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A passive-polarization-based imaging system records the polarization state of light reflected by objects that are illuminated with an unpolarized and generally uncontrolled source. Such systems can be useful in many remote sensing applications including target detection, object segmentation, and material classification. We present a method to jointly estimate the complex index of refraction and the reflection angle (reflected zenith angle) of a target from multiple measurements collected by a passive polarimeter. An expression for the degree of polarization is derived from the microfacet polarimetric bidirectional reflectance model for the case of scattering in the plane of incidence. Using this expression, we develop a nonlinear least-squares estimation algorithm for extracting an apparent index of refraction and the reflection angle from a set of polarization measurements collected from multiple source positions. Computer simulation results show that the estimation accuracy generally improves with an increasing number of source position measurements. Laboratory results indicate that the proposed method is effective for recovering the reflection angle and that the estimated index of refraction provides a feature vector that is robust to the reflection angle. OCIS codes: 100.0100, 100.5010, 120.5410.

We consider here the implementation of efficient search and retrieval of digital elevation maps (DEMs), in particular the ability to conduct elevation searches without decompressing the entire map. We utilize set partitioning in hierarchical trees (SPIHT) for the compression, and compare two wavelet-based search and retrieval systems: one utilizing nonlinear max- and min-lifted integer wavelets and the other using the standard 5/3 integer wavelet. While the coarse-scale maxima/minima preservation inherent in the max- and min-lifted wavelets may seem ideal for the implementation of efficient elevation searches, the interscale propagation of maxima/minima and the bit-plane layering of the SPIHT coder adversely affect the efficiency of such searches. The use of the standard 5/3 integer wavelet requires the addition of separate maxima and minima information but does not have the complication of coefficient propagation, providing more satisfactory results. Elevation search bitrates are presented for both systems and compared to results obtained using the Kakadu implementation of the JPEG2000 standard. Index Terms--Digital elevation maps (DEMs), image browsing, max-lifted, nonlinear wavelets, search and retrieval lossless compression.

Third-generation full-waveform (FW) light detection and ranging (LIDAR) systems collect time-resolved 1-D signals generated by laser pulses reflected off of intercepted objects. From these signals, scene depth profiles along each pulse path can be readily constructed. By emitting a series of pulses toward a scene using a predefined scanning pattern and with the appropriate sampling and processing, an image-like depth map can be generated. Unfortunately, massive amounts of data are typically acquired to achieve acceptable depth and spatial resolutions. The sampling systems acquiring this data, however, seldom take into account the underlying low-dimensional structure generally present in FW signals and, consequently, they sample very inefficiently. Our main goal and focus here is to develop efficient sampling models and processes to collect individual time-resolved FW LIDAR signals. Specifically, we study sub-Nyquist sampling of the continuous-time LIDAR FW reflected pulses, considering two different sampling mechanisms: 1) modeling FW signals as short-duration pulses with multiple band-limited echoes; and 2) modeling them as signals with finite rates of innovation. [ABSTRACT FROM PUBLISHER]

In this paper, we investigate the problem of determining the conditions under which the restricted isometry property (RIP) is satisfied for a particular type of matrix referred to in here as a banded random matrix (BRM). Such matrices have been recognized as suitable models for a number of compressive-sensing based sampling architectures, including the interleaved random demodulator, the random demodulator, the parallel non-interleaved random demodulator, the random sampler, and the periodic nonuniform sampler. It is thus important to establish the conditions under which the BRM satisfies the RIP; to our knowledge, this question has not been theoretically addressed in the literature. If the resulting conditions are satisfied, full signal recovery using a convex optimization algorithm is guaranteed. The specific objective of this research is to determine the conditions under which the RIP is satisfied for two possible sampling matricies: a BRM and a BRM multiplied by the discrete Fourier matrix. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the problem of characterizing the quality of audio that is impaired by time-varying distortions. Specifically, the quality of such audio must be characterized by a time-dependent function. We first study issues associated with the human subjective testing which must be addressed in order to create such a function, and we conclude that the best approach for achieving both high temporal resolution and high accuracy is most likely a combination of two testing methodologies. Using the collected subjective data, we then design an objective metric that attempts to replicate the subjective responses. The proposed metric uses as its core a subset of the model output variables that are part of the ITU perceptual evaluation of audio quality (PEAQ) recommendation as well as the structural similarity measure and the segmental signal to noise ratio. Depending on the dataset used in its design, we find that the estimated quality has an average correlation coefficient relative to the ground truth curves of between 0.887 and 0.933. Furthermore, we also find that it is possible to reduce the complexity of this metric considerably while only degrading its performance by between 0.3% and 1.6%. In addition, the reduced complexity metric appears to be more robust than the original one. [ABSTRACT FROM PUBLISHER]

Polarization, a property of light that conveys information about the transverse electric field orientation, complements other attributes of electromagnetic radiation such as intensity and frequency. Using multiple passive polarimetric images, we develop an iterative, model-based approach to estimate the complex index of refraction and apply it to target classification. [ABSTRACT FROM AUTHOR]

A perceptually scalable audio coder generates a bit-stream that contains layers of audio fidelity and is encoded in such a way that adding one of these layers enhances the reconstructed audio by an amount that is just noticeable by the listener. Such algorithms have applications like music on demand at variable levels of fidelity, for instance using 3G and 4G cellular radio systems operating at different bit rates. While the MPEG-4 natural audio coder can create finely scalable bit streams using bit sliced arithmetic coding (BSAC), its perceptual quality at low bit rates is poor. On the other hand, the nonscalable transform-domain weighted interleaved vector quantization (TWIN-VQ) performs well at low bit rates. In this paper, we present a modified version of TWIN-VQ algorithm that generates a perceptually scalable bit-stream with many fine layers of audio fidelity. Using TWIN-VQ as our base ensures the best possible perceptual quality at low bit rates. Specifically, the proposed scalable algorithm performs as well as TWIN-VQ at rates of 8 to 16 kb/s and outperforms scalable BSAC by between 64% and 172% at rates of less than 24 kbs. [ABSTRACT FROM AUTHOR]

The goal of this paper is to develop an audio quality metric that can accurately quantify subjective quality over audio fidelities ranging from highly impaired to perceptually lossless. As one example of its utility, such a metric would allow scalable audio coding algorithms to be easily optimized over their entire operating ranges. We have found that the ITU-recommended objective quality metric, ITU-R BS.1387, does not accurately predict subjective audio quality over the wide range of fidelity levels of interest to us. In developing the desired universal metric, we use as a starting point the model output variables (MOVs) that make up BS.1387 as well as the energy equalization truncation threshold which has been found to be particularly useful for highly impaired audio. To combine these MOVs into a single quality measure that is both accurate and robust, we have developed a hybrid least-squares/minimax optimization procedure. Our test results show that the minimax -optimized metric is up to 36% lower in maximum absolute error compared to a similar metric designed using the conventional least-squares procedure. [ABSTRACT FROM AUTHOR]

In this paper, we study coding artifacts in MPEG-compressed scalable audio. Specifically, we consider the MPEG advanced audio coder (AAC) using bit slice scalable arithmetic coding (BSAC) as implemented in the MPEG-4 reference software. First we perform human subjective testing using the comparison category rating (CCR) approach, quantitatively comparing the performance of scalable BSAC with the nonscaled TwinVQ and AAC algorithms. This testing indicates that scalable BSAC performs very poorly relative to TwinVQ at the lowest bitrate considered (16 kb/s) largely because of an annoying and seemingly random mid-range tonal signal that is superimposed onto the desired output. In order to better understand and quantify the distortion introduced into compressed audio at low bit rates, we apply two analysis techniques: Reng bifrequency probing and time-frequency decomposition. Using Reng probing, we conclude that aliasing is most likely not the cause of the annoying tonal signal; instead, time-frequency or spectrogram analysis indicates that its cause is most likely suboptimal bit allocation. Finally, we describe the energy equalization quality metric (EEQM) for predicting the relative perceptual performance of the different coding algorithms and compare its predictive ability with that of ITU Recommendation ITU-R BS.1387-1. [ABSTRACT FROM AUTHOR]

Focuses on a study which presented a novel synthesis for automatic target recognition/cueing and embedded image compression. Mathematical overview; Details on the embedded zerotree wavelet compression; Results and discussion.

Deals with a study which discussed the use of embedded coding algorithm in creating a compressed bit stream that can be truncated to produce reduced resolution versions of the original image. Details on adaptive embedding; Overview of the basic cache-optimized processing scheme; Conclusions.

Focuses on the method of robust image compression based on the embedded zerotree wavelet algorithm. Discussion on the conventional EZW image compression algorithm and its resistance to transmission errors; Indepth look at the performance of the robust algorithm in the presence of channel errors.

Examines modulated polypase filter banks which use reverse-time subfilters to achieve perfect reconstruction and studies in their performance for image coding when used to form a wavelet decomposition. Application of the embedded zerotree wavelet algorithm; Problems in eliminating filter transients; Coding comparisons between two infinite pulses response wavelets.