1293292
Generalized bitplane-by-bitplane shift method for JPEG2000 ROI coding
One interesting feature of the new JPEG2000 image coding standard is support of region of interest (ROI) coding using the maximum shift (Maxshift) method, which allows for arbitrarily shaped ROI image compression without shape coding or explicitly transmitting any shape information to the decoder. The major disadvantage of the Maxshift method is that it cannot adjust the scaling value which determines the degree of relative importance between the ROI and the background wavelet coefficients. The bitplane-by-bitplane shift (BbBShift) method was introduced to support both arbitrary ROI shape and arbitrary scaling without shape coding. We propose a generalized BbBShift (GBbBShift) method, which delivers much more flexibility than both Maxshift and BbBShift for "degree-of-interest" adjustment of the ROI with insignificant effect on coding efficiency and computational complexity. Experiments show that it can provide significantly better visual quality than Maxshift at low bit rates. GBbBShift is not compliant with the current JPEG2000 definitions. In order to use it, a new ROI coding mode would need to be added to the standard.
17056192
Automatic Alignment of High-Resolution NMR Spectra Using a Bayesian Estimation Approach
Nuclear magnetic resonance (NMR) spectral analysis has recently become one of the major means for the detection and recognition of metabolic changes of disease state, physiological alteration, and natural biological variation. For the pattern recognition tasks in which two or more NMR spectra need to be compared, it is critical to properly align the spectra for the subsequent pattern recognition analysis. Previous spectral alignment methods do not consider any baseline intensity variation between the spectra and disregard the effect of noise. Here we formulate the spectra alignment problem in a Bayesian statistical framework, which allows us to simultaneously and efficiently estimate the spectral shift and the baseline intensity variation in the existence of independent additive noise. Experimental results with real high-resolution NMR spectral data from human plasma demonstrate the effectiveness and robustness of the proposed approach
207761262
Image quality assessment: from error visibility to structural similarity
Objective methods for assessing perceptual image quality traditionally attempted to quantify the visibility of errors (differences) between a distorted image and a reference image using a variety of known properties of the human visual system. Under the assumption that human visual perception is highly adapted for extracting structural information from a scene, we introduce an alternative complementary framework for quality assessment based on the degradation of structural information. As a specific example of this concept, we develop a structural similarity index and demonstrate its promise through a set of intuitive examples, as well as comparison to both subjective ratings and state-of-the-art objective methods on a database of images compressed with JPEG and JPEG2000. A MATLAB implementation of the proposed algorithm is available online at http://www.cns.nyu.edu//spl sim/lcv/ssim/.
5251967
Foveation scalable video coding with automatic fixation selection
Image and video coding is an optimization problem. A successful image and video coding algorithm delivers a good tradeoff between visual quality and other coding performance measures, such as compression, complexity, scalability, robustness, and security. In this paper, we follow two recent trends in image and video coding research. One is to incorporate human visual system (HVS) models to improve the current state-of-the-art of image and video coding algorithms by better exploiting the properties of the intended receiver. The other is to design rate scalable image and video codecs, which allow the extraction of coded visual information at continuously varying bit rates from a single compressed bitstream. Specifically, we propose a foveation scalable video coding (FSVC) algorithm which supplies good quality-compression performance as well as effective rate scalability. The key idea is to organize the encoded bitstream to provide the best decoded video at an arbitrary bit rate in terms of foveated visual quality measurement. A foveation-based HVS model plays an important role in the algorithm. The algorithm is adaptable to different applications, such as knowledge-based video coding and video communications over time-varying, multiuser and interactive networks.
6449041
Adaptive frame prediction for foveation scalable video coding
Embedded rate scalable video coding allows for the extraction of coded visual information at continuously varying bit rates from a single compressed bitstream. This is a very attractive feature for many multimedia communication applications. Motion estimation (ME) /motion compensation (MC) techniques are widely employed in various video coding systems to reduce temporal information redundancy. One of the major challenging problems in ME/MC based rate scalable video coding is how to generate the prediction frame from the previous frame to match the current frame. This problem is more difficult in rate scalable coding than in fixed rate coding because the decoding data rate is unavailable to the encoder. We propose an adaptive frame prediction scheme for foveation scalable video coding (FSVC), which is a new video coding algorithm that combines a foveation-based human visual system (HVS) model with a wavelet-based rate scalable coding algorithm. The new frame prediction algorithm provides an adaptive mechanism to control the prediction errors while reduce error propagation.
8060733
Embedded foveation image coding
The human visual system (HVS) is highly space-variant in sampling, coding, processing, and understanding. The spatial resolution of the HVS is highest around the point of fixation (foveation point) and decreases rapidly with increasing eccentricity. By taking advantage of this fact, it is possible to remove considerable high-frequency information redundancy from the peripheral regions and still reconstruct a perceptually good quality image. Great success has been obtained previously by a class of embedded wavelet image coding algorithms, such as the embedded zerotree wavelet (EZW) and the set partitioning in hierarchical trees (SPIHT) algorithms. Embedded wavelet coding not only provides very good compression performance, but also has the property that the bitstream can be truncated at any point and still be decoded to recreate a reasonably good quality image. In this paper, we propose an embedded foveation image coding (EFIC) algorithm, which orders the encoded bitstream to optimize foveated visual quality at arbitrary bit-rates. A foveation-based image quality metric, namely, foveated wavelet image quality index (FWQI), plays an important role in the EFIC system. We also developed a modified SPIHT algorithm to improve the coding efficiency. Experiments show that EFIC integrates foveation filtering with foveated image coding and demonstrates very good coding performance and scalability in terms of foveated image quality measurement.
17971442
Exogenous connectors for software components
In existing component models, control originates in components, and connectors are channels for passing on the control to other components. This provides a mechanism for message passing, which allows components to invoke one another's operations by method calls (or remote procedure calls) either directly or indirectly via a channel such as a bus. Thus components in these models mix computation with control, since in performing their computation they also initiate method calls and manage their returns, via connectors. Consequently, in terms of control, components are not loosely coupled. In this paper, we propose exogenous connectors, and demonstrate their use in a small example. In contrast to connectors in existing component models, exogenous connectors initiate calls and manage their returns, and are used to encapsulate control in a component model we are working on. In the example, we demonstrate the feasibility of exogenous connectors, and compare them with connectors in closely related architecture description languages.
12482658
On circulant chromatic number and circulant chromatic function
Abstract A new concept of circulant chromatic function of a graph is introduced to generalize the concept of chromatic polynomial of a graph. This is similar to the generalization from the concept of chromatic number to the concept of circulant chromatic number. We provide circulant chromatic functions for a few classes of graphs. We consider circulant chromatic functions on the graphs obtained by elementary operations on given graphs, and the relationship between the circulant chromatic number of a graph and that of its complement. We also investigate some sufficient conditions for the circulant chromatic number and the chromatic number of a graph to be equal to each other.
31361781
Adaptive Processing of Tree-Structure Image Representation
Much research on image analysis and processing has been carried out for the last few decades. However, it is still challenging to represent the image contents effectively and satisfactorily. In this paper, a segmentation-free tree-structure image representation is presented. In order to learn the structure representation, a back-propagation through structure (BPTS) algorithm is adopted. Experiments on plant image classification and retrieval refining using only six visual features were conducted on a plant image database and a natural scene image database, respectively. Encouraging results have been achieved.
204983610
Pyramidic Clustering of Large-Scale Microarray Images
With ongoing research and development of imaging techniques such as those involved in brain MRIs, cDNA microarrays and satellite reconnaissance, the need for tools that can intelligently parse larger images is ever increasing. One group of such techniques often used is that of segmentation, an example of which is that of clustering algorithms. In order to deal with large data sets, current approaches require the data to be sampled or summarized before true analysis can take place. In this paper we propose a novel image analysis technique using pyramidic type grouping, namely copasetic clustering, which focuses on the problem of applying traditional clustering techniques to these large-scale image data sets with limited resources. A further benefit of the technique is the transparency of its intermediate clustering steps; when applied to spatial data sets this allows the capture and incorporation of contextual information to improve result accuracy. The algorithm achieves an ∼1--3 dB w-to-noise ratio when compared with the conventional techniques described.
14221801
An opto-VLSI based tunable fiber ring laser
We demonstrate a novel Opto-VLSI tunable fiber ring laser structure in which an Opto-VLSI processor driven by steering phase holograms dynamically selects the lasing wavelengths. A proof-of-concept tunable fiber ring laser which has a wavelength tuning range of more than 4 nm around 1530 nm and a side-mode suppression ratio more than 25 dB is demonstrated at room temperature. The output power of the lasing wavelengths can be controlled within 0.5 dB uniformity by reconfiguring the phase hologram of the Opto-VLSI processor. Dual-wavelength laser tuning is also experimentally demonstrated.