A rate-constrained adaptive quantization scheme for wavelet pyramid image coding

Conference theme: Connecting the WorldIt is well known that orthogonal wavelet transform with filters of nonlinear phase gives poor visual results in low bit rate image coding. Biorthogonal wavelet is a good substitute, which is, however essentially nonorthogonal. A greedy steepest descend algorithm is proposed to design an adaptive quantization scheme based on the actual statistics of the input image. Since the L2 norm of the quantization error is not preserved through the nonorthogonal transform, a quantization error estimation formula considering the characteristic value of the reconstruction filters is derived to incorporate the adaptive quantization scheme. Computer simulation results demonstrate significant SNR gains over standard coding technique, and comparable visual improvements.published_or_final_versio

Finite state lattice vector quantization for wavelet-based image coding

IEEE International Symposium on Circuits and Systems, Hong Kong, China, 9-12 June 1997It is well known that there exists strong energy correlation between various subbands of a real-world image. A new powerful technique of Finite State Vector Quantization (FSVQ) has been introduced to fully exploit the self-similarity of the image in wavelet domain across different scales. Lattices in RN have considerable structure, and hence, Lattice VQ offers the promise of design simplicity and reduced complexity encoding. The combination of FSVQ and LVQ gives rise to the so-called FSLVQ, which is proved to be successful in exploiting the energy correlation across scales and simple enough in implementation.published_or_final_versio

A novel entropy-constrained adaptive quantization scheme for wavelet pyramid image coding

The orthogonal wavelet transform with filters of nonlinear phase gives poor visual results in low bit rate image coding. The biorthogonal wavelet is a good substitute, which is, however essentially nonorthogonal. A greedy steepest descent algorithm is proposed to design an adaptive quantization scheme based on the actual statistics of the input image. Since the L2 norm of the quantization error is not preserved through the nonorthogonal transform, a quantization error estimation formula considering the characteristic value of the reconstruction filters is derived to incorporate the adaptive quantization scheme. Computer simulation results demonstrate significant SNR gains over standard coding techniques, and comparable visual improvements.published_or_final_versio

Model-based multirate Kalman filtering approach for optimal two-dimensional signal reconstruction from noisy subband systems

Conventional synthesis filters in subband systems lose their optimality when additive noise (due, for example, to signal quantization) disturbs the subband components. The multichannel representation of subband signals is combined with the statistical model of input signal to derive the multirate state-space model for the filter bank system with additive subband noises. Thus the signal reconstruction problem in subband systems can be formulated as the process of optimal state estimation in the equivalent multirate state-space model. Incorporated with the vector dynamical model, a 2-D multirate state-space model suitable for 2-D Kalman filtering is developed. The performance of the proposed 2-D multirate Kalman filter can be further improved through adaptive segmentation of the object plane. The object plane is partitioned into disjoint regions based on their spatial activity, and different vector dynamical models are used to characterize the nonstationary object-plane distributions. Finally, computer simulations with the proposed 2-D multirate Kalman filter give favorable results. ©1998 Society of Photo-Optical instrumentation Engineers.published_or_final_versio

Multirate Kalman filtering approach for optimal two-dimensional signal reconstruction from noisy subband systems

The International Conference on Image Processing, Santa Barbara, California, 26-29 October 1997Conventional synthesis filters in subband systems lose their optimality when additive noise due, for example, to signal quantization, disturbs the subband components. The multichannel representation of subband signal is combined with the statistical model of input signal to derive the multirate state-space model for filter bank system with additive noises. Thus the signal reconstruction problem in subband system can be formulated as the process of optimal state estimation in the equivalent multirate state-space model. With the input signal embedded in the state vector, the multirate Kalman filtering provides the minimum-variance reconstruction of input signal. Using the powerful Kronecker product notation, the results and derivations can then be extended to the 2-D cases. Incorporated with the vector dynamical model, the 2-D multirate state-space model for 2-D Kalman filtering is developed. Computer simulation with the proposed 2-D multirate Kalman filter gives favorable results.published_or_final_versio

On the Hardware/Software Design and Implementation of a High Definition Multiview Video Surveillance System

published_or_final_versio

A genome-scale shRNA resource for transgenic RNAi in Drosophila

Existing transgenic RNAi resources in Drosophila melanogaster based on long double-stranded hairpin RNAs are powerful tools for functional studies, but they are ineffective in gene knockdown during oogenesis, an important model system for the study of many biological questions. We show that shRNAs, modeled on an endogenous microRNA, are extremely effective at silencing gene expression during oogenesis. We also describe our progress toward building a genome-wide shRNA resource. © 2011 Nature America, Inc. All rights reserved

Electron-beam-assisted superplastic shaping of nanoscale amorphous silica

At room temperature, glasses are known to be brittle and fracture upon deformation. Zheng et al. show that, by exposing amorphous silica nanostructures to a low-intensity electron beam, it is possible to achieve dramatic shape changes, including a superplastic elongation of 200% for nanowires

Sarcomere Formation Occurs by the Assembly of Multiple Latent Protein Complexes

The stereotyped striation of myofibrils is a conserved feature of muscle organization that is critical to its function. Although most components that constitute the basic myofibrils are well-characterized biochemically and are conserved across the animal kingdom, the mechanisms leading to the precise assembly of sarcomeres, the basic units of myofibrils, are poorly understood. To gain insights into this process, we investigated the functional relationships of sarcomeric protein complexes. Specifically, we systematically analyzed, using either RNAi in primary muscle cells or available genetic mutations, the organization of myofibrils in Drosophila muscles that lack one or more sarcomeric proteins. Our study reveals that the thin and thick filaments are mutually dependent on each other for striation. Further, the tension sensor complex comprised of zipper/Zasp/α-actinin is involved in stabilizing the sarcomere but not in its initial formation. Finally, integrins appear essential for the interdigitation of thin and thick filaments that occurs prior to striation. Thus, sarcomere formation occurs by the coordinated assembly of multiple latent protein complexes, as opposed to sequential assembly