The ISO standard JPEG 2000 Part 9 (15444-9) specifies a versatile and flexible image browsing and delivering protocol
that allows the interactive selection of regions of large images and their transmission over a narrow bandwidth connection.
However, due to the enormous flexibility, achieving interoperability between software from differing vendors is not an
easy task. To address this challenge, the JPEG committee started an initiative in the form of an amendment to 15444-9
to establish common grounds on which interoperability can be defined. The outcome of this work are recommendations
which subsets of JPIP vendors should focus on, hopefully easing the adoption of JPIP by identifying the options the
committee found in widespread use. In this paper, the design and evolution of JPIP interoperability will be discussed, the
grounds on which interoperability can be achieved- variants and profiles- will be introduced, and their design will be
motivated. The paper closes with an outlook how to extend this amendment for future applications.
We approach the problem of point target detection in infrared
image sequences by modeling the temporal behavior of clutter and targets
on a single-pixel basis. These models, which are experimentally
verified, are then used to develop a temporal likelihood-ratio test and
derive the corresponding decision rule. We demonstrate the effectiveness
of the technique by applying it to real infrared image sequences
containing targets of opportunity and evolving cloud clutter. The physical
models and resulting hypothesis-testing approach could also be applicable
to other image-sequence-processing scenarios, using acquisition
systems besides infrared imaging, such as the detection of small moving
objects or structures in a biomedical or biological imaging scenario, or
the detection of satellites, meteors, or other celestial bodies in night-sky
imagery acquired using a telescope.
This paper addresses the problem of controlling the bit rate for image sequences compressed using the Motion JPEG2000 Standard. We propose a computationally efficient iterative technique that is intended for applications where real time (or near real time) encoding is required. Using real world video sequences, we analyze the rate control accuracy and image quality performance of the proposed technique. Although the effectiveness of the technique was demonstrated on high action video sequences, the proposed technique is also applicable to other video sequence encoding applications such as security and surveillance systems or video over the internet.
In this paper, we approach the problem of point target detection in IR image sequences by modeling the temporal behavior of clutter and targets on a single pixel basis. These models, which are experimentally verified, are then used to develop a temporal likelihood ratio test and drive the corresponding decision rule. We demonstrate the effectiveness of the technique by applying it to real IR image sequences containing targets of opportunity and evolving cloud clutter. The physical models and resulting hypothesis testing approach could also be applicable to other image sequence processing scenarios. Using acquisition system besides IR imaging, such as detection of small moving objects or structures in a biomedical or biological imaging scenario, or the detection of satellites, meteors or other celestial bodies in night sky imagery acquired using a telescope.
In this paper, we approach the problem of point target detection in infrared image sequences by investigating the application of the continuous wavelet transform to temporal pixel profiles. Observations made on the resulting time-scale images suggest that a multiscale temporal filtering algorithm is suitable for this application. Such an algorithm would exploit the fact that those clutter pixels that are the cause of false alarms when using a medium scale filter, respond to fine and coarse scale filters differently than the target pixels. To demonstrate the effectiveness of a multiscale approach, a first-cut 3-scale approach is tested on actual infrared image sequences featuring targets of opportunity and evolving cloud clutter. Results indicate that the 3-scale approach exhibits improved clutter suppression and target detection, when compared to a single scale filtering approach.
The responsivity of large scale platinum silicide arrays, having small pixels, is low compared to the responsivity of large area test diodes fabricated on the same wafer. Often, the responsivity loss is described by assigning a lower Fowler emission coefficient to the detectors. We find the reduced responsivity to be the direct result of a reduction in the effective active area of the detector. This reduction in effective active area becomes more pronounced as the detector cell size is reduced. We provide a simple model for the area reduction in terms of modulation of detector Schottky potential by the underlying depletion region of the detector guard ring. We also suggest changes in the detector array unit cell design, which will maximize responsivity.
The performance of starting PtSi infrared cameras is characterized based on estimating their spatial frequency response. Applying a modified knife-edge technique, we arrive at an estimate of the edge spread function (ESF), which is used to obtain a profile through the center of the 2-D modulation transfer function (MTF). Using this technique, the complete system MTF in the horizontal and vertical direction is measured for various imaging systems. The influence of charge transfer efficiency (CTE) on the knife-edge measurement and resulting MTF is also modeled and discussed. An estimate of the OlE can actually be obtained from the shape of the ESF in the horizontal direction. In addition, we demonstrate that this technique can be used as a field measurement. By applying the technique at long range, the MTF of the atmosphere can be measured.
This paper is an extension of previous work which dealt with characterizing the performance of staring PtSi infrared cameras, based on estimating their spatial frequency response. Applying a modified knife edge technique, we arrive at an estimate of the edge spread function (ESF), which is used to obtain a profile through the center of the two-dimensional modulation transfer function (MTF). In this paper, we demonstrate that this technique is applicable as a field measurement. The resolution of the system can be calculated using the width of the line spread function (LSF) and an image of an object of known width. In addition, by applying this technique at long range, the MTF of the atmosphere can be measured.
Our algorithm development for point target surveillance is closely meshed to our laboratory IR cameras. The two-stage approach falls into the category of `track before detect' and incorporates dynamic programming optimization techniques. The first stage generates merit scores for each pixel and suppresses clutter by spatial/temporal subtractions from N registered frames of data. The higher the value of the merit score, the more likely that a target is present. In addition to the merit score, the best track associated with each score is stored; together they comprise the merit function. In the second stage, merit functions are associated and dynamic programming techniques are used to create combined merit functions. Nineteen and thirteen frames of data are used to accumulate merit functions. Results using a total of 38 and 39 frames of data are presented for a set of simulated targets embedded in white noise. The result is a high probability of detection and low false alarm rate down to a signal to noise ratio of about 2.0. Preliminary results for some real targets (extracted from real scenes and then re- embedded in white noise) show a graceful degradation from the results obtained on simulated targets.
This work focuses on characterizing the performance of various staring PtSi infrared cameras, based on estimating their spatial frequency response. Applying a modified knife edge technique, we arrive at an estimate of the edge spread function (ESF), which is used to obtain a profile through the center of the two-dimensional Modulation Transfer Function (MTF). The MTF of various cameras in the horizontal and vertical direction is measured and compared to the ideal system MTF. The influence of charge transfer efficiency (CTE) on the knife edge measurement and resulting MTF is also modeled and discussed. An estimate of the CTE can actually be obtained from the shape of the ESF in the horizontal direction. The effect of pixel fill factor on the estimated MTF in the horizontal and vertical directions is compared and explained.
This work develops iterative algorithms for decoding cascade-coded images by Relative Entropy (RE) minimization. In cascade coding, blocks of an image ar first transform-coded and then the retained coefficients are transmitted by using moment-preserving Block Truncation Coding (BTC). The BTC coding introduces a quantization error in the values of the retained coefficients. Upon reception,t he distorted coefficients are used in reconstructing the image by the inverse transform, with the unretained coefficients set equal to zero. The proposed algorithms construct the original image from the distorted coefficients by minimizing the RE of the image, with the coefficients used as constraints. In addition, the error introduced by the BTC coding is used as an additional constraint, since it is known to the receiver by the nature of the BTC coding. The iterative nature of the algorithm pertains to the way the algorithm uses the constraints, i.e. one at a time, with each reconstruction used as a prior for the next RE minimization. This is the first time the RE minimization with errors in the constraints has been used in image decompression even though it is common in spectrum estimation when there are errors in the correlation measurements.
"Cascade coding," a technique of double coding an image is introduced in
this paper. Blocks of the image are first transform-coded and the retained
coefficients of the transform are then quantized by a Block Truncation Coding
C BTC) algorithm for transmission or storage. Upon reception or recall, the
quantized transform coefficients are used in the inverse transform to
reconstruct the image. The new method combines the spatial correlation
characteristics of the transform methods with the ease of implementation of the
BTC. Illustrations presented here on sub-bit image coding, shows it to perform
consistently better than straight Cosine Transform (DCI') coding.