Earticle

The quantity of digital image is huge. Undoubtedly, it will be a huge project to complete the image processing in a limited time, and it is unrealistic to directly deal with the real-time image signal with the Discrete Fourier Transform (DFT) algorithm. There is no fundamentally change until Cooley and Tukey proposed a Fast Fourier Transform Algorithm (FFT) and it will greatly promote the application of Discrete Fourier Transform in all aspects. The following will show its superiority from the detailed study of the FFT algorithm and accordingly make the further improvement to the algorithm to improve the use efficiency of the FFT algorithm.

At present, greatest outdoor video-surveillance, optical remote sensing systems and driver-assistance have been designed to work under decent visibility weather conditions. Less visibility often happens weather of hazy or foggy conditions and can strongly influence accuracy or even general functionality of such vision systems. Fog reduces the visibility of a scene and thus the performance of numerous algorithms of computer vision which use feature knowledge. Fog formation is the function of the depth. Estimation of depth knowledge is under constraint problem if single image is presented. Hence, fog removal need assumptions or prior information. In this paper, present a novel algorithm for fog or haze removal purpose with combination of edge enhancement method, color enhancement method, adjustable empirical function and also Wiener filter for efficient outcomes.

Developing a variational model that is capable of restoring both smooth (no edges) and non-smooth (with edges) images is still a valid challenge at the image processing. In this paper, we present two methods for image denoising problems based on the use of the LLT model (see [14]) and TV model (see [20]). The idea of our methods is, add the texture which is separated from the cartoon and noisy, back to the original noisy image or the texture plus noisy part, and the sum then processed. In order to obtain the texture, we first separate texture plus noise from cartoon by LLT model, and then use TV model to remove some noisy from texture. Numerical experiments show our method is able to maintain some important information such as small details in the image, and at the same time to get a better visualization.

A scheme of wireless real video transmission with optimized Quality-of-service is proposed in this paper. It combines H.264 video compression technology with Bluetooth technology to reduce demand of bandwidth and power consumption. Resource manager (RM) is used to smooth video output traffic and to partially eliminate peak of video stream transmitted in Bluetooth channel. The RM monitors status of video transmitters, manipulates and coordinates the being encoded video, and adopts traffic credits to support real-time video services. Measured results show that a maximal speed of transmission can be achieved with a best suitable ACL packets type, rather than the maximum payload packet, according to SNR to achieve. The system can support real-time video transmission with good quality. And more, it can be realized easily in mobile application for its good transportability and robustness.

Due to powerful computers and advanced photo-editing software tools the manipulation of images has become an easy task. Confirming the authenticity of images and detecting tampered regions in an image without any knowledge about the image content is an important part of the research field. An effort is made to survey the recent advancements being made in the field of digital image forgery detection and thus passive methods for forgery detection are being presented. Blind or passive methods do not require any explicit former information about the image. In the first part, various image forgery detection techniques are classified and then an overview of passive image authentication is presented and the existing blind forgery detection techniques are reviewed

The average symbol error probability (ASEP) and outage probability (OP) performance of the switched diversity combining (SDC) system over N-Nakagami fading channels is investigated in this paper. The probability density function (PDF) of the signal-to-noise ratio (SNR) is used to derive exact and approximate ASEP expressions for phase shift keying (PSK) and pulse amplitude modulation (PAM). Exact closed-form expressions for OP of the SDC system are also presented. The ASEP and OP performance under different conditions is evaluated through numerical simulation to verify the analysis. Results are presented which show that the performance of the SDC system is improved when the number of diversity branches and the fading coefficient is increased, but is degraded as the number of cascaded components is increased.

This paper compares the standard Bilateral Filter and its variants such as Modified Bilateral Filter(MBF), Joint Bilateral Filter(JBF), Fuzzy Bilateral Filter(FBF) and Switching Bilateral Filter(SBF). For comparison purpose various performance matrices such as: Peak Signal to Noise Ratio(PSNR), Mean Square Error(MSE), Mean Absolute Error(MAE), Normalized Color Difference(NCD), Perceptual Quality and Time complexity are used . All the techniques are implemented using simulation in MATLAB-9. It is found that the standard BF is the best technique to remove Gaussian noise from images with high PSNR value. However when the image is corrupted with mixed Gaussian and impulse noise, SBF gives the best results of PSNR value, MSE value, MAE value , NCD value and a good picture quality of de-noised image.

In this paper, we consider a cognitive radio network in which the sensing ability of cognitive radio is limited and the channel statistics are not known as a priori information in the opportunistic spectrum access(OSA) framework. It is a special challenge to design a joint spectrum sensing and access strategy for secondary users with diverse service requirements of heterogeneous applications, i.e. the real-time applications and best-effort applications. We formulate the spectrum decision problem as a decentralized multi-armed bandit problem and propose slot structures for cognitive radio network to cope with collisions between heterogeneous applications. The proposed scheme is proved achieving logarithmic regrets in time asymptotically and simulation results show that each user orthogonalizes into their rank-optimal channels according to their pre-allocated priorities, which indicates efficient spectrum utilization while satisfying service requirements.