secondary depth watermark frames is possible in the presence of attacks.

Robust Template-Based Watermarking for DIBR 3D Images

Several depth image-based rendering (DIBR) watermarking methods have been proposed, but they have various drawbacks, such as non-blindness, low imperceptibility and vulnerability to signal or geometric distortion. This paper proposes a template-based DIBR watermarking method that overcomes the drawbacks of previous methods. The proposed method exploits two properties to resist DIBR attacks: the pixel is only moved horizontally by DIBR, and the smaller block is not distorted by DIBR. The one-dimensional (1D) discrete cosine transform (DCT) and curvelet domains are adopted to utilize these two properties. A template is inserted in the curvelet domain to restore the synchronization error caused by geometric distortion. A watermark is inserted in the 1D DCT domain to insert and detect a message from the DIBR image. Experimental results of the proposed method show high imperceptibility and robustness to various attacks, such as signal and geometric distortions. The proposed method is also robust to DIBR distortion and DIBR configuration adjustment, such as depth image preprocessing and baseline distance adjustment.

Efficient JPEG Steganography Using Domain Transformation of Embedding Entropy

Nowadays, JPEG steganographic schemes, e.g., J-UNIWARD, which take into account the effects of embedding in the spatial domain tend to exhibit higher security and introduce less artifacts that can be captured by the prevalent steganalyzers. Following the paradigm, this letter proposes a new design of the distortion measure for JPEG steganography by incorporating the statistics of both the spatial and discrete cosine transform (DCT) domains. The spatial statistics of the decompressed JPEG images are first well characterized with distortion measures of some efficient steganographic schemes in the spatial domain, e.g., HILL, and the resulting embedding entropies of spatial blocks in alignment with DCT blocks are then transformed into the DCT domain to obtain the distortion measures for JPEG steganography. Experimental results show that the proposed method outperforms considerably other state-of-the-art JPEG steganographic schemes, i.e., J-UNIWARD and UERD, for the most effective feature set GFR at present, and rivals them for other feature sets, e.g., DCTR and CC-JRM.

Preserve Imperceptibility and Robustness Performance on Steganography Technique based on StegaSVM-Shifted LBS Model

In image steganography, the most popular and widely used techniques is the least significant bit (LSB) that hide data into a cover-image in a spatial and discrete cosine transform (DCT) domain as well. Beside the LSB technique, there is other technique that is also influential i.e support vector machine (SVM) normally used to strengthen the embedding algorithm. Whatever techniques used in the image steganography field, the main purpose is to keep the existence of the secret-message secret. This paper designing the new model is proposed called StegaSVM-Shifted LSB model in DCT domain to preserve the imperceptibility and increase the robustness of stego-images. The StegaSVM-Shifted LSB model that has been proposed that utilize HVS and embedding technique through Shifted LSB showed a good performance.

Weak GPS signal acquisition method based on DBZP

Double block zero padding (DBZP) is a widely used but costly method for weak global positioning system (GPS) signal acquisition in software receivers. To improve the computational efficiency, this paper proposes an algorithm based on the differential DBZP algorithm and the discrete cosine transform (DCT) domain filtering method. The proposed method involves using a differential correlator after the DBZP operation. Subsequently, DCT domain low pass filtering (LPF) and inverse DCT (IDCT) reconstruction are carried out to improve the signal to noise ratio (SNR). The theoretical analysis and simulation results show that the detection algorithm can effectively improve the SNR of the acquired signal and increase the probability of detection under the same false alarm probability.

Robust hybrid watermarking techniques for different color imaging systems

Digital watermarking is an efficient and promising mechanism for protecting the copyright of the transmitted multimedia information. Thus, this paper presents two robust hybrid color image watermarking techniques. The objective of the proposed watermarking techniques is to increase the immunity of the watermarked color images against attacks and to achieve adequate perceptual quality. The first proposed hybrid technique is the homomorphic transform based Singular Value Decomposition (SVD) in Discrete Wavelet Transform (DWT) domain. Firstly, the DWT is employed to divide an image into non-overlapping bands. Then, the reflectance components of the LL sub-bands are extracted using the homomorphic transform of each of the RGB (Red, Green, and Blue) color image components. After that, the watermark is embedded by applying the SVD on these reflectance components. The second proposed hybrid technique is the three-level Discrete Stationary Wavelet Transform (DSWT) in Discrete Cosine Transform (DCT) domain. In this technique, the RGB components of the host color image are separated, and then the DCT is applied on each separated color component. The three-level DSWT is employed to divide the DCT components into four sub-bands. These sub-bands are the A, H, V, and D matrices, which have the same host image size. The watermark image is then embedded into the determined matrix A. The two proposed hybrid watermarking techniques are compared with the current state-of-the-art techniques. This paper also presents a comparative study of the proposed techniques for different color imaging systems to determine their robustness and stability. The comparisons are based on the subjective visual results to detect any degradation in the watermarked image in addition to the objective results of the Peak Signal-to-Noise Ratio (PSNR) of the watermarked image, and the Normalized Correlation (NC) of the extracted watermark to test and evaluate the performance efficiency of the proposed watermarking techniques. Extensive experimental results show that the proposed hybrid watermarking techniques are both robust and have adequate immunity against different types of attacks compared to the traditional watermarking techniques. They achieve not only very good perceptual quality with appreciated PSNR values, but also high correlation coefficient values in the presence of different multimedia attacks.

A time-efficient optimization for robust image watermarking using machine learning

Watermarking is utilized for securing multimedia data exchange. The techniques used to embed a watermark typically require optimizing scheme parameters often through applying meta-heuristic optimization techniques. Although meta-heuristic techniques have been widely used due to their performance enhancing capability, they are not suitable for time sensitive applications due to their large time consumption. In this paper, a time-efficient optimization based on machine learning is proposed to find the best embedding strength parameter for robust image watermarking in terms of both the imperceptibility and robustness. First, a watermark embedding scheme is designed in the Discrete Cosine Transform domain, which provide a proper robustness against common watermarking attacks. Then, a training process is performed through selecting set of images upon which the watermarking is applied and optimized using the Artificial Bee Colony algorithm. Observation data is collected, which includes the optimum strength values along with the feature vectors that represent the training images. The features, of an image, are extracted by calculating the optimization fitness function at different values of the embedding strength. Finally, new set of images are chosen to be watermarked using the optimum embedding parameters that are predicted through the K-Nearest Neighborhood regression method. Experimental results show that the proposed method consumes considerably less time to evaluate the optimum solutions compared to using meta-heuristic optimization. Meanwhile, the error between the optimum and predicted optimum solutions has negligible impact on the optimization objectives.

Color image interpolation in the DCT domain using a wavelet-based differential value

We propose a new image-interpolation technique using a combination of an adaptive directional wavelet transform (ADWT) and discrete cosine transform (DCT). In the proposed method, we use ADWT to decompose the low-resolution image into different frequency subband images. The high-frequency subband images are further transformed to DCT coefficients, and the zero-padding method is used for interpolation. Simultaneously, the low-frequency subband image is replaced by the original low-resolution image. Finally, we generate the interpolated image by combining the original low-resoultion image and the interpolated subband images by using inverse DWT. Experimental results demonstrate that the proposed algorithm yields better quality images in terms of subjective and objective quality metrics compared to the other methods considered in this paper.

Gray-scale image watermarking based on DE-KELM in DCT domain

A semi-blind discrete cosine transform (DCT) domain watermarking technique for gray-scale images using differential evolution (DE) and kernel extreme learning machine (KELM) has been presented in this paper. The selection of m×m sized blocks (non-overlapping) is done with the help of entropy. It gives the degree of randomness of the sub blocks. DCT for the selected blocks is carried out, following which the low frequency coefficients are selected in zig-zag manner from each block. The coefficients from each block form the dataset of input vectors and target vector for KELM which uses the non-linear regression model to predict the coefficient where the watermark bit is to be embedded for each block. DE is used for obtaining the optimal scaling factors and controls the strength of the watermark. Use of multiple scaling factors helps in better optimization as it uses the local information like tolerance and noise sensitivity to determine the strength of watermark bit in each block. The watermarking scheme shows robustness against numerous attacks like JPEG compression, Weiner filtering, median filtering, average filtering, Gaussian filtering, histogram equalization, etc. as well as the watermarked image retains its quality and is not compromised. Hence, the proposed technique is good candidate for watermarking.

A robust and blind image watermarking scheme in DCT domain

In this paper, the authors have presented a robust and blind watermarking scheme based on discrete cosine transform (DCT) for protecting the copyright ownership of digital images. Initially, the image is decomposed into non-overlapping blocks and subsequently DCT is employed on each block to embed a binary bit of watermark into each transformed block by modifying some middle significant AC coefficients using repetition code. During the embedding phase of the proposed method, DC and some higher AC coefficients are kept intact after zigzag scanning of each DCT block to ensure the high visual quality of watermarked image. This scheme is suitable to protect the copyright information even in compressed form of the watermarked image since it exploits middle bands of DCT coefficients for embedding the watermark bits. The proposed scheme is also tested to verify the withstand capability against several image processing attacks and satisfactory results are achieved.

A robust reversible image watermarking scheme in DCT domain using Arnold scrambling and histogram modification

Among the various watermarking schemes, the reversible watermarking scheme has drawn extensive attention in the recent years for its application in sensitive issues like medical, military and typical law-enforcement images. Cover image dependent embedding capacity and lack of robustness are the most crucial concerns of the reversible watermarking methods. To overcome these issues, a discrete cosine transform (DCT) and histogram shifting based robust reversible image watermarking scheme using Arnold scrambling is presented in this paper. Initially, the image is decomposed into non-overlapping blocks and consequently DCT are applied to each block to embed a binary bit of watermark into each transformed block by modifying one pair of middle significant AC coefficients. In this initial step, location map is also generated for the cover image restoration purpose in the extracting side. Then, this location map is embedded in the cover image using histogram modification technique. In the receiver side, at first location map is generated from an image using histogram modification method and watermark is recovered from the corresponding image. Using location map reversible image is reversed in the following extracting phase of the proposed method. The proposed reversible watermarking scheme has also been experimented to verify the robustness property against several image processing attacks and satisfactory results are achieved.

A robust reversible image watermarking scheme in DCT domain using Arnold scrambling and histogram modification

Among the various watermarking schemes, the reversible watermarking scheme has drawn extensive attention in the recent years for its application in sensitive issues like medical, military and typical law-enforcement images. Cover image dependent embedding capacity and lack of robustness are the most crucial concerns of the reversible watermarking methods. To overcome these issues, a discrete cosine transform (DCT) and histogram shifting based robust reversible image watermarking scheme using Arnold scrambling is presented in this paper. Initially, the image is decomposed into non-overlapping blocks and consequently DCT are applied to each block to embed a binary bit of watermark into each transformed block by modifying one pair of middle significant AC coefficients. In this initial step, location map is also generated for the cover image restoration purpose in the extracting side. Then, this location map is embedded in the cover image using histogram modification technique. In the receiver side, at first location map is generated from an image using histogram modification method and watermark is recovered from the corresponding image. Using location map reversible image is reversed in the following extracting phase of the proposed method. The proposed reversible watermarking scheme has also been experimented to verify the robustness property against several image processing attacks and satisfactory results are achieved.

Prediction of Compression Ratio for DCT-Based Coders With Application to Remote Sensing Images

A problem of predicting compression ratio (CR) for lossy image compression methods based on discrete cosine transform (DCT) is considered for remote sensing imaging as a main target application. We demonstrate that the noise presence in images leads to specific requirements to lossy image compression as well as to criteria used, and ways to meet these requirements. In particular, it is often desired to compress images in the neighborhood of optimal operation point (OOP) where a compressed image might be closer to the corresponding noise-free one compared to noisy (original, uncompressed) counterpart. In this paper, first, we consider a problem of predicting CR for compressing noisy images in OOP neighborhood. Several statistical parameters calculated in DCT domain in 8 × 8 pixel blocks are used for this. The factors that influence a prediction accuracy and the ways to improve this accuracy are discussed. Next, we show that there is a statistical parameter that does not require any a priori information on noise properties, and that can be used to predict CR with a high accuracy without any necessity to apply multiple image compression/decompression procedures. The proposed methods are thoroughly tested for two DCT-based image coders applied to component-wise lossy compression of hyperspectral data. Finally, a modification of the prediction approach for 3-D compression of multichannel images is proposed.

Secure Image-Authentication Schemes With Hidden Double Random-Phase Encoding

We present a new image-authentication algorithm based on binary-quantified double random-phase encoding (DRPE) and a discrete cosine transformation (DCT) domain watermarking scheme. The image is encrypted using a DRPE scheme, in which only the phase part of the encoded image is preserved. Then, this phase image is quantified to become a binary image by giving 0 to these phase values that are less than 0 and setting others to 1. Then, the quantified binary image is secretly inserted into a host image with a DCT-domain watermarking algorithm. During image authentication, the receiver gets the binary image from the watermarked image using an inverse DCT operation and codes 0 values as $-\pi $ and values of 1 as $\pi $ to create a phase image. Finally, the input image is decoded from the retrieved phase image based on a double random phase decryption technique and is further authenticated using a nonlinear cross-correlation method. The present image-authentication algorithm offers an additional layer of system security because the hidden binary image reveals no information that is from the original image. Moreover, the image decrypted from the retrieved phase image cannot be easily recognized with naked eyes. However, it can be successfully authenticated by nonlinear cross-correlation, even in the face of attacks including noise attacks, filtering attacks, partial occlusion attacks, or geometric transformation attacks to the watermarked image. Our simulation results demonstrated the capability of the proposed image-authentication technique.

A Psychoacoustic-Based Multiple Audio Object Coding Approach via Intra-Object Sparsity

Rendering spatial sound scenes via audio objects has become popular in recent years, since it can provide more flexibility for different auditory scenarios, such as 3D movies, spatial audio communication and virtual classrooms. To facilitate high-quality bitrate-efficient distribution for spatial audio objects, an encoding scheme based on intra-object sparsity (approximate k-sparsity of the audio object itself) is proposed in this paper. The statistical analysis is presented to validate the notion that the audio object has a stronger sparseness in the Modified Discrete Cosine Transform (MDCT) domain than in the Short Time Fourier Transform (STFT) domain. By exploiting intra-object sparsity in the MDCT domain, multiple simultaneously occurring audio objects are compressed into a mono downmix signal with side information. To ensure a balanced perception quality of audio objects, a Psychoacoustic-based time-frequency instants sorting algorithm and an energy equalized Number of Preserved Time-Frequency Bins (NPTF) allocation strategy are proposed, which are employed in the underlying compression framework. The downmix signal can be further encoded via Scalar Quantized Vector Huffman Coding (SQVH) technique at a desirable bitrate, and the side information is transmitted in a lossless manner. Both objective and subjective evaluations show that the proposed encoding scheme outperforms the Sparsity Analysis (SPA) approach and Spatial Audio Object Coding (SAOC) in cases where eight objects were jointly encoded.

Visual fidelity without sacrificing capacity: an adaptive Laplacian pyramid approach to information hiding

This paper investigates the improvements in hiding capacity and perceptibility of image-based steganography using a hiding scheme which utilizes a multiscale Laplacian pyramid of the cover image and the discrete cosine transform (DCT). The proposed methodology allows for an enhanced visual quality of the resulting stego image, while allowing for very high embedding payload capacities, which improves security by reducing an eavesdropper’s ability to detect and successively extract or change the hidden information. The basic idea is to hide the secret data in the DCT of the lowest level of the Laplacian pyramid of the cover image. This scheme employs a curve-fitting adaptive region approach in the DCT domain for enhanced visual fidelity as well as very high capacities as compared to competing methods. This paper also compares the embedding capacities of various steganography schemes that have been recently published in the literature. Experimental results confirm that the proposed hiding scheme can maintain consistently high stego image quality, in comparison to other spatial and frequency-domain schemes, when hiding at extremely high payload capacities.

A Novel Similarity Measure for Content Based Image Retrieval in Discrete Cosine Transform Domain

A Novel Similarity Measure for Content Based Image Retrieval in Discrete Cosine Transform Domain

Approach to Detecting Forest Fire by Image Processing Captured from IP Cameras

In this paper, the results show an algorithm to detect the presence of smoke and flame using image sequences captured by Internet Protocol (IP) cameras is represented. The important characteristics of smoke such as color, motion and growth properties are employed to detect fire. For the efficient smoke and fire detection in the captured images by the IP camera, a detection algorithm must operate directly in the Discrete Cosine Transform (DCT) domain to reduce computational weigh, avoiding a complete decoding process required for algorithms that operate in spatial domain. In order to assess the possibility and the accuracy of proposed algorithm, the author used the video sequences which are captured by IP camera from control forest fire at different spatial location and levels of fire intensity. Evaluation results illustrated the efficiency of the proposed algorithm in effectively detecting forest fires with accuracy at 97%.

Approach to Detecting Forest Fire by Image Processing Captured from IP Cameras

In this paper, the results show an algorithm to detect the presence of smoke and flame using image sequences captured by Internet Protocol (IP) cameras is represented. The important characteristics of smoke such as color, motion and growth properties are employed to detect fire. For the efficient smoke and fire detection in the captured images by the IP camera, a detection algorithm must operate directly in the Discrete Cosine Transform (DCT) domain to reduce computational weigh, avoiding a complete decoding process required for algorithms that operate in spatial domain. In order to assess the possibility and the accuracy of proposed algorithm, the author used the video sequences which are captured by IP camera from control forest fire at different spatial location and levels of fire intensity. Evaluation results illustrated the efficiency of the proposed algorithm in effectively detecting forest fires with accuracy at 97%.

An iterative sinogram gap-filling method with object- and scanner-dedicated discrete cosine transform (DCT)-domain filters for high resolution PET scanners.

We aimed to develop a gap-filling algorithm, in particular the filter mask design method of the algorithm, which optimizes the filter to the imaging object by an adaptive and iterative process, rather than by manual means. Two numerical phantoms (Shepp-Logan and Jaszczak) were used for sinogram generation. The algorithm works iteratively, not only on the gap-filling iteration but also on the mask generation, to identify the object-dedicated low frequency area in the DCT-domain that is to be preserved. We redefine the low frequency preserving region of the filter mask at every gap-filling iteration, and the region verges on the property of the original image in the DCT domain. The previous DCT2 mask for each phantom case had been manually well optimized, and the results show little difference from the reference image and sinogram. We observed little or no difference between the results of the manually optimized DCT2 algorithm and those of the proposed algorithm. The proposed algorithm works well for various types of scanning object and shows results that compare to those of the manually optimized DCT2 algorithm without perfect or full information of the imaging object.