Yosuke Sugiura

SVD based audio watermarking using angle-quantization

This paper presents a new blind audio watermarking scheme based on singular value decomposition (SVD) using Angle-Quantization. Initially, the original audio is divided into some frames and the samples of each frame are arranged into matrix. SVD is applied to the matrix for each frame. Watermark data is embedded into the angle between the largest singular value and the second largest singular value of each diagonal matrix by quantization. Date payload of the proposed scheme is 172.39 bps. Simulation results confirm the inaudibility and higher robustness against various signal processing attacks for the proposed method.

Optimized three scores combination for image quality assessment

Digital images are distorted by a variety of processes. Thus we need objective image quality assessment (IQA) equivalent to subjective assessment. Several objective IQA methods have been proposed, and recently a combination method has been derived successfully. The combination technique is able to assess distorted images correctly. However, it is weak against Meanshift images. In this paper, we propose a new objective IQA method adding another IQA score to the original combination technique. Adjustable parameters included in the new IQA measure are optimized with the genetic algorithm. By experiments, it is validated that the proposed method provides a superior performance on various images including Meanshift.

Iterative extended spectral subtraction for restoration from image degraded by white noise

It is well known that the iterative spectral subtraction (ISS) method is effective to eliminate white noise in speech, the fact that the ISS method is suitable for restoration from image degraded by white noise has been confirmed. In this paper, we presents an image denoising technique in which an iterative extended spectral subtraction (IESS) method is developed. We discuss the factors of the IESS that affect the restoration results, and by setting the best parameters, set out to improve the performance. We compare the performance of the IESS method with that of state of the art filtering approaches in experiments.

Fundamental frequency estimation combining air-conducted speech with bone-conducted speech in noisy environment

Air-conducted speech is currently used for fundamental frequency extraction in noisy environment. However, the results are severely affected by noise. In this paper, additionally bone-conducted speech is combined with air-conducted speech and a novel pitch extraction method is derived. Experiments indicate that the proposed method provides an accurate estimate of fundamental frequency of speech in highly noisy environment.

Narrowband interference suppression with symbol interleaving for UWB communication systems

In this paper, we propose a new method for mitigating narrowband interference in Ultra-WideBand (UWB) communication systems based on Orthogonal Frequency Division Multiplexing (OFDM). Spreading data symbols to some subcarriers, the interference is effectively mitigated. However, the range to be spread for the interference is limited in conventional methods. In the proposed method, we widen more the range of the interference spread by applying symbol interleaving and deinterleaving techniques. We can obtain better Bit Error Rate (BER) performance with the proposed method. Combining the proposed method with spectral shaping, a further improved BER performance is obtained.