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In this work, a No-Reference objective image quality assessment based on NRDPF-IQA metric and classification based metric are tested using LIVE database, which consisting of Gaussian white noise, Gaussian blur, Rayleigh fast fading channel, JPEG compressed images, JPEG2000 images. We plot the Spearman's Rank Order Correlation Coefficient [SROCC] between each of these features and human DMOS from the LIVE-IQA database using our proposed method to ascertain how well the features correlate with human judgement quality. The analysis of the testing and training is done by SVM model. The proposed method shows better results compared with the earlier methods. Finally, the results are generated by using MATLAB. [ABSTRACT FROM AUTHOR]

Increasingly mature cloud computing technology promotes virtual desktop technology, which can solve many problems existing in traditional computing models. However, virtual desktop solutions introduce the thorny problem of how to deliver a real desktop experience to users, as if they are using it locally, especially when playing video. The SPICE (simple protocol for independent computing environments) virtual desktop solution provides several image compression algorithms to address this problem with the purpose of making virtual desktops as real as possible. Although different compression algorithms can contribute their own abilities to different images to a large extent, switching between them is a big problem that consumes a large amount of resources to detect the different type of image and also causes jitter of the virtual desktop. This paper proposes a new solution, called SPICEx, using the JPEG2000 compression algorithm with dynamic compression ratios to solve the problem and finally validates that the performance is better than that of SPICE. With better quality of user experience and also reducing bandwidth consumption, SPICEx solution is meaningful in virtual desktop fields and can be widely used. [ABSTRACT FROM AUTHOR]

The sheer volume of data anticipated to be captured by future radio telescopes, such as, the Square Kilometer Array (SKA) and its precursors present new data challenges, including the cost and technical feasibility of data transport and storage. Image and data compression are going to be important techniques to reduce the data size. We provide a quantitative analysis of the effects of JPEG2000’s lossy wavelet image compression algorithm on the quality of the radio astronomy imagery data. This analysis is completed by evaluating the completeness, soundness and source parameterisation of the Duchamp source finder using compressed data. Here we found the JPEG2000 image compression has the potential to denoise image cubes, however this effect is only significant at high compression rates where the accuracy of source parameterisation is decreased. [ABSTRACT FROM AUTHOR]

Compression of frontal facial images is an appealing and important application. Recent work has shown that specially tailored algorithms for this task can lead to performance far exceeding JPEG2000. This letter proposes a novel such compression algorithm, exploiting our recently developed redundant tree-based wavelet transform. Originally meant for functions defined on graphs and cloud of points, this new transform has been shown to be highly effective as an image adaptive redundant and multi-scale decomposition. The key concept behind this method is reordering of the image pixels so as to form a highly smooth 1D signal that can be sparsified by a regular wavelet. In this work we bring this image adaptive transform to the realm of compression of aligned frontal facial images. Given a training set of such images, the transform is designed to best sparsify the whole set using a common feature-ordering. Our compression scheme consists of sparse coding using the transform, followed by entropy coding of the obtained coefficients. The inverse transform and a post-processing stage are used to decode the compressed image. We demonstrate the performance of the proposed scheme and compare it to other competing algorithms. [ABSTRACT FROM AUTHOR]

In certain disciplines, it is necessary to access information in large digital images, and because of their size and resolution characteristics, they are difficult to store, transfer and navigate in low capacity devices. Additionally, nowadays the requirements of portability and ubiquity of applications are present in different professional activities. Consequently, development of applications for mobile devices has a great potential for improving different activities with the adequate support from emerging technology. However, it is important to note, that the intrinsic characteristics of these high-resolution images require specific strategies to achieve an efficient way to visualize them in limited capacity devices. On the other hand, most of the interaction interfaces are not easy to use because of their configuration or the need to use complex gestures, which requires both hands, one to hold the devise and the other to interact with the content. This paper presents the design and evaluation of the user experience in the use of mobile devices with three models of interaction, in which it is possible to navigate in high-resolution JPEG2000 images in a flexible and scalable way, focusing in particular areas of interest. The models were designed for limited scenarios in which the user has only one hand to use the device, and they were evaluated by means of standards of usability and accessibility. This development takes advantage of new technologies and proposes an interaction model effective, efficient and accessible to navigate images, exploiting the advantages of touch screens, saving time and facilitating activities that require using images in fieldwork assisted by technology. [ABSTRACT FROM AUTHOR]

A major requirement for electronic publishing systems is the availability of rich and intuitive mechanisms that enhance the user experience of viewing and searching online electronic documents such as books, monographs and journal papers. This work concerns a set of infrastructural components and their utilization for the creation of related coherent services and features for end users. We present a set of sophisticated platforms, tools and mechanisms that have been employed in real-life cases for implementing document viewing and full-text search features, shared among application instances of various types. Challenges encountered and the provided solutions are discussed. [ABSTRACT FROM AUTHOR]

Highlights: [•] New transformation requiring 4 operations per pixel gave the best overall ratios. [•] New transformation done in 2 operations gave the best JPEG2000 and JPEG XR ratios. [•] A transformation from human vision system outperformed established ones. [•] PCA/KLT resulted in ratios inferior to ratios of new and established transformations. [Copyright &y& Elsevier]

Image compression is applied to many fields such as television dissemination, remote sensing, image storage. Digitized images are compressed by a method which exploits the redundancy of the images so that the number of bits required to represent the image can be reduced with acceptable degradation of the decoded image. The humiliation of the image quality is limited with respect to the application used. There are various biomedical applications where accuracy is of major concern. To attain the objective of performance improvement with respect to decoded picture quality and compression ratios, in contrast to existing image compression techniques, an effective image coding technique which involves transforming the image into another domain with ridgelet function and then quantizing the coefficients with hybrid neural networks combining two different learning networks called auto-associative multilayer perceptron and self-organizing feature map is proposed. Ridge functions are effective in representing functions that have discontinuities along straight lines. Normal wavelet transforms not succeed to represent such functions effectively. The results obtained from the combination of finite ridgelet transform with hybrid neural networks found much better than that obtained from the JPEG2000 image compression system. [ABSTRACT FROM AUTHOR]

Parallel processing is key to augmenting the throughput of image codecs. Despite numerous efforts to parallelize wavelet-based image coding systems, most attempts fail at the parallelization of the bitplane coding engine, which is the most computationally intensive stage of the coding pipeline. The main reason for this failure is the causality with which current coding strategies are devised, which assumes that one coefficient is coded after another. This work analyzes the mechanisms employed in bitplane coding and proposes alternatives to enhance opportunities for parallelism. We describe a stationary probability model that, without sacrificing the advantages of current approaches, removes the main obstacle to the parallelization of most coding strategies. Experimental tests evaluate the coding performance achieved by the proposed method in the framework of JPEG2000 when coding different types of images. Results indicate that the stationary probability model achieves similar coding performance, with slight increments or decrements depending on the image type and the desired level of parallelism. [ABSTRACT FROM PUBLISHER]

Currently, the wavelet transform is widely used in the signal processing domain, especially in the image compression because of its excellent de-correlation property and the redundancy property included in the wavelet coefficients. This paper investigates the redundancy relationships between any two or three components of the wavelet coefficients, the wavelet bases and the original signal. We discuss those contents for every condition according to the continuous form and the discrete form, respectively, by which we also derive a uniform formula which illuminates the inherent connection among the redundancy of the wavelet coefficients, the wavelet bases and the original signals. Finally, we present the application of the wavelet coefficient redundancy property in the still image compression domain and compare the properties of the Discrete Wavelet Transform (DWT) with that of the Discrete Cosine Transform (DCT). [ABSTRACT FROM AUTHOR]

JPEG2000 is known as an efficient standard to encode images. However, at very low bit-rates, artifacts or distortions can be observed in decoded images. In order to improve the visual quality of decoded images and make them perceptually acceptable, we propose in this work a new preprocessing scheme. This scheme consists in preprocessing the image to be encoded using a nonlinear filtering, considered as a prior phase to JPEG 2000 compression. More specifically, the input image is decomposed into low- and high-frequency sub-images using morphological filtering. Afterward, each sub-image is compressed using JPEG2000, by assigning different bit-rates to each sub-image. To evaluate the quality of the reconstructed image, two different metrics have been used, namely (a) peak signal to noise ratio, to evaluate the visual quality of the low-frequency sub-image, and (b) structural similarity index measure, to evaluate the visual quality of the high-frequency sub-image. Based on the reconstructed images, experimental results show that, at low bit-rates, the proposed scheme provides better visual quality compared to a direct use of JPEG2000 (excluding any preprocessing). [ABSTRACT FROM AUTHOR]

With the emergence of new scalable coding standards, such as JPEG2000, multimedia is stored as scalable coded bit streams that may be adapted to cater network, device and usage preferences in multimedia usage chains providing universal multimedia access. These adaptations include quality, resolution, frame rate and region of interest scalability and achieved by discarding least significant parts of the bit stream according to the scalability criteria. Such content adaptations may also affect the content protection data, such as watermarks, hidden in the original content. Many wavelet-based robust watermarking techniques robust to such JPEG2000 compression attacks are proposed in the literature. In this paper, we have categorized and evaluated the robustness of such wavelet-based image watermarking techniques against JPEG2000 compression, in terms of algorithmic choices, wavelet kernel selection, subband selection, or watermark selection using a new modular framework. As most of the algorithms use a different set of parametric combination, this analysis is particularly useful to understand the effect of various parameters on the robustness under a common platform and helpful to design any such new algorithm. The analysis also considers the imperceptibility performance of the watermark embedding, as robustness and imperceptibility are two main watermarking properties, complementary to each other. [ABSTRACT FROM AUTHOR]

Last years have witnessed the widespread use of online terrain visualization applications. However, the significant improvements achieved in sensing technologies have allowed an increasing size of the terrain databases. These increasing sizes represent a serious drawback when terrain data must be transmitted and rendered at interactive rates. In this paper, we propose a novel wavelet-tiled pyramid for compressing terrain data that replaces the traditional multiresolution pyramid usually used in wavelet compression schemes. The new wavelet-tiled pyramid modifies the wavelet analysis and synthesis processes, allowing an efficient transmission and reconstruction of terrain data in those applications based on multiresolution tiled pyramids. A comparative performance evaluation with the currently existing techniques shows that the proposed scheme obtains a better compression ratio of the terrain data, reducing the storage space and transmission bandwidth required, and achieving a better visual quality of the virtual terrain reconstructed after data decompression. [ABSTRACT FROM PUBLISHER]

Background Despite the importance of images in the discipline and the diffusion of digital imaging devices, the issue of image compression in dermatology was discussed only in few studies, which yielded results often not comparable, and left some unanswered questions. Objective To evaluate and compare the performance of the JPEG and JPEG2000 algorithms for compression of dermatological images. Methods Nineteen macroscopic and fifteen videomicroscopic images of skin lesions were compressed with JPEG and JPEG2000 at 18 different compression rates, from 90% to 99.5%. Compressed images were shown, next to uncompressed versions, to three dermatologists with different experience, who judged quality and suitability for educational/scientific and diagnostic purposes. Moreover, alterations and quality were evaluated by calculation of mean 'distance' of pixel colors between compressed and original images and by peak signal-to-noise ratio, respectively. Results JPEG2000 was qualitatively better than JPEG at all compression rates, particularly highest ones, as shown by dermatologists' ratings and objective parameters. Agreement between raters was high, but with some differences in specific cases, showing that different professional experience can influence judgement on images. Conclusion In consideration of its high qualitative performance and wide diffusion, JPEG2000 represents an optimal solution for the compression of digital dermatological images. [ABSTRACT FROM AUTHOR]

Differing from common 2D images, a texture map, since it is used to project onto a 3D model in 3D space, not only contains 2D texture information, but also implicitly associates certain 3D geometric information. Related to this, an effective 3D geometry-dependent texture map compression method with hybrid region of interest (ROI) coding is proposed in this paper. We regard the visually important area of the texture map as the ROI. To acquire the visually important areas of the texture map, we take into account information from both the 3D geometry and 2D texture maps, depicting the saliency of the textured model, distortion of the texture mapping, and boundary of the texture atlas. These visually important areas are expressed as a visual importance map. According to the particularity of the texture map, a hybrid ROI coding method that utilizes Max-Shift and an improved post compression rate distortion (PCRD) technique is presented, guided by this visual importance map. To find the exact wavelet coefficients pertaining to these ROIs before carrying out the hybrid ROI coding, this paper proposes a stochastic coefficient priority mask map computational method. Experimental results show that the visually important areas of the texture image have a better visual effect and that a good rendering result can be obtained from the texture mapping. [ABSTRACT FROM AUTHOR]

Visually lossless coding allows image codecs to achieve high compression ratios while producing images without visually noticeable distortion. In general, visually lossless coding is approached from the point of view of the encoder, so most methods are not applicable to already compressed codestreams. This paper presents two algorithms focused on the visually lossless decoding and transmission of JPEG2000 codestreams. The proposed strategies can be employed by a decoder, or a JPIP server, to reduce the decoding or transmission rate without penalizing the visual quality of the resulting images. [ABSTRACT FROM PUBLISHER]

In the present paper, an important mathematical transform which is called Gabor transform be used to develop a method for image compression. Gabor transform is a type of wavelet-based transform. It is embedded in the standard compression algorithm (JPEG2000) as a mother wavelet. Based on the obtained results we believe that Gabor wavelet transform can provide the optimal resolution in both the time and frequency domains, as well as it seems to be the optimal basis to extract local features such as discontinuities. These advantages of Gabor wavelet transform make it an efficient transform for compression. The proposed compression system is a new approach that achieves a high compression ratio with acceptable visual quality by exploiting the advantages of Gabor wavelets .The simulation results show that the proposed model gives a good compression images that could be competitive to JPEG2000 using Haar wavelet.

Modern lossy image coding systems generate a quality progressive codestream that, truncated at increasing rates, produces an image with decreasing distortion. Quality progressivity is commonly provided by an embedded quantizer that employs uniform scalar deadzone quantization (USDQ) together with a bitplane coding strategy. This paper introduces a 2-step scalar deadzone quantization (2SDQ) scheme that achieves same coding performance as that of USDQ while reducing the coding passes and the emitted symbols of the bitplane coding engine. This serves to reduce the computational costs of the codec and/or to code high dynamic range images. The main insights behind 2SDQ are the use of two quantization step sizes that approximate wavelet coefficients with more or less precision depending on their density, and a rate-distortion optimization technique that adjusts the distortion decreases produced when coding 2SDQ indexes. The integration of 2SDQ in current codecs is straightforward. The applicability and efficiency of 2SDQ are demonstrated within the framework of JPEG2000. [ABSTRACT FROM AUTHOR]

The efficient transmission of large resolution images and, in particular, the interactive transmission of images in a client-server scenario, is an important aspect for many applications. Among the current image compression standards, JPEG2000 excels for its interactive transmission capabilities. In general, three mechanisms are employed to optimize the transmission of images when using the JPEG2000 Interactive Protocol (JPIP): 1) packet re-sequencing at the server; 2) prefetching at the client; and 3) proxy servers along the network infrastructure. To avoid the congestion of the network, prefetching mechanisms are not commonly employed when many clients within a local area network (LAN) browse images from a remote server. Aimed to maximize the responsiveness of all the clients within a LAN, this work proposes the use of prefetching strategies at the proxy server—rather than at the clients. The main insight behind the proposed prefetching strategies is a user-navigation model and a semantic map that predict the future requests of the clients. Experimental results indicate that the introduction of these strategies into a JPIP proxy server enhances the browsing experience of the end-users notably. [ABSTRACT FROM PUBLISHER]

This work demonstrates the image qualities between two popular JPEG2000 programs. Two medical image compression algorithms are both coded using JPEG2000, but they are different regarding the interface, convenience, speed of computation, and their characteristic options influenced by the encoder, quantization, tiling, etc. The differences in image quality and compression ratio are also affected by the modality and compression algorithm implementation. Do they provide the same quality? The qualities of compressed medical images from two image compression programs named Apollo and JJ2000 were evaluated extensively using objective metrics. These algorithms were applied to three medical image modalities at various compression ratios ranging from 10:1 to 100:1. Following that, the quality of the reconstructed images was evaluated using five objective metrics. The Spearman rank correlation coefficients were measured under every metric in the two programs. We found that JJ2000 and Apollo exhibited indistinguishable image quality for all images evaluated using the above five metrics ( r > 0.98, p < 0.001). It can be concluded that the image quality of the JJ2000 and Apollo algorithms is statistically equivalent for medical image compression. [ABSTRACT FROM AUTHOR]

The JPEG2000 image compression standard is the newest still image compression standard for digital image consumer electronics, such as digital cameras. However, Tier-1 encoding in the JPEG2000 standard algorithm requires a significant amount of memory and code time. In this study, a highly efficient and low-complexity rate control algorithm for JPEG2000 is proposed to reduce the memory requirements and the computation time. A revisable threshold is developed and is used to select the passes of each code block during Tier-1 encoding. Only the selected passes are encoded during Tier-1 and Tier-2 encoding. This routine avoids the encoding of all code passes and improves the coding efficiency. The experimental results based on standard test images show that the proposed algorithm can reduce the Tier- 1 coding time by up to 86.36% and the working memory by up to 95.50% at a bit rate of 0.125 bpp in comparison to the postcompression rate distortion algorithm. The peak-signal-to-noise ratio across the images remains almost unchanged. The proposed algorithm can not only significantly improve the encoding efficiency but also maintain the image quality. Therefore, it can be applied to consumer imaging devices such as digital cameras, cameras in mobile phones and compact consumer cameras in the form of either embedded or processing software to reduce the memory and hardware requirements. [ABSTRACT FROM PUBLISHER]

Rational and Objectives: To investigate the effect of the Joint Photographic Experts Group (JPEG2000) 30:1 and 60:1 lossy compression on the detection of cranial vault fractures when compared to JPEG2000 lossless compression. Materials and Methods: Fifty cranial computed tomography (CT) images were processed with three different level of JPEG2000 compression (lossless, 30:1 lossy, and 60:1 lossy) creating three sets of images. These were presented to five musculoskeletal specialists and five neuroradiologists. Each reader read at two of the three compression levels. Twenty-two cases contained a single fracture; the remaining 28 cases contained no fractures. Observers were asked to identify the presence or absence of a fracture, to locate its site, and rate their degree of confidence. Receiver operating characteristic (ROC), jackknife free-response receiver operating characteristic (JAFROC) and the Dorfman-Berbaum-Metz multiple reader multiple case (DBM-MRMC) analyses were used to explore differences between the lossless and lossy compressed images. Results: JPEG2000 lossless and 30:1 lossy compression demonstrated no significant difference in their performance with JAFROC and DBM-MRMC analysis (P < .416); however, JPEG2000 30:1 lossy compression demonstrated significantly better performance than 60:1 lossy compression (P < .016). A significant increase in misplaced confidence ratings was also seen with 60:1 (P < .037) over 30:1 lossy and lossless compression. Conclusion: JPEG2000 60:1 compression degrades the detection of skull fractures significantly while increasing the confidence with which readers rate fractures compared with 30:1 lossy and lossless compression. JPEG2000 30:1 lossy compression does not significantly change performance when compared to JPEG2000 lossless for the detection of skull fractures on CT. [ABSTRACT FROM AUTHOR]

The current study presents a quantitative approach towards visually lossless compression ratio (CR) threshold determination of JPEG2000 in digitized mammograms. This is achieved by identifying quantitative image quality metrics that reflect radiologists' visual perception in distinguishing between original and wavelet-compressed mammographic regions of interest containing microcalcification clusters (MCs) and normal parenchyma, originating from 68 images from the Digital Database for Screening Mammography. Specifically, image quality of wavelet-compressed mammograms (CRs, 10:1, 25:1, 40:1, 70:1, 100:1) is evaluated quantitatively by means of eight image quality metrics of different computational principles and qualitatively by three radiologists employing a five-point rating scale. The accuracy of the objective metrics is investigated in terms of (1) their correlation ( r) with qualitative assessment and (2) ROC analysis ( A index), employing pooled radiologists' rating scores as ground truth. The quantitative metrics mean square error, mean absolute error, peak signal-to-noise ratio, and structural similarity demonstrated strong correlation with pooled radiologists' ratings ( r, 0.825, 0.823, −0.825, and −0.826, respectively) and the highest area under ROC curve ( A, 0.922, 0.920, 0.922, and 0.922, respectively). For each quantitative metric, the highest accuracy values of corresponding ROC curves were used to define metric cut-off values. The metrics cut-off values were subsequently used to suggest a visually lossless CR threshold, estimated to be between 25:1 and 40:1 for the dataset analyzed. Results indicate the potential of the quantitative metrics approach in predicting visually lossless CRs in case of MCs in mammography. [ABSTRACT FROM AUTHOR]

Memory requirements (for storing intermediate signals) and critical path are essential issues for 2-D (or multidimensional) transforms. This paper presents new algorithms and hardware architectures to address the above issues in 2-D dual-mode (supporting 5/3 lossless and 9/7 lossy coding) lifting-based discrete wavelet transform (LDWT). The proposed 2-D dual-mode LDWT architecture has the merits of low transpose memory (TM), low latency, and regular signal flow, making it suitable for very large-scale integration implementation. The TM requirement of the N\times N 2-D 5/3 mode LDWT and 2-D 9/7 mode LDWT are 2N and 4N, respectively. Comparison results indicate that the proposed hardware architecture has a lower lifting-based low TM size requirement than the previous architectures. As a result, it can be applied to real-time visual operations such as JPEG2000, motion-JPEG2000, MPEG-4 still texture object decoding, and wavelet-based scalable video coding applications. [ABSTRACT FROM PUBLISHER]

Due to exponential growth in image sizes, visually lossless coding is increasingly being considered as an alternative to numerically lossless coding, which has limited compression ratios. This paper presents a method of encoding color images in a visually lossless manner using JPEG2000. In order to hide coding artifacts caused by quantization, visibility thresholds (VTs) are measured and used for quantization of subband signals in JPEG2000. The VTs are experimentally determined from statistically modeled quantization distortion, which is based on the distribution of wavelet coefficients and the dead-zone quantizer of JPEG2000. The resulting VTs are adjusted for locally changing backgrounds through a visual masking model, and then used to determine the minimum number of coding passes to be included in the final codestream for visually lossless quality under the desired viewing conditions. Codestreams produced by this scheme are fully JPEG2000 Part-I compliant. [ABSTRACT FROM AUTHOR]

This paper presents novel techniques to mitigate the effects of SRAM memory failures caused by low voltage operation in JPEG2000 implementations. We investigate error control coding schemes, specifically single error correction double error detection code based schemes, and propose an unequal error protection scheme tailored for JPEG2000 that reduces memory overhead with minimal effect in performance. Furthermore, we propose algorithm-specific techniques that exploit the characteristics of the discrete wavelet transform coefficients to identify and remove SRAM errors. These techniques do not require any additional memory, have low circuit overhead, and more importantly, reduce the memory power consumption significantly with only a small reduction in image quality. [ABSTRACT FROM AUTHOR]

This work introduces a rate allocation method for the transmission of pre-encoded JPEG2000 video over time-varying channels, which vary their capacity during video transmission due to network congestion, hardware failures, or router saturation. Such variations occur often in networks and are commonly unpredictable in practice. The optimization problem is posed for such networks and a rate allocation method is formulated to handle such variations. The main insight of the proposed method is to extend the complexity scalability features of the FAst rate allocation through STeepest descent (FAST) algorithm. Extensive experimental results suggest that the proposed transmission scheme achieves near-optimal performance while expending few computational resources. [ABSTRACT FROM PUBLISHER]

In this paper a novel approach to the compression of sparse histogram images is proposed. First, we define a sparsity index which gives hints on the relationship between the mathematical concept of matrix sparsity and the visual information of pixel distribution. We use this index to better understand the scope of our approach and its preferred field of applicability, and to evaluate the performance. We present two algorithms which modify one of the coding steps of the JPEG2000 standard for lossless image compression. A theoretical study of the gain referring to the standard is given. Experimental results on well standardized images of the literature confirm the expectations, especially for high sparse images.

Abstract: It is widely recognized that the JPEG2000 facilitates issues in medical imaging: storage, communication, sharing, remote access, interoperability, and presentation scalability. Therefore, JPEG2000 support was added to the DICOM standard Supplement 61. Two approaches to support JPEG2000 medical image are explicitly defined by the DICOM standard: replacing the DICOM image format with corresponding JPEG2000 codestream, or by the Pixel Data Provider service, DICOM supplement 106. The latest one supposes two-step retrieval of medical image: DICOM request and response from a DICOM server, and then JPIP request and response from a JPEG2000 server. We propose a novel strategy for transmission of scalable JPEG2000 images extracted from a single codestream over DICOM network using the DICOM Private Data Element without sacrificing system interoperability. It employs the request redirection paradigm: DICOM request and response from JPEG2000 server through DICOM server. The paper presents programming solution for implementation of request redirection paradigm in a DICOM transparent manner. [Copyright &y& Elsevier]

Watermarking in the Joint Photographic Experts Group (JPEG)2000 coding pipeline is investigated in this paper. A joint quantization and watermarking method based on trellis-coded quantization (TCQ) is proposed to reliably embed data during the quantization stage of the JPEG2000 part 2 codec. The central contribution of this work is the use of a single quantization module to jointly perform quantization and watermark embedding at the same time. The TCQ-based watermarking technique allows embedding the watermark in the detail sub-bands of one or more resolution levels except the first one. Watermark recovery is performed after image decompression. The performance of this joint scheme in terms of image quality and robustness against common image attacks was estimated on real images. [ABSTRACT FROM AUTHOR]

Wavelets/filter banks have become a popular area of research, especially in pavement distress, because they can be used concurrently to separate the subbandsof signal frequencies and analyze the data in time/spatial domains. Because of this, filter banks have been studied in automated pavement distress detection and distress segmentation systems research. However, incorporatingstandard compression coders like Set Partitioning in Hierarchical Tree (SPIHT) or Joint Photographic Experts Group 2000 (JPEG2000) into automated filter bank-based distress detection and segmentation systems has not been presented.An automated filter bank-based pavement crackdetectionsystemthat can effectively incorporate Standard Compression Coders into a filter bank-based automated crackdetection and segmentation system has been proposed in this paper.This is the first known attempt to incorporate standard coders into a system.The proposed system has been validated using real pavement images provided by the Georgia Department of Transportation (GDOT). Preliminary results show that the proposed system can provide usable segmentation results, even at a low bit rate. This allows researchers to reduce data storage requirements and, most importantly, increase the speed over the Embedded Zero-tree Wavelet (EZW) used in previous filter bank-based automated pavement distress systems. Future research is also discussed. [ABSTRACT FROM AUTHOR]

Digital asset management systems (DAMS) generally handle media data in a compressed and encrypted form. It is sometimes necessary to watermark these compressed encrypted media items in the compressed-encrypted domain itself for tamper detection or ownership declaration or copyright management purposes. It is a challenge to watermark these compressed encrypted streams as the compression process would have packed the information of raw media into a low number of bits and encryption would have randomized the compressed bit stream. Attempting to watermark such a randomized bit stream can cause a dramatic degradation of the media quality. Thus it is necessary to choose an encryption scheme that is both secure and will allow watermarking in a predictable manner in the compressed encrypted domain. In this paper, we propose a robust watermarking algorithm to watermark JPEG2000 compressed and encrypted images. The encryption algorithm we propose to use is a stream cipher. While the proposed technique embeds watermark in the compressed-encrypted domain, the extraction of watermark can be done in the decrypted domain. We investigate in detail the embedding capacity, robustness, perceptual quality and security of the proposed algorithm, using these watermarking schemes: Spread Spectrum (SS), Scalar Costa Scheme Quantization Index Modulation (SCS-QIM), and Rational Dither Modulation (RDM). [ABSTRACT FROM PUBLISHER]

Scanning orders of bitplane image coding engines are commonly envisaged from theoretical or experimental insights and assessed in practice in terms of coding performance. This paper evaluates classic scanning strategies of modern bitplane image codecs using several theoretical-practical mechanisms conceived from rate–distortion theory. The use of these mechanisms allows distinguishing those features of the bitplane coder that are essential from those that are not. This discernment can aid the design of new bitplane coding engines with some special purposes and/or requirements. To emphasize this point, a low-complexity scanning strategy is proposed. Experimental evidence illustrates, assesses, and validates the proposed mechanisms and scanning orders. [ABSTRACT FROM AUTHOR]

Lossy compression is becoming increasingly used in remote sensing, although its effect on the processing results has yet not been fully investigated. This paper presents the effects of JPEG2000 lossy compression on the classification of very high-resolution WorldView-2 imagery. For the first time, the k-nearest neighbor and support vector machine methods of the object based classification were used. The results explore the impact of compression on the images, segmentation and resulting classification. The study proves that in general lossy compression does not adversely affect the classification of images; moreover, in some cases classification of compressed images yields better results than classification of the original image. Classification accuracy of the support vector machine method indicates that compression ratios of up to 30:1 can be used without any loss of classification accuracy. The best result of the k-nearest neighbor method was obtained with the highest compression ratio (100:1). The support vector machine is recommended for further research. In addition to the classification method, image segmentation also plays an important role in the accuracy of the results. [ABSTRACT FROM AUTHOR]

High-content screening has brought new dimensions to cellular assays by generating rich data sets that characterize cell populations in great detail and detect subtle phenotypes. To derive relevant, reliable conclusions from these complex data, it is crucial to have informatics tools supporting quality control, data reduction, and data mining. These tools must reconcile the complexity of advanced analysis methods with the user-friendliness demanded by the user community. After review of existing applications, we realized the possibility of adding innovative new analysis options. Phaedra was developed to support workflows for drug screening and target discovery, interact with several laboratory information management systems, and process data generated by a range of techniques including high-content imaging, multicolor flow cytometry, and traditional high-throughput screening assays. The application is modular and flexible, with an interface that can be tuned to specific user roles. It offers user-friendly data visualization and reduction tools for HCS but also integrates Matlab for custom image analysis and the Konstanz Information Miner (KNIME) framework for data mining. Phaedra features efficient JPEG2000 compression and full drill-down functionality from dose-response curves down to individual cells, with exclusion and annotation options, cell classification, statistical quality controls, and reporting. [ABSTRACT FROM PUBLISHER]