We have proposed a novel concept of a digital watermarking technique for music data that focuses on the use of sound synthesis and sound effect techniques. This paper describes the details of our proposed technique that employs the distortion effect, one of the most common sound effects frequently utilized especially for guitar and bass instruments. This paper describes the experimental results of evaluating the resistance of the proposed technique against some basic malicious attacks utilizing MP3 coding, tempo alteration, pitch alteration, and high-pass filtering. It is demonstrated that the proposed technique potentially has appropriate resistance against such attacks except for the high-pass filtering attack. A technique for increasing the resistance against the high-pass filtering attack is also supplementarily discussed.

We normally hold a lot of confidential information in hard disk drives and solid-state drives. When we want to erase such information to prevent the leakage, we have to overwrite the sequence of information with a sequence of symbols independent of the information. The overwriting is needed only at places where overwritten symbols are different from original symbols. Then, the cost of overwrites such as the number of overwritten symbols to erase information is important. In this paper, we clarify the minimum cost such as the minimum number of overwrites to erase information under weak and strong independence criteria. The former (resp. the latter) criterion represents that the mutual information between the original sequence and the overwritten sequence normalized (resp. not normalized) by the length of the sequences is less than a given desired value.

In the successive refinement problem, a fixed-length sequence emitted from an information source is encoded into two codewords by two encoders in order to give two reconstructions of the sequence. One of two reconstructions is obtained by one of two codewords, and the other reconstruction is obtained by all two codewords. For this coding problem, we give non-asymptotic inner and outer bounds on pairs of numbers of codewords of two encoders such that each probability that a distortion exceeds a given distortion level is less than a given probability level. We also give a general formula for the rate-distortion region for general sources, where the rate-distortion region is the set of rate pairs of two encoders such that each maximum value of possible distortions is less than a given distortion level.

Image quality assessment (IQA) is an inherent problem in the field of image processing. Recently, deep learning-based image quality assessment has attracted increased attention, owing to its high prediction accuracy. In this paper, we propose a fully-blind and fast image quality predictor (FFIQP) using convolutional neural networks including two strategies. First, we propose a distortion clustering strategy based on the distribution function of intermediate-layer results in the convolutional neural network (CNN) to make IQA fully blind. Second, by analyzing the relationship between image saliency information and CNN prediction error, we utilize a pre-saliency map to skip the non-salient patches for IQA acceleration. Experimental results verify that our method can achieve the high accuracy (0.978) with subjective quality scores, outperforming existing IQA methods. Moreover, the proposed method is highly computationally appealing, achieving flexible complexity performance by assigning different thresholds in the saliency map.

This letter presents numerical results of lossy source coding for non-uniformly distributed binary source with trellis codes. The results show how the performance of trellis codes approaches the rate-distortion function in terms of the number of states.

This paper proposes a method for reducing the peak-to-average power ratio (PAPR) at the output signal of a digital predistortion linearizer (DPDL) that compensates for frequency dependent intermodulation distortion (IMD) components. The proposed method controls the amplitude and phase values of the frequency components corresponding to the transmission bandwidth of the output signal. A DPDL employing the proposed method simultaneously provides IMD component cancellation of out-of-band components and PAPR reduction at the output signal. This paper identifies the amplitude and phase conditions to minimize the PAPR. Experimental results based on a 2-GHz band 1-W class power amplifier show that the proposed method improves the drain efficiency of the power amplifier when degradation is allowed in the error vector magnitude. To the best knowledge of the authors, this is the first PAPR reduction method for DPDL that reduces the PAPR while simultaneously compensating for IMD components.

For mobile video codecs, the huge energy dissipation for external memory traffic is a critical challenge under the battery power constraint. Lossy embedded compression (EC), as a solution to this challenge, is considered in this paper. While previous studies in lossy EC mostly focused on algorithm optimization to reduce distortion, this work, to the best of our knowledge, is the first one that addresses the distortion control. Firstly, from both theoretical analysis and experiments for distortion optimization, a conclusion is drawn that, at the frame level, allocating memory traffic evenly is a reliable approximation to the optimal solution to minimize quality loss. Then, to reduce the complexity of decoding twice, the distortion between two sequences is estimated by a linear function of that calculated within one sequence. Finally, on the basis of even allocation, the distortion control is proposed to determine the amount of memory traffic according to a given distortion limitation. With the adaptive target setting and estimating function updating in each group of pictures (GOP), the scene change in video stream is supported without adding a detector or retraining process. From experimental results, the proposed distortion control is able to accurately fix the quality loss to the target. Compared to the baseline of negative feedback on non-referred B frames, it achieves about twice memory traffic reduction.

In this study, an anonymization infrastructure for the secondary use of data is proposed. The proposed infrastructure can publish data that includes privacy information while preserving the privacy by using anonymization techniques. The infrastructure considers a situation where ill-motivated users redistribute the data without authorization. Therefore, we propose a watermarking method for anonymized data to solve this problem. The proposed method is implemented, and the proposed method's tolerance against attacks is evaluated.

Distributed compressive video sensing (DCVS) is a new paradigm for low-complexity video compression. To achieve the highest possible perceptual coding performance under the measurements budget constraint, we propose a perceptual optimized DCVS codec by jointly exploiting the reweighted sampling and rate-distortion optimized measurements allocation technologies. A visual saliency modulated just-noticeable distortion (VS-JND) profile is first developed based on the side information (SI) at the decoder side. Then the estimated correlation noise (CN) between each non-key frame and its SI is suppressed by the VS-JND. Subsequently, the suppressed CN is utilized to determine the weighting matrix for the reweighted sampling as well as to design a perceptual rate-distortion optimization model to calculate the optimal measurements allocation for each non-key frame. Experimental results indicate that the proposed DCVS codec outperforms the other existing DCVS codecs in term of both the objective and subjective performance.

In this paper, we deal with the fixed-length lossy compression, where a fixed-length sequence emitted from the information source is encoded into a codeword, and the source sequence is reproduced from the codeword with a certain distortion. We give lower and upper bounds on the minimum number of codewords such that the probability of exceeding a given distortion level is less than a given probability. These bounds are characterized by using the α-mutual information of order infinity. Further, for i.i.d. binary sources, we provide numerical examples of tight upper bounds which are computable in polynomial time in the blocklength.

In this paper, we propose an improved method of embedding and detecting data in a printed image using a camera of a mobile device. The proposed method is based on the data diffusion method. We discuss several problems in the conventional lens distortion correction method. In addition, the possibility of using multiple captured images by employing a motion-image-capturing technique is also examined. A method of selecting captured images that are expected to obtain a high detection rate is also proposed. From the experimental results, it is shown that the proposed method is effective for improving data detection.

This paper presents a wideband digital predistortion (DPD) architecture suitable for wideband wireless systems, such as IEEE 802.11ad/WiGig, where low oversampling ratio of the digital-to-analog converter (DAC) is a bottleneck for available linearization bandwidth. In order to overcome the bandwidth limitation in the conventional DPD, the proposed DPD introduces a complex coefficient filter in the DPD signal processing, which enables it to achieve asymmetric linearization. This approach effectively suppresses one side of adjacent channel leakages with twice the bandwidth as compared to the conventional DPD. The concept is verified through system simulation and measurements. Using a scaled model of a 2 GHz RF carrier frequency, the measurement shows a 4.2 dB advantage over the conventional DPD in terms of adjacent channel leakage.

Distributed compressive video sensing (DCVS) is an emerging low-complexity video coding framework which integrates the merits of distributed video coding (DVC) and compressive sensing (CS). In this paper, we propose a novel rate-distortion optimized DCVS codec, which takes advantage of a rate-distortion optimization (RDO) model based on the estimated correlation noise (CN) between a non-key frame and its side information (SI) to determine the optimal measurements allocation for the non-key frame. Because the actual CN can be more accurately recovered by our DCVS codec, it leads to more faithful reconstruction of the non-key frames by adding the recovered CN to the SI. The experimental results reveal that our DCVS codec significantly outperforms the legacy DCVS codecs in terms of both objective and subjective performance.

Radio frequency over fiber (RoF) advanced technology is already integrated into current 3G and 4G radio access networks in which the digital unit and remote radio head equipped with nonlinear high power amplifiers (HPAs) are connected through the RoF-based fronthaul links. In this study, we investigated the degradation in the adjacent channel leakage ratio (ACLR) of equipment with the adaptive linearizer RF HPA when both the direct and feedback paths of the transmitting system include RoF links. We show that an ACLR exceeding -57dBc @ 5-MHz offset, which completely satisfies the requirements of the 3GPP technical specifications, can be achieved for a 20-W-class Doherty power amplifier linearized through commercial RoF links. Experiments showed that the achieved ACLR strongly depends on the RoF-link noise figure and that most of the nonlinear distortions caused by RoF can be completely suppressed with the proposed joint linearization approach for simultaneous linearization of RoF and HPA nonlinearities with a single common “joint” linearizer. Experimental results confirm significant ACLR performance enhancements as a result of RoF noise floor reduction, which is achieved under RoF driving conditions optimized together with joint RoF and HPA linearization. Our joint linearization approach via RoF links is confirmed to be applicable for next-generation mobile fronthaul architectures.

Radio over Fiber (RoF) is a promising solution for providing wireless access services. Heterogeneous radio signals are transferred via an optical fiber link using an analog transmission technique. When the RoF and the radio frequency (RF) devices have a nonlinear characteristic, these will create the intermodulation products (IMPs) in the system and generate the intermodulation distortion (IMD). In this paper, the IMD interference in the uplink RF signals from the coupling effect between the downlink and the uplink antennas has been addressed. We propose a method using the dynamic channel allocation (DCA) algorithm with the predistortion (PD) technique to improve the throughput performance of the multi-channel RoF system. The carrier to distortion plus noise power ratio (CDNR) is evaluated for all channel allocation combinations; then the best channel combination is assigned as a set of active channels to minimize the effect of IMD. The results show that the DCA with PD has the lowest IMD and obtains a better throughput performance.

Analog and digital collaborative design techniques for wireless SoCs are reviewed in this paper. In wireless SoCs, delicate analog performance such as sensitivity of the receiver is easily degraded due to interferences from digital circuit blocks. On the other hand, an analog performance such as distortion is strongly compensated by digital assist techniques with low power consumption. In this paper, a sensitivity recovery technique using the analog and digital collaborative design, and digital assist techniques to achieve low-power and high-performance analog circuits are presented. Such analog and digital collaborative design is indispensable for wireless SoCs.

Explicit evaluation of the rate-distortion function has rarely been achieved when it is strictly greater than its Shannon lower bound since it requires to identify the support of the optimal reconstruction distribution. In this paper, we consider the rate-distortion function for the distortion measure defined by an ε-insensitive loss function. We first present the Shannon lower bound applicable to any source distribution with finite differential entropy. Then, focusing on the Laplacian and Gaussian sources, we prove that the rate-distortion functions of these sources are strictly greater than their Shannon lower bounds and obtain upper bounds for the rate-distortion functions. Small distortion limit and numerical evaluation of the bounds suggest that the Shannon lower bound provides a good approximation to the rate-distortion function for the ε-insensitive distortion measure. By using the derived bounds, we examine the performance of a scalar quantizer. Furthermore, we discuss variants and extensions of the ε-insensitive distortion measure and obtain lower and upper bounds for the rate-distortion function.

We consider the distributed source coding system of two correlated Gaussian Vector sources Yl=t(Yl1, Yl2),l=1,2 which are noisy observations of correlated Gaussian scalar source X0. We assume that for each (l,k)∈{1,2}, Ylk is an observation of the source X0, having the form Ylk=X0+Nlk, where Nlk is a Gaussian random variable independent of X0. We further assume that Nlk, (l,k)∈{1,2}2 are independent. In this system two correlated Gaussian observations are separately compressed by two encoders and sent to the information processing center. We study the remote source coding problem where the decoder at the center attempts to reconstruct the remote source X0. The determination problem of the rate distortion region for this communication system can be regarded as an extension of the Gaussian CEO problem to the case of vector observations. For each vector observation we can obtain an estimation on X0 from this observation. Those estimations are sufficient statistics on X0. Using those sufficient statistics, we determine the rate distortion region by showing that it coincides with the rate distortion region of the CEO problem where the scalar observations of X0 are equal to the estimations computed from the vector observations. We further extend the result to the case of L terminal and general vector observations.

Recently, cameras are equipped on cars in order to assist their drivers. These cameras often have a severe radial distortion because of their wide view angle, and sometimes it is necessary to compensate it in a fully automatic way in the field. We have proposed such a method, which uses the entropy of the histogram of oriented gradient (HOG) to evaluate the goodness of the compensation. Its performance was satisfactory, but the computational burden was too heavy to be executed by drive assistance devices. In this report, we discuss a method to speed up the algorithm, and obtain a new light algorithm feasible for such devices. We also show more comprehensive performance evaluation results then those in the previous reports.

Barrel distortion is a critical problem that can hinder the successful application of wide-angle cameras. This letter presents an implementation method for fast correction of the barrel distortion. In the proposed method, the required scaling factor is obtained by interpolating a mapping polynomial with a non-uniform spline instead of calculating it directly, which reduces the number of computations required for the distortion correction. This reduction in the number of computations leads to faster correction while maintaining quality: when compared to the conventional method, the reduction ratio of the correction time is about 89%, and the correction quality is 35.3 dB in terms of the average peak signal-to-noise ratio.