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PubMed2005

Joint source/channel coding for image transmission with JPEG2000 over memoryless channels.

The high compression efficiency and various features provided by JPEG2000 make it attractive for image transmission purposes. A novel joint source/channel coding scheme tailored for JPEG2000 is proposed in this paper to minimize the end-to-end image distortion within a given total transmission rate through memoryless channels. It provides unequal error protection by combining the forward error correction capability from channel codes and the error detection/localization functionality from JPEG2000 in an effective way. The proposed scheme generates quality scalable and error-resilient codestreams. It gives competitive performance with other existing schemes for JPEG2000 in the matched channel condition case and provides more graceful quality degradation for mismatched cases. Furthermore, both fixed-length source packets and fixed-length channel packets can be efficiently formed with the same algorithm.

Algorithms↗
PubMed2006

Towards a new tool for the evaluation of the quality of ultrasound compressed images.

This paper presents a new tool for the evaluation of ultrasound image compression. The goal is to measure the image quality as easily as with a statistical criterion, and with the same reliability as the one provided by the medical assessment. An initial experiment is proposed to medical experts and represents our reference value for the comparison of evaluation criteria. Twenty-one statistical criteria are selected from the literature. A cumulative absolute similarity measure is defined as a distance between the criterion to evaluate and the reference value. A first fusion method based on a linear combination of criteria is proposed to improve the results obtained by each of them separately. The second proposed approach combines different statistical criteria and uses the medical assessment in a training phase with a support vector machine. Some experimental results are given and show the benefit of fusion.

Algorithms↗
PubMedDate not supplied

Mean square error approximation for wavelet-based semiregular mesh compression.

The objective of this paper is to propose an efficient model-based bit allocation process optimizing the performances of a wavelet coder for semiregular meshes. More precisely, this process should compute the best quantizers for the wavelet coefficient subbands that minimize the reconstructed mean square error for one specific target bitrate. In order to design a fast and low complex allocation process, we propose an approximation of the reconstructed mean square error relative to the coding of semiregular mesh geometry. This error is expressed directly from the quantization errors of each coefficient subband. For that purpose, we have to take into account the influence of the wavelet filters on the quantized coefficients. Furthermore, we propose a specific approximation for wavelet transforms based on lifting schemes. Experimentally, we show that, in comparison with a "naive" approximation (depending on the subband levels), using the proposed approximation as distortion criterion during the model-based allocation process improves the performances of a wavelet-based coder for any model, any bitrate, and any lifting scheme.

Algorithms↗
PubMed2006

Oriented wavelet transform for image compression and denoising.

In this paper, we introduce a new transform for image processing, based on wavelets and the lifting paradigm. The lifting steps of a unidimensional wavelet are applied along a local orientation defined on a quincunx sampling grid. To maximize energy compaction, the orientation minimizing the prediction error is chosen adaptively. A fine-grained multiscale analysis is provided by iterating the decomposition on the low-frequency band. In the context of image compression, the multiresolution orientation map is coded using a quad tree. The rate allocation between the orientation map and wavelet coefficients is jointly optimized in a rate-distortion sense. For image denoising, a Markov model is used to extract the orientations from the noisy image. As long as the map is sufficiently homogeneous, interesting properties of the original wavelet are preserved such as regularity and orthogonality. Perfect reconstruction is ensured by the reversibility of the lifting scheme. The mutual information between the wavelet coefficients is studied and compared to the one observed with a separable wavelet transform. The rate-distortion performance of this new transform is evaluated for image coding using state-of-the-art subband coders. Its performance in a denoising application is also assessed against the performance obtained with other transforms or denoising methods.

Algorithms↗
PubMed2005

[Use of telepathology to provide rapid diagnosis of neurosurgical specimens].

To determine whether still digital images of neurosurgical specimens sent by e-mail are an effective and safe way of obtaining an emergency pathological diagnosis, representative images from 48 neurosurgical smear specimens were digitized, compressed and sent by electronic mail to our consultant neuropathologist with relevant clinical and radiological information. The time to select, digitize, compress and send the images for each case was recorded. Comparison was made between diagnosis made from digital images (DI) and historical smear (HS) using the original permanent section (PS) diagnosis as the gold standard. A diagnosis of normal vs. abnormal, neoplastic vs. non-neoplastic, primary vs. secondary and tumor grade was made in each case. The mean time for selection and digitalization of each case was 9.51 minutes. The number of correct pathological diagnosis was 41/48 using DI and 48/48 using HS, giving an accuracy rate of 85.4% and 100% respectively. DI was 100% sensitive in recognizing neoplastic tissue but only 98% specific. Most inaccuracies were in grading and caused by problems with field selection and familiarity with the technique. We conclude that static digital images are reliable and safe method of interpreting tissue during neurosurgical procedures. This corresponds with the findings of previous studies.

Brain Neoplasms↗
PubMed2004

Evaluation of compressed video-images for emergency telemedicine work with trauma patients.

Video-encoders in telemedicine systems need to adjust their coding methods for operation on heterogeneous networks on which bandwidth fluctuates. We evaluated MPEG-4 compressed video-pictures of three trauma patients. We compared the original video-frames with compressed video-frames in terms of the peak signal-to-noise ratio (PSNR). In a qualitative evaluation, three emergency specialists scored the quality of the video-images blind, on a five-point scale (1= bad to 5 = excellent). The PSNR increased as the bit rate increased from 0.2 to 6 Mbit/s. When the bit rate was fixed, in other words at a given network bandwidth, a higher PSNR was obtained at the expense of spatial resolution and frame rate. The video quality was highly affected by the amount of camera shake. Emergency telemedicine systems require a high bit rate, high spatial resolution and a high frame rate to achieve optimum video quality. However, if the bandwidth is limited (i.e. the bit rate is fixed), temporal resolution becomes more important than spatial resolution.

Data Compression↗
PubMed2005

Perceptual adaptive insensitivity for support vector machine image coding.

Support vector machine (SVM) learning has been recently proposed for image compression in the frequency domain using a constant epsilon-insensitivity zone by Robinson and Kecman. However, according to the statistical properties of natural images and the properties of human perception, a constant insensitivity makes sense in the spatial domain but it is certainly not a good option in a frequency domain. In fact, in their approach, they made a fixed low-pass assumption as the number of discrete cosine transform (DCT) coefficients to be used in the training was limited. This paper extends the work of Robinson and Kecman by proposing the use of adaptive insensitivity SVMs [2] for image coding using an appropriate distortion criterion [3], [4] based on a simple visual cortex model. Training the SVM by using an accurate perception model avoids any a priori assumption and improves the rate-distortion performance of the original approach.

Algorithms↗
PubMed2005

Deblocking of block-transform compressed images using weighted sums of symmetrically aligned pixels.

A new class of related algorithms for deblocking block-transform compressed images and video sequences is proposed in this paper. The algorithms apply weighted sums on pixel quartets, which are symmetrically aligned with respect to block boundaries. The basic weights, which are aimed at very low bit-rate images, are obtained from a two-dimensional function which obeys predefined constraints. Using these weights on images compressed at higher bit rates produces a deblocked image which contains blurred "false" edges near real edges. We refer to this phenomenon as the ghosting effect. In order to prevent its occurrences, the weights of pixels, which belong to nonmonotone areas, are modified by dividing each pixel's weight by a predefined factor called a grade. This scheme is referred to as weight adaptation by grading (WABG). Better deblocking of monotone areas is achieved by applying three iterations of the WABG scheme on such areas followed by a fourth iteration which is applied on the rest of the image. We refer to this scheme as deblocking frames of variable size (DFOVS). DFOVS automatically adapts itself to the activity of each block. This new class of algorithms produces very good subjective results and PSNR results which are competitive relative to available state-of-the-art methods.

Algorithms↗
PubMed2006

A modified SPIHT algorithm for image coding with a joint MSE and classification distortion measure.

The set partitioning in hierarchical trees (SPIHT) algorithm is an efficient wavelet-based progressive image-compression technique, designed to minimize the mean-squared error (MSE) between the original and decoded imagery. However, the MSE-based distortion measure is not in general well correlated with image-recognition quality, especially at low bit rates. Specifically, low-amplitude wavelet coefficients that may be important for classification are given low priority by conventional SPIHT. In this paper, we use the kernel matching pursuits (KMP) method to autonomously estimate the importance of each wavelet subband for distinguishing between different textures, with textural segmentation first performed via a hidden Markov tree. Based on subband importance determined via KMP, we scale the wavelet coefficients prior to SPIHT coding, with the goal of minimizing a Lagrangian distortion based jointly on the MSE and classification error. For comparison we consider Bayes tree-structured vector quantization (B-TSVQ), also designed to obtain a tradeoff between MSE and classification error. The performances of the original SPIHT, the modified SPIHT, and B-TSVQ are compared.

Algorithms↗
PubMed2005

On multirate optimality of JPEG2000 code stream.

Arguably, the most important and defining feature of the JPEG2000 image compression standard is its R-D optimized code stream of multiple progressive layers. This code stream is an interleaving of many scalable code streams of different sample blocks. In this paper, we reexamine the R-D optimality of JPEG2000 scalable code streams under an expected multirate distortion measure (EMRD), which is defined to be the average distortion weighted by a probability distribution of operational rates in a given range, rather than for one or few fixed rates. We prove that the JPEG2000 code stream constructed by embedded block coding of optimal truncation is almost optimal in the EMRD sense for uniform rate distribution function, even if the individual scalable code streams have nonconvex operational R-D curves. We also develop algorithms to optimize the JPEG2000 code stream for exponential and Laplacian rate distribution functions while maintaining compatibility with the JPEG2000 standard. Both of our analytical and experimental results lend strong support to JPEG2000 as a near-optimal scalable image codec in a fairly general setting.

Algorithms↗
PubMed2005

Dynamic contrast-based quantization for lossy wavelet image compression.

This paper presents a contrast-based quantization strategy for use in lossy wavelet image compression that attempts to preserve visual quality at any bit rate. Based on the results of recent psychophysical experiments using near-threshold and suprathreshold wavelet subband quantization distortions presented against natural-image backgrounds, subbands are quantized such that the distortions in the reconstructed image exhibit root-mean-squared contrasts selected based on image, subband, and display characteristics and on a measure of total visual distortion so as to preserve the visual system's ability to integrate edge structure across scale space. Within a single, unified framework, the proposed contrast-based strategy yields images which are competitive in visual quality with results from current visually lossless approaches at high bit rates and which demonstrate improved visual quality over current visually lossy approaches at low bit rates. This strategy operates in the context of both nonembedded and embedded quantization, the latter of which yields a highly scalable codestream which attempts to maintain visual quality at all bit rates; a specific application of the proposed algorithm to JPEG-2000 is presented.

Algorithms↗
PubMed2006

Adaptive downsampling to improve image compression at low bit rates.

At low bit rates, better coding quality can be achieved by downsampling the image prior to compression and estimating the missing portion after decompression. This paper presents a new algorithm in such a paradigm, based on the adaptive decision of appropriate downsampling directions/ratios and quantization steps, in order to achieve higher coding quality with low bit rates with the consideration of local visual significance. The full-resolution image can be restored from the DCT coefficients of the downsampled pixels so that the spatial interpolation required otherwise is avoided. The proposed algorithm significantly raises the critical bit rate to approximately 1.2 bpp, from 0.15-0.41 bpp in the existing downsample-prior-to-JPEG schemes and, therefore, outperforms the standard JPEG method in a much wider bit-rate scope. The experiments have demonstrated better PSNR improvement over the existing techniques before the critical bit rate. In addition, the adaptive mode decision not only makes the critical bit rate less image-independent, but also automates the switching coders in variable bit-rate applications, since the algorithm turns to the standard JPEG method whenever it is necessary at higher bit rates.

Algorithms↗
PubMed2006

Context-based coding of bilevel images enhanced by digital straight line analysis.

A new efficient compression scheme for bilevel images containing locally straight edges is presented. This paper is especially focused on lossless (intra) coding of binary shapes for image and video objects, but other images with similar characteristics such as line drawings, layers of digital maps, or segmentation maps are also encoded efficiently. The algorithm is not targeted at document images with text, which can be coded efficiently with dictionary-based techniques as in JBIG2. The scheme is based on a local analysis of the digital straightness of the causal part of the object boundary, which is used in the context definition for arithmetic encoding. Tested on individual images of standard TV resolution binary shapes and the binary layers of a digital map, the proposed algorithm outperforms PWC, JBIG, JBIG2, and MPEG-4 CAE. On the binary shapes, the code lengths are reduced by 21%, 27%, 28%, and 41%, respectively. On the map layers, the reductions are 31%, 34%, 32%, and 64%, respectively. The algorithm is also more efficient on the test material than the state-of-the-art generic bilevel image coder free tree.

Algorithms↗
PubMed2005

Rate-distortion optimized tree-structured compression algorithms for piecewise polynomial images.

This paper presents novel coding algorithms based on tree-structured segmentation, which achieve the correct asymptotic rate-distortion (R-D) behavior for a simple class of signals, known as piecewise polynomials, by using an R-D based prune and join scheme. For the one-dimensional case, our scheme is based on binary-tree segmentation of the signal. This scheme approximates the signal segments using polynomial models and utilizes an R-D optimal bit allocation strategy among the different signal segments. The scheme further encodes similar neighbors jointly to achieve the correct exponentially decaying R-D behavior (D(R) - c(o)2(-c1R)), thus improving over classic wavelet schemes. We also prove that the computational complexity of the scheme is of O(N log N). We then show the extension of this scheme to the two-dimensional case using a quadtree. This quadtree-coding scheme also achieves an exponentially decaying R-D behavior, for the polygonal image model composed of a white polygon-shaped object against a uniform black background, with low computational cost of O(N log N). Again, the key is an R-D optimized prune and join strategy. Finally, we conclude with numerical results, which show that the proposed quadtree-coding scheme outperforms JPEG2000 by about 1 dB for real images, like cameraman, at low rates of around 0.15 bpp.

Algorithms↗
PubMed2004

Evaluation of JPEG 2000 encoder options: human and model observer detection of variable signals in X-ray coronary angiograms.

Previous studies have evaluated the effect of the new still image compression standard JPEG 2000 using nontask based image quality metrics, i.e., peak-signal-to-noise-ratio (PSNR) for nonmedical images. In this paper, the effect of JPEG 2000 encoder options was investigated using the performance of human and model observers (nonprewhitening matched filter with an eye filter, square-window Hotelling, Laguerre-Gauss Hotelling and channelized Hotelling model observer) for clinically relevant visual tasks. Two tasks were investigated: the signal known exactly but variable task (SKEV) and the signal known statistically task (SKS). Test images consisted of real X-ray coronary angiograms with simulated filling defects (signals) inserted in one of the four simulated arteries. The signals varied in size and shape. Experimental results indicated that the dependence of task performance on the JPEG 2000 encoder options was similar for all model and human observers. Model observer performance in the more tractable and computationally economic SKEV task can be used to reliably estimate performance in the complex but clinically more realistic SKS task. JPEG 2000 encoder settings different from the default ones resulted in greatly improved model and human observer performance in the studied clinically relevant visual tasks using real angiography backgrounds.

Algorithms↗
PubMed2005

Regression-based prediction for blocking artifact reduction in JPEG-compressed images.

In order to reduce the blocking artifact in the Joint Photographic Experts Group (JPEG)-compressed images, a new noniterative postprocessing algorithm is proposed. The algorithm consists of a two-step operation: low-pass filtering and then predicting. Predicting the original image from the low-pass filtered image is performed by using the predictors, which are constructed based on a broken line regression model. The constructed predictor is a generalized version of the projector onto the quantization constraint set, or the narrow quantization constraint set. We employed different predictors depending on the frequency components in the discrete cosine transform (DCT) domain since each component has different statistical properties. Further, by using a simple classifier, we adaptively applied the predictors depending on the local variance of the DCT block. This adaptation enables an appropriate blurring depending on the smooth or detail region, and shows improved performance in terms of the average distortion and the perceptual view. For the major-edge DCT blocks, which usually suffer from the ringing artifact, the quality of fit to the regression model is usually not good. By making a modification of the regression model for such DCT blocks, we can also obtain a good perceptual view. The proposed algorithm does not employ any sophisticated edge-oriented classifiers and nonlinear filters. Compared to the previously proposed algorithms, the proposed algorithm provides comparable or better results with less computational complexity.

Algorithms↗
PubMed2006

Active leukocyte crawling in microvessels assessed by digital time-lapse intravital microscopy.

OBJECTIVE: The ability of active movement is an important feature of leukocytes. Here, we used a hybrid technique that combines intravital microscopy and digital time-lapse video microscopy to investigate the physiology and molecular mechanisms of intravascular leukocyte movement. METHODS: Intravital microscopy of mesenteric venules was performed in male, Wistar rats using digital video recording and time-lapse image compression. The leukocyte movement and extravasation were analyzed after local application of TNF-alpha, after blockade of endothelial (anti-ICAM-1 antibody) and leukocyte (anti-CD18 antibody) adhesion molecules. Additionally, the migratory activity of isolated leukocytes in collagen gel was analyzed and compared with their intravascular locomotion. RESULTS: Adherent leukocytes showed an active intraluminal crawling along the endothelial lining. Most permanent stickers (84 +/- 13%) crawled actively on the intraluminal site of venules. Baseline measurement of leukocyte crawling velocity yielded an average 9.0 +/- 1.8 mum/min that was not significantly different from crawling velocity of extravascular leukocytes (8.9 +/- 4.5 mum/min). The maximum distance of leukocyte crawling observed was 150 microm. The maximum time of crawling was 15 min. Intraluminal crawlers traveled over a mean distance of 35 +/- 17 mum with the average duration of 5.4 +/- 1.4 min. Under unstimulated conditions, almost all crawling leukocytes detached from the endothelium and did not migrate through the vascular wall. TNF-alpha induced a significant increase of leukocyte extravasation. Anti-ICAM-1 and anti-CD18 antibodies significantly reduced leukocyte crawling. The proportion of isolated migrating leukocytes in collagen gel (87% +/- 6%) was not significantly different from the percentage of intravascular crawling leukocytes in vivo. CONCLUSIONS: The method of digital time-lapse intravital microscopy represents an advantageous technology for the investigation of intravascular, transendothelial, and extravascular migration of leukocytes. Using this technology, we showed that leukocyte-endothelial-interactions are an active and dynamic process. This process involves long-time (several minutes) crawling of leukocytes along the endothelium and, finally, detachment from the endothelium. Intravascular leukocyte crawling reflects the migratory potential of circulating leukocytes and strongly depends on the expression of adhesion molecules. For extravasation, an additional pro-inflammatory stimulus is required.

Animals↗
PubMed2006

Passive mechanical properties of large intestine under in vivo and in vitro compression.

This paper presents experimental data obtained from both in vivo and in vitro compression of the large intestine of goat. In vivo experimental data were obtained from compression tests on the large intestine of an anesthetized goat using force-displacement acquisition equipment. In vitro experimental data were also obtained from tissue excised after the in vivo experiments, and two types of data were then compared. The results demonstrated that the stress values had a strong dependence on the compressive rate in the in vivo experiments, although such effect was not distinct in the in vitro experiments. Additionally, at a lower compression rate, the intestinal tissues were found to be stiffer in the in vitro experiments than in the in vivo ones. This paper is a preliminary report on the mechanical properties of the large intestine based on in vivo and in vitro experimental data.

Animals↗