Wavelet-based image compression for mobile applications

The transmission of digital colour images is rapidly becoming popular on mobile telephones, Personal Digital Assistant (PDA) technology and other wireless based image services. However, transmitting digital colour images via mobile devices is badly affected by low air bandwidth. Advances in communications Channels (example 3G communication network) go some way to addressing this problem but the rapid increase in traffic and demand for ever better quality images, means that effective data compression techniques are essential for transmitting and storing digital images. The main objective of this thesis is to offer a novel image compression technique that can help to overcome the bandwidth problem. This thesis has investigated and implemented three different wavelet-based compression schemes with a focus on a suitable compression method for mobile applications. The first described algorithm is a dual wavelet compression algorithm, which is a modified conventional wavelet compression method. The algorithm uses different wavelet filters to decompose the luminance and chrominance components separately. In addition, different levels of decomposition can also be applied to each component separately. The second algorithm is segmented wavelet-based, which segments an image into its smooth and nonsmooth parts. Different wavelet filters are then applied to the segmented parts of the image. Finally, the third algorithm is the hybrid wavelet-based compression System (HWCS), where the subject of interest is cropped and is then compressed using a wavelet-based method. The details of the background are reduced by averaging it and sending the background separately from the compressed subject of interest. The final image is reconstructed by replacing the averaged background image pixels with the compressed cropped image. For each algorithm the experimental results presented in this thesis clearly demonstrated that encoder output can be effectively reduced while maintaining an acceptable image visual quality particularly when compared to a conventional wavelet-based compression scheme.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

An approach for efficient energy consumption and delay guarantee MAC protocol for wireless sensor networks

Wireless sensor networks is an emergent technology that open a world of environment controlling, helping the administrator to predict and anticipate for any possible action that the environment could produce.Unfortunately these energy constrained miniatures must operate in a way that keeps fair consuming between sensor nodes to reach efficient network productivity.In this paper we present a MAC protocol that offers an improved energy efficient consumption and efficient delay guarantee operation. Simulation results shows that the proposed scheme provided better operation than S-MAC protocol

A Motion Estimation Algorithm Using DTCWT and ARPS

In this paper, a hybrid motion estimation algorithm utilizing the Dual Tree Complex Wavelet Transform (DTCWT) and the Adaptive Rood Pattern Search (ARPS) block is presented. The proposed algorithm first transforms each video sequence with DTCWT. The frame n of the video sequence is used as a reference input and the frame n+2 is used to find the motion vector. Next, the ARPS block search algorithm is carried out and followed by an inverse DTCWT. The motion compensation is then carried out on each inversed frame n and motion vector. The results show that PSNR can be improved for mobile device without depriving its quality. The proposed algorithm also takes less memory usage compared to the DCT-based algorithm. The main contribution of this work is a hybrid wavelet-based motion estimation algorithm for mobile devices. Other contribution is the visual quality scoring system as used in section 6

Exploring the Effects of EEG-Based Alpha Neurofeedback on Working Memory Capacity in Healthy Participants

Neurofeedback, an operant conditioning neuromodulation technique, uses information from brain activities in real-time via brain–computer interface (BCI) technology. This technique has been utilized to enhance the cognitive abilities, including working memory performance, of human beings. The aims of this study are to investigate how alpha neurofeedback can improve working memory performance in healthy participants and to explore the underlying neural mechanisms in a working memory task before and after neurofeedback. Thirty-six participants divided into the NFT group and the control group participated in this study. This study was not blinded, and both the participants and the researcher were aware of their group assignments. Increasing power in the alpha EEG band was used as a neurofeedback in the eyes-open condition only in the NFT group. The data were collected before and after neurofeedback while they were performing the N-back memory task (N = 1 and N = 2). Both groups showed improvement in their working memory performance. There was an enhancement in the power of their frontal alpha and beta activities with increased working memory load (i.e., 2-back). The experimental group showed improvements in their functional connections between different brain regions at the theta level. This effect was absent in the control group. Furthermore, brain hemispheric lateralization was found during the N-back task, and there were more intra-hemisphere connections than inter-hemisphere connections of the brain. These results suggest that healthy participants can benefit from neurofeedback and from having their brain networks changed after the training

The effect of colour space on tracking robustness

This paper studies the effect of colour space on the performance of tracking algorithms. The colour spaces that were investigated were grayscale, RGB, YCbCr and HSV. The performance of a normalised cross correlation tracking algorithm was measured to determine robustness and accuracy in the different colour spaces. Track Detection Rate (TDR) and Object Tracking Standard Deviation (OTStd) were used to provide quantitative measures of tracking performance. The combined results indicate that the colour spaces of YCbCr and HSV give more accurate and more robust tracking results compared to grayscale and RGB images. The results also show that the information stored in the chrominance layers of CbCr in the YCbCr colour space and chromaticity layers HS in the HSV colour space, were sufficient for robust tracking. The TDR results range from 93.7% to 97.1% for grayscale and RGB, and 98% to 100% for the YCbCr and HSV colour spaces respectively. A similar trend in the OTStd was observed with a range of 17.0 pixels to 23.9 pixels for grayscale and RGB, and 7.56 pixels to 20.5 pixels for YCbCr and HSV