Scan Order Research Articles

A Secure Steganography Method Based on Integer Lifting Wavelet Transform

Steganography plays an important role in secret communication in digital worlds and open environments like Internet. Undetectability and imperceptibility of confidential data are major challenges of steganography methods. This article presents a secure steganography method in frequency domain based on partitioning approach. The cover image is partitioned into 8×8 blocks and then integer wavelet transform through lifting scheme is performed for each block. The symmetric RC4 encryption method is applied to secret message to obtain high security and authentication. Tree Scan Order is performed in frequency domain to find proper location for embedding secret message. Secret message is embedded in cover image with minimal degrading of the quality. Experimental results demonstrate that the proposed method has achieved superior performance in terms of high imperceptibility of stego-image and it is secure against statistical attack in comparison with existing methods.

Implications of MODIS bow-tie distortion on aerosol optical depth retrievals, and techniques for mitigation

Abstract. The scan geometry of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors, combined with the Earth's curvature, results in a pixel shape distortion known as the "bow-tie effect". Specifically, sensor pixels near the edge of the swath are elongated along-track and across-track compared to pixels near the centre of the swath, resulting in an increase of pixel area by up to a factor of ∼ 9 and, additionally, the overlap of pixels acquired from consecutive scans. The Deep Blue and Dark Target aerosol optical depth (AOD) retrieval algorithms aggregate sensor pixels and provide level 2 (L2) AOD at a nominal horizontal pixel size of 10 km, but the bow-tie distortion means that they also suffer from this size increase and overlap. This means that the spatial characteristics of the data vary as a function of satellite viewing zenith angle (VZA) and, for VZA > 30°, corresponding to approximately 50 % of the data, are areally enlarged by a factor of 50 % or more compared to this nominal pixel area and are not spatially independent of each other. This has implications for retrieval uncertainty and aggregated statistics, causing a narrowing of AOD distributions near the edge of the swath, as well as for data comparability from the application of similar algorithms to sensors without this level of bow-tie distortion. Additionally, the pixel overlap is not obvious to users of the L2 aerosol products because only pixel centres, not boundaries, are provided within the L2 products. A two-step procedure is proposed to mitigate the effects of this distortion on the MODIS aerosol products. The first (simple) step involves changing the order in which pixels are aggregated in L2 processing to reflect geographical location rather than scan order, which removes the bulk of the overlap between L2 pixels and slows the rate of growth of L2 pixel size vs. VZA. This can be achieved without significant changes to existing MODIS processing algorithms. The second step involves additionally changing the number of sensor pixels aggregated across-track as a function of VZA, which preserves L2 pixel size at around 10 km × 10 km across the whole swath but would require algorithmic quality assurance tests to be re-evaluated. Both of these steps also improve the extent to which the pixel locations a user would infer from the L2 data products represent the actual spatial extent of the L2 pixels.

Scan Paths Reduction in Eye Tracking Techniques

Nowadays, the eye tracking is gaining interest as an evaluation technique in a variety of areas and disciplines. Its use allows the study and analysis of the way in which a person visually explores a particular scene, interface or image. The use of this technique in the educational field has increasingly gained place and impact, highlighting its use in the evaluation of multimedia materials. It is interesting to know where and how the students focus their attention when studying the educational materials displayed on a screen. In particular, it is interesting to know the order of visual exploration that the student follows. In this way, for example, we can know, given a content consisting of text and images, whether the explanatory text is helpful or if the image on its own is enough. One of the representations obtained by applying eye tracking sessions is the scan path, which shows the order of points of attention (points of fixation) and the user fixation time on the scene. The main problem is the huge number of points on which a user fixes their attention while visually scanning the contents displayed, so these representations are complex and the analysis task is arduous. Thus, the objective sought is to reduce these scan paths and represent those data that can be more relevant to the researcher, such as transitions between the different areas of interest, or the scanning order of them. In this way, we can achieve a higher level of abstraction and a great deal of information easier to analyze for obtaining conclusions.

Watermarking technique based on three-coefficient comparison in DCT domain

In order to hide information, Yu et al. (Appl Res Comput 26(3):1082---1083, 1103, 2009) presented a method by using the numerical value relation of three pixel values in spatial domain. Their algorithm is very easy to realize and has a big hiding capacity. But its visual performance is not very good, because it is based on spatial domain and cannot control the modification value effectively in edge region or texture region of image. Our work embedded watermark by comparing the numerical value relation of three neighboring DCT coefficients with Zig-Zag order of block image to enhance the visual performance. First, each block of the host image was transformed by DCT. Then the DCT coefficient matrix was scanned by Zig-Zag scanning order to ensure the continuity of the neighboring coefficients. And then through modifying the numerical value relation of three Zig-Zag neighboring DCT coefficients, the three corresponding watermark bits were embedded in. To further improve its performance, the algorithm also employed redundant encoding, watermark scrambling encryption techniques, etc. The experiments show that the algorithm can guarantee a better quality of watermarked image, and has stronger robust to general image processing operations than the method proposed by Yu et al. (Appl Res Comput 26(3):1082---1083, 1103, 2009).

Monitoring Crohn's disease during anti-TNF-α therapy: validation of the magnetic resonance enterography global score (MEGS) against a combined clinical reference standard.

To assess the ability of magnetic resonance enterography global score (MEGS) to characterise Crohn's disease (CD) response to anti-TNF-α therapy. Thirty-six CD patients (median age 26years, 20 males) commencing anti-TNF-α therapy with concomitant baseline MRI enterography (MRE) were identified retrospectively. Patients' clinical course was followed and correlated with subsequent MREs. Scan order was randomised and MEGS (a global activity score) was applied by two blinded radiologists. A physician's global assessment of the disease activity (remission, mild, moderate or severe) at the time of MRE was assigned. The cohort was divided into clinical responders and non-responders and MEGS compared according to activity status and treatment response. Interobserver agreement was assessed. Median MEGS decreased significantly between baseline and first follow-up in responders (28 versus 6, P < 0.001) but was unchanged in non-responders (26 versus 18, P = 0.28). The median MEGS was significantly lower in clinical remission (9) than in moderate (14) or severe (29) activity (P < 0.001). MEGS correlated significantly with clinical activity (r = 0.53; P < 0.001). Interobserver Bland-Altman limits of agreement (BA LoA) were -19.7 to 18.5. MEGS decreases significantly in clinical responders to anti-TNF-α therapy but not in non-responders, demonstrates good interobserver agreement and moderate correlation with clinical disease activity. • MRI scores of Crohn's activity are used increasingly in clinical practice and therapeutic trials. • Such scores have been advocated as biomarkers of therapeutic response. • MEGS reflects clinical response to anti-TNF-α therapy and the clinical classification of disease activity. • MEGS demonstrates good interobserver agreement.

Bitplane Image Coding With Parallel Coefficient Processing.

Image coding systems have been traditionally tailored for multiple instruction, multiple data (MIMD) computing. In general, they partition the (transformed) image in codeblocks that can be coded in the cores of MIMD-based processors. Each core executes a sequential flow of instructions to process the coefficients in the codeblock, independently and asynchronously from the others cores. Bitplane coding is a common strategy to code such data. Most of its mechanisms require sequential processing of the coefficients. The last years have seen the upraising of processing accelerators with enhanced computational performance and power efficiency whose architecture is mainly based on the single instruction, multiple data (SIMD) principle. SIMD computing refers to the execution of the same instruction to multiple data in a lockstep synchronous way. Unfortunately, current bitplane coding strategies cannot fully profit from such processors due to inherently sequential coding task. This paper presents bitplane image coding with parallel coefficient (BPC-PaCo) processing, a coding method that can process many coefficients within a codeblock in parallel and synchronously. To this end, the scanning order, the context formation, the probability model, and the arithmetic coder of the coding engine have been re-formulated. The experimental results suggest that the penalization in coding performance of BPC-PaCo with respect to the traditional strategies is almost negligible.

Sequential block-based disparity map estimation algorithm for stereoscopic image coding

This paper deals with the problem of block-based disparity map estimation for stereoscopic image coding where the estimated map is transmitted to the decoder in order to predict one view from the other. The estimation problem of the disparity map is thus a trade-off between the quality prediction and the binary cost of the disparities to be stored or transmitted. This trade-off is modeled as a joint entropy-distortion metric assuming that the disparity map is encoded with an entropy coder; and one of the two views is fully predicted using this map when applied to the other view. However minimizing this joint metric is a complex combinatorial optimization problem where choices of disparities are all interrelated. A sub-optimal optimization solution is then proposed. It is based on a tree structure which is constructed sequentially whenever a block is matched. The developed algorithm, called Modified M-Algorithm (MMA), processes the reference view in a raster scanning order and assumes that the disparities to be selected in the unprocessed area are likely to follow a chosen disparity distribution. This algorithm has the ability at each step of the process not only to retain the M-best paths of the tree in terms of entropy-distortion cost but also to explore all possible extensions of each of these M paths until reading the last block of the view. Simulations, conducted on stereoscopic images extracted from Middlebury and Deimos datasets, show the advantage of our MMA compared to the conventional Block Matching Algorithm (BMA) with and without regularization both in terms of reducing bitrate and distortion.

Reliability of 2 Different Positioning Protocols for Dual-Energy X-ray Absorptiometry Measurement of Body Composition in Healthy Adults

Dual-energy X-ray absorptiometry (DXA) is an accepted time-efficient method of body composition assessment for total body and regional fat mass (FM), lean mass (LM), and bone mineral content (BMC), but for longitudinal monitoring the measurements must be sufficiently reliable. The aim of this study was to compare the reliability of a new positioning protocol (Nana et al) with the current reference (National Health and Nutrition Examination Survey [NHANES]) protocol and investigate their within-protocol precision. Thirty healthy adults (16 females and 14 males) underwent 4 whole-body DXA scans in succession with full repositioning between scans. The scan order was randomized, with 2 scans undertaken in accordance with the current NHANES protocol and 2 using the Nana et al protocol. Magnitudes of typical errors of measurement and changes in the mean of DXA body composition estimates were assessed as standardized effect sizes. The Nana et al protocol repositioning produced trivial typical errors for total body across all LM estimates except for FM in the arms and trunk which were moderately substantial. The NHANES protocol produced similar typical errors for all measurements in LM except for FM and BMC in the trunk and arms which were substantially larger than the smallest worthwhile effect. The difference between protocols produced substantially large typical errors in estimations of both total body FM and regional FM and BMC, but differences in LM were all less than the smallest worthwhile effect. Although both protocols demonstrated acceptable intratest reliability, the Nana et al protocol produced enhanced precision in regional (arms and trunk) FM and BMC. The protocols were substantially different in body composition assessment especially for FM and thus should not to be interchanged. Anecdotally, subjects felt more comfortable and supported during the scan with the Nana et al protocol.

Test-retest reliability of graph metrics in high-resolution functional connectomics: a resting-state functional MRI study.

The combination of resting-state functional MRI (R-fMRI) technique and graph theoretical approaches has emerged as a promising tool for characterizing the topological organization of brain networks, that is, functional connectomics. In particular, the construction and analysis of high-resolution brain connectomics at a voxel scale are important because they do not require prior regional parcellations and provide finer spatial information about brain connectivity. However, the test-retest reliability of voxel-based functional connectomics remains largely unclear. This study tended to investigate both short-term (∼20 min apart) and long-term (6 weeks apart) test-retest (TRT) reliability of graph metrics of voxel-based brain networks. Based on graph theoretical approaches, we analyzed R-fMRI data from 53 young healthy adults who completed two scanning sessions (session 1 included two scans 20 min apart; session 2 included one scan that was performed after an interval of ∼6 weeks). The high-resolution networks exhibited prominent small-world and modular properties and included functional hubs mainly located at the default-mode, salience, and executive control systems. Further analysis revealed that test-retest reliabilities of network metrics were sensitive to the scanning orders and intervals, with fair to excellent long-term reliability between Scan 1 and Scan 3 and lower reliability involving Scan 2. In the long-term case (Scan 1 and Scan 3), most network metrics were generally test-retest reliable, with the highest reliability in global metrics in the clustering coefficient and in the nodal metrics in nodal degree and efficiency. We showed high test-retest reliability for graph properties in the high-resolution functional connectomics, which provides important guidance for choosing reliable network metrics and analysis strategies in future studies.

An enhanced one-dimensional SPIHT algorithm and its implementation for TV systems

In general, to achieve high compression efficiency, a 2D image or a 2D block is used as the compression unit. However, 2D compression requires a large memory size and long latency when input data are received in a raster scan order that is common in existing TV systems. To address this problem, a 1D compression algorithm that uses a 1D block as the compression unit is proposed. 1D set partitioning in hierarchical trees (SPIHT) is an effective compression algorithm that fits the encoded bit length to the target bit length precisely. However, the 1D SPIHT can have low compression efficiency because 1D discrete wavelet transform (DWT) cannot make use of the redundancy in the vertical direction. This paper proposes two schemes for improving compression efficiency in the 1D SPIHT. First, a hybrid coding scheme that uses different coding algorithms for the low and high frequency bands is proposed. For the low-pass band, a differential pulse code modulation–variable length coding (DPCM–VLC) is adopted, whereas a 1D SPIHT is used for the high-pass band. Second, a scheme that determines the target bit length of each block by using spatial correlation with a minimal increase in complexity is proposed. Experimental results show that the proposed algorithm improves the average peak signal to noise ratio (PSNR) by 2.97dB compared with the conventional 1D SPIHT algorithm. With the hardware implementation, the throughputs of both encoder and decoder designs are 6.15Gbps, and gate counts of encoder and decoder designs are 42.8K and 57.7K, respectively.

Block based reversible data hiding algorithm using edge direction scan order

In this paper, we present a block based reversible data hiding algorithm using the edge direction scan order. In the proposed algorithm, we first divide an image into a set of blocks. Then, we develop a novel feature prediction scheme to classify the blocks into non-smooth and smooth blocks as well as predict the edge directions of the blocks. Based on the four kinds of edge directions, four edge direction scan orders of blocks are presented to gain a better prediction as well as to guide the embedding process with a higher embedding capacity. Finally, we exploit the difference expansion conducted by the proposed edge direction scan order to embed hidden data. In addition, since the appropriate threshold determination is a critical issue for a data hiding algorithm, we design a new systematic way to tackle this problem. The results of experiments on some typical test images demonstrate that, under the same embedding capacity, the proposed reversible data hiding algorithm delivers better quality of marked images than the three previously published reversible data hiding algorithms. Conversely, under the same quality of marked images, the proposed algorithm has higher peak signal/noise ratio performance.

Alternating scanning orders and combining algorithms to improve the efficiency of flow accumulation calculation

Conventionally, a raster operation that needs to scan the entire image employs only one scanning order (i.e., single scanning order (SSO)), and the scan usually runs from upper left to lower right and row by row. We explore the idea of alternately applying multiple scanning orders (MSO) to raster operations that are based on the local direction, using the flow accumulation (FA) calculation as an example. We constructed several FA methods based on MSO, and compared them with those widely used methods. Our comparison includes experiments over digital elevation models (DEMs) of different landforms and DEMs of different resolutions. For each DEM, we calculated both single-direction FA (SD-FA) and multi-direction FA (MD-FA). In the theoretical aspect, we deducted the time complexity of an MSO sequential algorithm (MSOsq) for FA based on empirical equations in hydrology. Findings from the experiments include the following: (1) an MSO-based method is generally superior to its counterpart SSO-based method. (2) The advantage of MSO is more significant in the SD-FA calculation than in the MD-FA calculation. (3) For SD-FA, the best method among the compared methods is the one that combines the MSOsq and the depth-first algorithm. This method surpasses the commonly recommended dependency graph algorithm, in both speed and memory use. (4) The differences between the compared methods are not sensitive to specific landforms. (5) For SD-FA, the advantage of MSO-based methods is more obvious in a higher DEM resolution, but this does not apply to MD-FA.

Spatial Error Concealment With an Adaptive Linear Predictor

In this paper, a novel spatial error concealment (EC) algorithm is proposed. Under the sequential recovery framework, pixels in missing blocks are successively reconstructed based on adaptive linear predictor. The predictor automatically tunes its order and support shape according to local contexts. The predictor order and support shape are determined using Bayesian information criterion, which is able to strike a balance between the bias and variance of the prediction errors. The flexibility of the order-adaptive predictor is able to recover more important features or structures. A novel scan order based on the uncertainty of each pixel is also proposed to alleviate error propagation problem. Compared with the state-of-the-art EC algorithms, experimental results show that the proposed method gives better reconstruction performance in terms of objective and subjective evaluations.

Impulse noise removal using 1-D switching median filter with adaptive scanning order based on structural context of image

This paper describes the detail-preserving impulse noise removal performance of a one-dimensional (1-D) switching median filter (SMF) applied along an adaptive space-filling curve. Usually, a SMF with a two-dimensional (2-D) filter window is widely used for impulse noise removal while still preserving detailed parts in an input image. However, the noise detector of the 2-D filter does not always distinguish between the original pixels and the noise-corrupted ones perfectly. In particular, pixels constituting thin lines in an input image tend to be incorrectly detected as noise-corrupted pixels, and such pixels are filtered regardless of the necessity of the filtering. To cope with this problem, we propose a new impulse noise removal method based on a 1-D SMF and a space-filling curve which is adaptively drawn using a minimum spanning tree reflecting structural context of an input image.

The Impact of a Health IT Changeover on Medical Imaging Department Work Processes and Turnaround Times: A mixed method study.

To assess the impact of introducing a new Picture Archiving and Communication System (PACS) and Radiology Information System (RIS) on: (i) Medical Imaging work processes; and (ii) turnaround times (TATs) for x-ray and CT scan orders initiated in the Emergency Department (ED). We employed a mixed method study design comprising: (i) semi-structured interviews with Medical Imaging Department staff; and (ii) retrospectively extracted ED data before (March/April 2010) and after (March/April 2011 and 2012) the introduction of a new PACS/RIS. TATs were calculated as: processing TAT (median time from image ordering to examination) and reporting TAT (median time from examination to final report). Reporting TAT for x-rays decreased significantly after introduction of the new PACS/RIS; from a median of 76 hours to 38 hours per order (p<.0001) for patients discharged from the ED, and from 84 hours to 35 hours (p<.0001) for patients admitted to hospital. Medical Imaging staff reported that the changeover to the new PACS/RIS led to gains in efficiency, particularly regarding the accessibility of images and patient-related information. Nevertheless, assimilation of the new PACS/RIS with existing Departmental work processes was considered inadequate and in some instances unsafe. Issues highlighted related to the synchronization of work tasks (e.g., porter arrangements) and the material set up of the work place (e.g., the number and location of computers). The introduction of new health IT can be a "double-edged sword" providing improved efficiency but at the same time introducing potential hazards affecting the effectiveness of the Medical Imaging Department.

The Role of Imaging in Acute Appendicitis among Children from a Community Hospital

Background: Acute appendicitis is one of the most common surgical emergencies with a lifetime prevalence of approximately 1 in 7. Early diagnosis and prompt surgical intervention is the key for successful management of acute appendicitis and avoidance of complications. With increased availability of advanced imaging, computed tomography (CT) has become the primary modality for evaluating patients with abdominal pain in many institutions across the United States. The incidence of appendicitis and it propensity to occur in younger patients strongly argue for judicious use of CT. Objective: Our goal is to reduce the use of CT scans and potential radiation risk in the diagnosis of acute appendicitis. Method: We conducted a retrospective chart review of hospital data of patients who presented to the Emergency Department with abdominal 2006 to 2010. Statistical analysis was done using STATA 11.0 statistical software. Results: There were 175 patients who met the inclusion criteria for the study. There were no statistically significant differences in baseline characteristics between patients with Alvarado ≥ 7 and those with Alvarado<7. Patients with Alvarado ≥ 7 made up 50.9% of our study population. Abdominal CT scan was ordered in 63.4% of the patients; 44.8% with Alvarado ≥ 7. There was no significant difference in proportion with CT scan order between those who had Alvarado score ≥ 7 and those with Alvarado score<7 (p-value 0.19) after adjusting for age, gender and BMI. Conclusion: We found no significant difference between CT scan order and Alvarado score. There was no significant difference between Alvarado score and gender, race/ethnicity or BMI. Despite the wealth of information regarding the role of clinical skills in reducing the need for imaging in diagnoses of acute appendicitis, our study showed no difference in CT ordering based on clinical presentation.

Novel superimposed diamond search algorithm for medical image compression

A novel search algorithm called superimposed diamond search algorithm SDSA based on lifting wavelet transform LWT for medical image compression is proposed in this paper. Fuzzy C means clustering FCM is applied to extract the region of interest ROI from the medical image. MAXSHIFT method is used to scale the coefficients so that the bits associated with the ROI are placed in higher bit planes than the bits associated with the background without the requirement of the shape information and without the need for calculating the ROI mask. SDSA keeps track of significant pixels of wavelet sub-band in hexagonal search in the scan order of left to right and top to bottom. The experimental results show the good compression ratio over the other existing methods such as set partitioning in hierarchical trees SPIHT and embedded zerotree wavelet EZW.

Dynamic Image-to-Class Warping for Occluded Face Recognition

Face recognition (FR) systems in real-world applications need to deal with a wide range of interferences, such as occlusions and disguises in face images. Compared with other forms of interferences such as nonuniform illumination and pose changes, face with occlusions has not attracted enough attention yet. A novel approach, coined dynamic image-to-class warping (DICW), is proposed in this work to deal with this challenge in FR. The face consists of the forehead, eyes, nose, mouth, and chin in a natural order and this order does not change despite occlusions. Thus, a face image is partitioned into patches, which are then concatenated in the raster scan order to form an ordered sequence. Considering this order information, DICW computes the image-to-class distance between a query face and those of an enrolled subject by finding the optimal alignment between the query sequence and all sequences of that subject along both the time dimension and within-class dimension. Unlike most existing methods, our method is able to deal with occlusions which exist in both gallery and probe images. Extensive experiments on public face databases with various types of occlusions have confirmed the effectiveness of the proposed method.

Frame Rate Up-Conversion Method for Video Processing Applications

In this paper, a new low-complexity frame rate up-conversion (FRUC) method is proposed for video processing applications. In the proposed FRUC method, true motion estimation (TME) is used to track motion trajectories by imposing smoothness constraints on block-matching algorithm (BMA). In order to produce high-quality interpolated frames, TME is performed in both forward and backward directions; then, the reliable dense motion vector field is obtained by using the multistage motion vector (MV) post-processing method. The constraints of low computational complexity and low memory bandwidth are also considered in our method. We use a histogram-based predictive search to impose smoothness constrains and reduce the number of search points. Furthermore, a complexity-simplified improvement of the proposed method is introduced to reduce computational complexity with slight quality degradation. In addition, a new scan order of BMA and a pipelining of MV post-processing are presented to guarantee the causality of the system and improve the pixel data reuse, which reduces the memory bandwidth. The experiment results show that the proposed FRUC method achieves not only better video quality, but also low computational complexity and memory bandwidth compared to the conventional methods.

A new adaptive coefficient scanning based on local and global prediction

In this paper, a new adaptive coefficient scanning scheme, which is called local- and global-prediction-based adaptive scanning (LGPAS), is described to improve the coding efficiency of discrete cosine transform (DCT)-based image compression methods including JPEG and H.264/AVC intra-coding, in which zigzag scanning is used. The coding performance is limited because the zigzag scan order ignores the statistical properties of the DCT coefficients. On the other hand, we adopt not only the global information but also the local information to perform learning and adaptively generate the scanning patterns, unlike the existing methods. Furthermore, we adopt variation prediction, nonzero probability estimation, and the proposed techniques of zigzag weighting and energy weighting matrices to generate the scanning pattern. On the basis of the local and global predictions for the probability distributions of the nonzero DCT coefficients in an image, the proposed LGPAS scheme can adaptively update the scan order patterns and thus achieves a higher entropy coding gain. Simulations show that the proposed scheme significantly outperforms the conventional zigzag scanning method and other existing adaptive scanning methods.