Development Of Efficient Multi-Level Discrete Wavelet Transform Hardware Architecture For Image Compression

Berfokuskan pengkomputeran intensif dalam gelombang kecil diskret (DWT), reka bentuk seni bina perkakasan efisen bagi pengkomputeran laju menjadi imperatif terutamanya dalam aplikasi masa nyata. Focusing on the intensive computations involved in the discrete wavelet transform (DWT), the design of efficient hardware architectures for a fast computation of the transform has become imperative, especially for real-time applications

Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

Hardware and Software Codesign of a JPEG2000 Watermarking Encoder

Analog technology has been around for a long time. The use of analog technology is necessary since we live in an analog world. However, the transmission and storage of analog technology is more complicated and in many cases less efficient than digital technology. Digital technology, on the other hand, provides fast means to be transmitted and stored. Digital technology continues to grow and it is more widely used than ever before. However, with the advent of new technology that can reproduce digital documents or images with unprecedented accuracy, it poses a risk to the intellectual rights of many artists and also on personal security. One way to protect intellectual rights of digital works is by embedding watermarks in them. The watermarks can be visible or invisible depending on the application and the final objective of the intellectual work. This thesis deals with watermarking images in the discrete wavelet transform domain. The watermarking process was done using the JPEG2000 compression standard as a platform. The hardware implementation was achieved using the ALTERA DSP Builder and SIMULINK software to program the DE2 ALTERA FPGA board. The JPEG2000 color transform and the wavelet transformation blocks were implemented using the hardware-in-the-loop (HIL) configuration

The Mechanisms and Consequences of Cerebral Lateralization

There is a clearly established division of functional processing between left and right hemispheres of the brain, with the pattern showing robust consistency across individuals. The finding of functional differences between the hemispheres of the brain raises two important questions: First, what mechanisms gave rise to the lateralized biases in processing function? Second, what are the consequences of functional asymmetry of cognitive processing in the human brain on our everyday behaviour? Examining the mechanisms that give rise to cerebral lateralization, Experiments 1 and 2 tested the assumption that there is a causal relationship in the degree and direction of lateralization between left- and right-hemisphere dominant tasks. In experiment 1, this relationship between left-hemisphere processing of speech sounds and right-hemisphere processing of emotional vocalizations was examined using dichotic listening tasks. An overall complementary pattern of lateralization was observed across participants, but no significant relationship was found for degree of lateralization of speech and emotional vocalization processing within individuals. These results support the view that functions in the left and right hemispheres are independently lateralized. In Experiment 2 we examined the relationship pattern in degree of lateralization between linguistic processing and melody recognition using dichotic-listening tasks. The expected left-hemisphere advantage was observed for the linguistic processing task, but the expected right-hemisphere advantage was not observed for the melody recognition task, precluding an informative assessment of complementarity between the two tasks. The division of processing between the two hemispheres of the brain has been shown to result in lateralized performance advantages and behavioural biases. Examining these consequences of lateralization, Experiments 3 through 6 explored the influence of lateral biases on everyday behaviour. Experiments 3 and 4 examined the influence of asymmetries in facial attractiveness on posing biases. Despite evidence suggesting that the right side of the face is found to be more attractive, professional modeling photographs examined in Experiment 3 revealed a leftward posing bias suggesting that asymmetries in facial attractiveness are not dominant in influencing posing behaviour, even when the purpose of the image is to highlight attractiveness. Experiment 4 controlled for image selection biases by examining posing behaviour directly and revealed a rightward posing bias when participants were asked to emphasize their attractiveness. Experiments 5 and 6 examined the influence of lateralized cognitive processing demands on seating preferences. Experiment 5 investigated the real-world seating patterns of theatre patrons during actual film screenings. It was found that, when processing expectations relied on right-hemisphere dominant processes, such as emotional, facial, or visuospatial processing, people were more likely to choose a seat to the right side of the room. Experiment 6 was designed to test two competing theories that have attempted to explain seating biases: one posits that expectation of processing demand drives the bias; the other posits that basic motor asymmetries drive the bias. Through naturalistic observation, I recorded classroom-seating choices of university students using photographs. When processing expectations relied on left-hemisphere dominant processes, such as linguistic processing, people were more likely to choose seats on the left side of the classroom; this finding contrasts the right side bias observed in theatre seating studies, providing evidence that expectation of processing demands influences the seating bias. Addressing the mechanisms that guide the evolution of lateralization, no support for the assumption of a causal relationship between complementary left-and right-lateralized cognitive functions was found. Additionally, examination of asymmetries in everyday behaviours such as seating and posing provide evidence that the lateralization of cognitive functions has a direct influence on human behaviour and interaction with the environment

Remote Sensing

This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas

Exploiting the GPU power for intensive geometric and imaging data computation.

Wang Jianqing.Thesis (M.Phil.)--Chinese University of Hong Kong, 2004.Includes bibliographical references (leaves 81-86).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Overview --- p.1Chapter 1.2 --- Thesis --- p.3Chapter 1.3 --- Contributions --- p.4Chapter 1.4 --- Organization --- p.6Chapter 2 --- Programmable Graphics Hardware --- p.8Chapter 2.1 --- Introduction --- p.8Chapter 2.2 --- Why Use GPU? --- p.9Chapter 2.3 --- Programmable Graphics Hardware Architecture --- p.11Chapter 2.4 --- Previous Work on GPU Computation --- p.15Chapter 3 --- Multilingual Virtual Performer --- p.17Chapter 3.1 --- Overview --- p.17Chapter 3.2 --- Previous Work --- p.18Chapter 3.3 --- System Overview --- p.20Chapter 3.4 --- Facial Animation --- p.22Chapter 3.4.1 --- Facial Animation using Face Space --- p.23Chapter 3.4.2 --- Face Set Selection for Lip Synchronization --- p.27Chapter 3.4.3 --- The Blending Weight Function Generation and Coartic- ulation --- p.33Chapter 3.4.4 --- Expression Overlay --- p.38Chapter 3.4.5 --- GPU Algorithm --- p.39Chapter 3.5 --- Character Animation --- p.44Chapter 3.5.1 --- Skeletal Animation Primer --- p.44Chapter 3.5.2 --- Mathematics of Kinematics --- p.46Chapter 3.5.3 --- Animating with Motion Capture Data --- p.48Chapter 3.5.4 --- Skeletal Subspace Deformation --- p.49Chapter 3.5.5 --- GPU Algorithm --- p.50Chapter 3.6 --- Integration of Skeletal and Facial Animation --- p.52Chapter 3.7 --- Result --- p.53Chapter 3.7.1 --- Summary --- p.58Chapter 4 --- Discrete Wavelet Transform On GPU --- p.60Chapter 4.1 --- Introduction --- p.60Chapter 4.1.1 --- Previous Works --- p.61Chapter 4.1.2 --- Our Solution --- p.61Chapter 4.2 --- Multiresolution Analysis with Wavelets --- p.62Chapter 4.3 --- Fragment Processor for Pixel Processing --- p.64Chapter 4.4 --- DWT Pipeline --- p.65Chapter 4.4.1 --- Convolution Versus Lifting --- p.65Chapter 4.4.2 --- DWT Pipeline --- p.67Chapter 4.5 --- Forward DWT --- p.68Chapter 4.6 --- Inverse DWT --- p.71Chapter 4.7 --- Results and Applications --- p.73Chapter 4.7.1 --- Geometric Deformation in Wavelet Domain --- p.73Chapter 4.7.2 --- Stylish Image Processing and Texture-illuminance De- coupling --- p.73Chapter 4.7.3 --- Hardware-Accelerated JPEG2000 Encoding --- p.75Chapter 4.8 --- Web Information --- p.78Chapter 5 --- Conclusion --- p.79Bibliography --- p.8