Row Of Pixels Research Articles

Reducing Microfluidic Very Large-Scale Integration (mVLSI) Chip Area by Seam Carving

Seam carving is an algorithm that analyzes image content and can be used for size reduction in a manner that avoids direct compression or downscaling. Seam carving iteratively identifies horizontal and/or vertical paths of least visual importance and removes them from the image; each path removal reduces the length or width of the image by one row or column of pixels. This article adapts seam carving to reduce excess area of flow-based microfluidic chips that have been drawn by hand or by computer-aided heuristics without negatively impacting their functionality. The proposed approach leverages domain knowledge, wherein the image to be carved consists of I/O ports, components, and fluid channels, with known and understood fluidic behavior. Three different variants of seam carving are presented: 1) linear; 2) nonlinear; and 3) nonrectilinear; experimental results show that nonrectilinear, which is the most general of the three, yields the best results: it improves area utilization by 8.6× and reduces fluid routing channel length by 73% across a set of benchmark microfluidic designs.

Enhancing the kinetic complexity of 2-D digital coupled chaotic lattice

A 2-dimensional coupled logistic map lattice model and a 2-dimensional Logistic-nested-Sine map are proposed in this paper. In order to strengthen complexity of 2-dimensional coupled logistic map lattice, chaotic sequences are transformed to binary sequences, and new decimal sequences are constructed by perturbed binary sequences. Numerical experimental results demonstrate that this method can increase the complexity and ergodicity of 2-dimensional coupled logistic map lattice effectively. The initial values of the 2-dimensional coupled logistic map lattice are determined by utilization of the SHA 512 hash function. The row and column positions of pixels are shuffled completely in permutation process. Unlike 1-dimensional linear diffusion operation, we have adopted two-dimensional space diffusion began from random semi-surround. Keys security, correlation coefficient, information entropy, and ability of defending differential attack are analyzed to confirm the security of our encryption scheme. Experimental results confirm that the proposed algorithm can encrypt image effectively.

Camera ISP Modification to Enable Image De-rendering

A camera's image signal processor (ISP) is dedicated hardware that performs a series of processing steps to render a captured raw sensor image to its final display-referred output suitable for viewing and sharing. It is often desirable to be able to revert – or de-render – the ISP-processed image back to the original raw sensor image. Undoing the ISP rendering, however, is not an easy task. This is because ISPs perform many nonlinear routines in the rendering pipeline that are difficult to invert. Moreover, modern cameras often apply scene-specific image processing, resulting in a wide range of possible ISP parameters. In this paper, we propose a modification to the ISP that allows the ISP-rendered image to be reverted back to a raw image. Our approach works by appending a fixed-sampling of the raw sensor values to all captured images. The appended raw samples comprise no more than 8 rows of pixels in the full-sized image and represent a negligible overhead given that 12–16 MP sensors typically have 3000 rows of pixels or more. The appended pixels are rendered along with the captured image to the final output. From these rendered raw samples, a reverse mapping function can be computed to undo the ISP processing. We demonstrate that this method performs almost on par with competing state-ofthe-art approaches for ISP de-rendering while offering a practical solution that is integrable to current camera ISP hardware.

Grating Spectrometry and Spatial Heterodyne Fourier Transform Spectrometry: Comparative Noise Analysis for Raman Measurements

The desire for portable Raman spectrometers is continuously driving the development of novel spectrometer architectures where miniaturisation can be achieved without the penalty of a poorer detection performance. Spatial heterodyne spectrometers are emerging as potential candidates for challenging the dominance of traditional grating spectrometers, thanks to their larger etendue and greater potential for miniaturisation. This paper provides a generic analytical model for estimating and comparing the detection performance of Raman spectrometers based on grating spectrometer and spatial heterodyne spectrometer designs by deriving the analytical expressions for the performance estimator (signal-to-noise ratio, SNR) for both types of spectrometers. The analysis shows that, depending on the spectral characteristics of the Raman light and on the values of some instrument-specific parameters, the ratio of the SNR estimates for the two spectrometers () can vary as much as by two orders of magnitude. Limit cases of these equations are presented for a subset of spectral regimes which are of practical importance in real-life applications of Raman spectroscopy. In particular, under the experimental conditions where the background signal is comparable or larger than the target Raman line and shot noise is the dominant noise contribution, the value of is, to a first order of approximation, dependent solely on the relative values of each spectrometer’s etendue and on the number of row pixels in the detector array. For typical values of the key instrument-specific parameters (e.g., etendue, number of pixels, spectral bandwidth), the analysis shows that spatial heterodyne spectrometer-based Raman spectrometers have the potential to compete with compact grating spectrometer designs for delivering in a much smaller footprint (10–30 times) levels of detection performance that are approximately only five to ten times poorer.

Effectiveness of multipass and multirow writing methods for massively parallel e-beam systems

Massively parallel electron-beam systems are equipped with a large number of beams to improve the writing throughput. It is unavoidable that some of the beams are abnormal, e.g., always on or off, spatial and temporal fluctuations of beam current, beam-positioning error, etc. A practical approach to improve the writing quality is to spread the negative effects of abnormal beams spatially. The multirow writing (MRW) was introduced, which uses each beam to expose pixels over multiple rows in each writing path minimizing the localization of pixels affected by an abnormal beam. In another method, the single-row writing (SRW), each beam exposes pixels in one row in each writing path localizing the affected pixels in a row. To spread the negative effects, especially for the single-row writing, each row of pixels may be exposed through multiple passes, i.e., multipass writing. In this study, the multirow and multipass writing methods in various combinations with the MRW and SRW are compared in terms of their effectiveness in reducing the negative effects of abnormal beams. The results from an extensive simulation study are analyzed in detail.

Cross-plane colour image encryption using a two-dimensional logistic tent modular map

Chaotic systems are suitable for image encryption owing to their numerous intrinsic characteristics. However, chaotic maps and algorithmic structures employed in many existing chaos-based image encryption algorithms exhibit various shortcomings. To overcome these, in this study, we first construct a two-dimensional logistic tent modular map (2D-LTMM) and then develop a new colour image encryption algorithm (CIEA) using the 2D-LTMM, which is referred to as the LTMM-CIEA. Compared with the existing chaotic maps used for image encryption, the 2D-LTMM has a fairly wide and continuous chaotic range and more uniformly distributed trajectories. The LTMM-CIEA employs cross-plane permutation and non-sequential diffusion to obtain the diffusion and confusion properties. The cross-plane permutation concurrently shuffles the row and column positions of pixels within the three colour planes, and the non-sequential diffusion method processes the pixels in a secret and random order. The main contributions of this study are the construction of the 2D-LTMM to overcome the shortcomings of existing chaotic maps and the development of the LTMM-CIEA to concurrently encrypt the three colour planes of images. Simulation experiments and security evaluations show that the 2D-LTMM outperforms recently developed chaotic maps, and the LTMM-CIEA outperforms several state-of-the-art image encryption algorithms in terms of security.

A hyperspectral projector for simultaneous 3D spatial and hyperspectral imaging via structured illumination.

Both 3D imaging and hyperspectral imaging provide important information of the scene and combining them is beneficial in helping us perceive and understand real-world structures. Previous hyperspectral 3D imaging systems typically require a hyperspectral imaging system as the detector suffers from complicated hardware design, high cost, and high acquisition and reconstruction time. Here, we report a low-cost, high-frame rate, simple-design, and compact hyperspectral stripe projector (HSP) system based on a single digital micro-mirror device, capable of producing hyperspectral patterns where each row of pixels has an independently programmable spectrum. We demonstrate two example applications using the HSP via hyperspectral structured illumination: hyperspectral 3D surface imaging and spectrum-dependent hyperspectral compressive imaging of volume density of participating medium. The hyperspectral patterns simultaneously encode the 3D spatial and spectral information of the target, requiring only a grayscale sensor as the detector. The reported HSP and its applications provide a solution for combining structured illumination techniques with hyperspectral imaging in a simple, efficient, and low-cost manner. The work presented here represents a novel structured illumination technique that provides the basis and inspiration of future variations of hardware systems and software encoding schemes.

Fast charge exchange recombination spectroscopy on HuanLiu-2A tokamak.

A Fast Charge eXchange Recombination Spectroscopy (CXRS) diagnostic with eight radial channels has been implemented on a HuanLiu-2A (HL-2A) tokamak with a time resolution of up to 10 kHz monitoring helium II spectra or 1 kHz monitoring carbon VI spectra. The crucial aspects of the fast CXRS are to improve the spectral intensity and the acquisition frequency. The spectral intensity has been greatly enhanced by customized fiber bundles. The main boost in optimizing the acquisition frequency is achieved by binning more pixel rows of the charge coupled device (CCD) representing one radial channel and by reducing the effective image area of the CCD. Consequently, the sawtooth oscillations of ion temperature and rotation velocity are continuously observed for the first time in the HL-2A tokamak.

Image encryption algorithm based on gradient decomposition and improved logistic map

We propose an image encryption algorithm based on gradient decomposition and an improved logistic map. The original image is first decomposed into three subimages with different gradient sizes using the gradient decomposition. The pixel position of the three subimages is then changed by applying Arnold transformation, and the random sequence generated by the improved logistic map is used to perform the XOR operation on the three subimages. Subsequently, the row pixel values of the three subimages are converted into binary sequences, and then the binary sequences are shuffled with the random sequences generated by the improved logistic map. Finally, the three subimages are obtained as the R, G, and B components of the color image to generate the final encrypted image. For image decryption, the original image can be simply restored by joining the three subimages. The experimental results show that the improved logistic map has a larger key space and better randomness compared with the classical logistic map. Furthermore, the proposed encryption scheme exhibits better robustness against various attacks than several existing encryption algorithms.

Forgery Detection and Localization of Modifications at the Pixel Level

In this paper, we present a new technique of image forgery detection. The proposed technique uses digital signatures embedded in the least significant bits of the selected pixels of each row and column. The process maintains a symmetry in the use of pixels for computing and hiding the digital signatures. Each row and column of the image symmetrically contributes to both processes, with the number of pixels per row or column used for computing the signature, and the pixels used for embedding are not equal and are asymmetric. The pixels in each row and column of an image are divided into two groups. One group contains pixels of a row or column used in the calculation of digital signatures, and the second group of pixels is used for embedding the digital signatures of the respective row or column. The digital signatures are computed using the hash algorithm, e.g., message digest five (MD5). The least significant bits substitution technique is used for embedding the computed digital signature in the least significant bits of the selected pixels of the corresponding row or column. The proposed technique can successfully detect the modification made in an image. The technique detects pixel level modification in a single or multiple pixels.

A 10-Gb/s Eye-Opening Monitor Circuit for Receiver Equalizer Adaptations in 65-nm CMOS

A 10-Gb/s on-chip 1-D eye-opening monitor (EOM) for receiver front-end equalizer boost gain adaptations is presented. The proposed EOM circuits report in real-time horizontal eye-openings using equalizer output by calculating the probability density of the waveform in the central row of pixels of the eye diagram. In addition, a novel multi-phase generator circuit with a delay gain calibration is also demonstrated. It is suitable for EOM circuits to generate a multi-phase sampling clock. The proposed 1-D-EOM circuit is included in a 10-Gb/s receiver design to verify its adaptation functions, and the circuit is implemented using the 65-nm CMOS technology. The sampling phase resolution is 1.5625 ps (where the time for one bit is 100 ps, with a total of 64 phases), and the response time is $64~\mu \text{s}$ . The total power consumption of the EOM circuit is 1.5 mW with a 1-V supply voltage, and the circuit occupies a layout area of 60 $\mu \text{m}\,\,\times $ 450 $\mu \text{m}$ . The results show that the reported horizontal eye-opening value is proportional to the value from a real eye diagram monitor from the test buffer.

Reliable and Robust Unmanned Aerial Vehicle Wireless Video Transmission

The wireless video transmission environment of unmanned aerial vehicles (UAVs) is complex and unstable given the high mobility and changeable working conditions of UAVs, which lead to burst and consecutive errors and high error rates. A compressed video stream is extremely sensitive to transmission errors, such that even a single bit error sharply degrades the video quality. Hence, we propose an intraframe pixel-row-interleaved error concealment algorithm that interleaves pixel rows to generate high similarity in different parts of a frame, thereby achieving intraframe error resilience. Subsequently, we suggest an interframe time-field-interleaved alternative motion-compensated prediction that allows for automatic error elimination and recovers at least four consecutive frames in wireless video communications. The experiments demonstrate that the proposed algorithms recover frames with excellent subjective and objective effects. Moreover, these algorithms can provide reliable and robust video transmission for UAVs.

Heterogeneity of regional inflection points from pressure-volume curves assessed by electrical impedance tomography

BackgroundThe pressure-volume (P-V) curve has been suggested as a bedside tool to set mechanical ventilation; however, it reflects a global behavior of the lung without giving information on the regional mechanical properties. Regional P-V (PVr) curves derived from electrical impedance tomography (EIT) could provide valuable clinical information at bedside, being able to explore the regional mechanics of the lung. In the present study, we hypothesized that regional P-V curves would provide different information from those obtained from global P-V curves, both in terms of upper and lower inflection points. Therefore, we constructed pressure-volume curves for each pixel row from non-dependent to dependent lung regions of patients affected by acute hypoxemic respiratory failure (AHRF) and acute respiratory distress syndrome (ARDS).MethodsWe analyzed slow-inflation P-V maneuvers data from 12 mechanically ventilated patients. During the inflation, the pneumotachograph was used to record flow and airway pressure while the EIT signals were recorded digitally. From each maneuver, global respiratory system P-V curve (PVg) and PVr curves were obtained, each one corresponding to a pixel row within the EIT image. PVg and PVr curves were fitted using a sigmoidal equation, and the upper (UIP) and lower (LIP) inflection points for each curve were mathematically identified; LIP and UIP from PVg were respectively called LIPg and UIPg. From each measurement, the highest regional LIP (LIPrMAX) and the lowest regional UIP (UIPrMIN) were identified and the pressure difference between those two points was defined as linear driving pressure (ΔPLIN).ResultsA significant difference (p < 0.001) was found between LIPrMAX (15.8 [9.2–21.1] cmH2O) and LIPg (2.9 [2.2–8.9] cmH2O); in all measurements, the LIPrMAX was higher than the corresponding LIPg. We found a significant difference (p < 0.005) between UIPrMIN (30.1 [23.5–37.6] cmH2O) and UIPg (40.5 [34.2–45] cmH2O), the UIPrMIN always being lower than the corresponding UIPg. Median ΔPLIN was 12.6 [7.4–20.8] cmH2O and in 56% of cases was < 14 cmH2O.ConclusionsRegional inflection points derived by EIT show high variability reflecting lung heterogeneity. Regional P-V curves obtained by EIT could convey more sensitive information than global lung mechanics on the pressures within which all lung regions express linear compliance.Trial registrationClinicaltrials.gov, NCT02907840. Registered on 20 September 2016.

Novel Scheme of Reversible Watermarking With a Complementary Embedding Strategy

In this paper, a new scheme of reversible watermarking is proposed using a complementary embedding strategy in the spatial domain. The proposed scheme consists of two stages: horizontal direction embedding and vertical direction embedding. A complementary embedding strategy is designed to increase the embedding capacity and decrease the distortion of the watermarked image in the vertical direction embedding. Specifically, in the horizontal direction, the proposed scheme embeds one secret data bit by increasing values of pixels in even rows and decreasing values of pixels in odd rows by one. In the vertical direction, it embeds another secret data bit by decreasing values of pixels in even rows and increasing values of pixels in odd rows by one. In addition, a histogram shrinkage technique is adopted to prevent overflow and underflow problems. Experimental results demonstrate that the proposed reversible watermarking scheme outperforms state-of-the-art methods in terms of both embedding capacity and watermarked image quality.

Fast and Resource-Efficient Hardware Implementation of Modified Line Segment Detector

Lines are significant features enclosing high-level information in an image. The line segment Detector (LSD) Algorithm with low error rate is a widely used method to extract lines in images effectively and accurately. However, the algorithm on PC performs too costly both in time and resources for the real-time video processing. This paper provides a fast and resource-efficient hardware implementation solution for a modified LSD algorithm on Field Programmable Gate Arrays (FPGA) for real-time line detection. The task-level pipeline structures are exploited fully in a stream process mapped to the hardware architecture free of frame buffer. Our proposed hardware implementation processes in a stream-in–stream-out manner with little consumption of the on-chip block RAM to store intermediate values. We first employ hardware Gaussian filter and adjust Canny edge detection to obtain an edge map at single-pixel width. Then, a novel structure of region growing model based on dynamic rooted tree is used to detect line segment regions accurately with a latency of only a few rows of pixels. The low cost in time, on-chip resources, and power consumption makes our proposed algorithm suitable for portable real-time streaming video processing applications using line segment features, such as Lane departure warning systems. It can also be applied in real-time machine vision systems that use line segments information for further recognition or stereo correspondence and many others. The proposed algorithm is synthesized and tested on XC7Z020 FPGA with high reliability, accuracy speed, and low cost in both resources and energy.

A Novel Algorithm Based on the Pixel-Entropy for Automatic Detection of Number of Lanes, Lane Centers, and Lane Division Lines Formation.

Lane detection for traffic surveillance in intelligent transportation systems is a challenge for vision-based systems. In this paper, a novel pixel-entropy based algorithm for the automatic detection of the number of lanes and their centers, as well as the formation of their division lines is proposed. Using as input a video from a static camera, each pixel behavior in the gray color space is modeled by a time series; then, for a time period , its histogram followed by its entropy are calculated. Three different types of theoretical pixel-entropy behaviors can be distinguished: (1) the pixel-entropy at the lane center shows a high value; (2) the pixel-entropy at the lane division line shows a low value; and (3) a pixel not belonging to the road has an entropy value close to zero. From the road video, several small rectangle areas are captured, each with only a few full rows of pixels. For each pixel of these areas, the entropy is calculated, then for each area or row an entropy curve is produced, which, when smoothed, has as many local maxima as lanes and one more local minima than lane division lines. For the purpose of testing, several real traffic scenarios under different weather conditions with other moving objects were used. However, these background objects, which are out of road, were filtered out. Our algorithm, compared to others based on trajectories of vehicles, shows the following advantages: (1) the lowest computational time for lane detection (only 32 s with a traffic flow of one vehicle/s per-lane); and (2) better results under high traffic flow with congestion and vehicle occlusion. Instead of detecting road markings, it forms lane-dividing lines. Here, the entropies of Shannon and Tsallis were used, but the entropy of Tsallis for a selected q of a finite set achieved the best results.

Object Shape Approximation and Contour Adaptive Depth Image Coding for Virtual View Synthesis

A depth image provides partial geometric information of a 3D scene, namely the shapes of physical objects as observed from a particular viewpoint. This information is important when synthesizing images of different virtual camera viewpoints via depth-image-based rendering (DIBR). It has been shown that depth images can be efficiently coded using contour-adaptive codecs that preserve edge sharpness, resulting in visually pleasing DIBR-synthesized images. However, contours are typically losslessly coded as side information, which is expensive if the object shapes are complex. In this paper, we pursue a new paradigm in depth image coding for color-plus-depth representation of a 3D scene: in a pre-processing step, we pro-actively simplify object shapes in a depth and color image pair to reduce depth coding cost, at a penalty of a slight increase in synthesized view distortion. Specifically, we first mathematically derive a distortion upper-bound proxy for 3DSwIM—a quality metric tailored for DIBR-synthesized images. This proxy reduces inter-dependency among pixel rows in a block to ease optimization. We then approximate object contours via a dynamic programming algorithm to optimally tradeoff coding the cost of contours using arithmetic edge coding with our proposed view synthesis distortion proxy. We modify the depth and color images according to the approximated object contours in an inter-view consistent manner. These are then coded, respectively, using a contour-adaptive image codec based on graph Fourier transform for edge preservation and High Efficiency Video Coding (HEVC) intra. Experimental results show that by maintaining sharp but simplified object contours during contour-adaptive coding, for the same visual quality of DIBR-synthesized virtual views, our proposal can reduce depth image coding rate by up to 22% in 3DSwIM and 42% in peak signal-to-noise ratio compared with alternative coding strategies, such as HEVC intra.

Clinical Practicability of a Newly Developed Real-time Digital Kymographic System

A digital kymogram shows real images of vocal fold vibration. However, DKG is difficult to use in clinical practice because the recorded image cannot be seen instantaneously after examination, as considerable encoding time is required to visualize a digital kymogram. In addition, frame-by frame analysis should be implemented to evaluate high-speed videoendoscopy data, but is time- and labor-intensive. The purpose of the study was to validate the clinical practicability of a real-time multislice digital kymographic system developed by the authors. We analyzed the promptness and accuracy of the examination before and after intracordal injections in patients with unilateral vocal fold paralysis. To assess the clinical applicability of this system, six patients with unilateral vocal fold paralysis were selected. Real-time DKG was performed before and immediately after intracordal injection. We observed changes in the digital kymogram after the intracordal injection. Using this system, 10 scanning lines and up to five vertical pixel row could be obtained in real time, and the maximum acquisition time for the DKG image was 10 seconds. A digital kymogram of the patients could be instantaneously acquired, and whether the intracordal injection was appropriate or not. This article is the first validation study after the development of the real-time multislice digital kymographic system. Our system may be a promising tool in clinical practice for immediate assessment of the vibratory patterns of the vocal cords. More research is necessary for further clinical validation.

Laser line scan underwater imaging by complementary metal–oxide–semiconductor camera

This work employs the complementary metal–oxide–semiconductor (CMOS) camera to acquire images in a scanning manner for laser line scan (LLS) underwater imaging to alleviate backscatter impact of seawater. Two operating features of the CMOS camera, namely the region of interest (ROI) and rolling shutter, can be utilized to perform image scan without the difficulty of translating the receiver above the target as the traditional LLS imaging systems have. By the dynamically reconfigurable ROI of an industrial CMOS camera, we evenly divided the image into five subareas along the pixel rows and then scanned them by changing the ROI region automatically under the synchronous illumination by the fun beams of the lasers. Another scanning method was explored by the rolling shutter operation of the CMOS camera. The fun beam lasers were turned on/off to illuminate the narrow zones on the target in a good correspondence to the exposure lines during the rolling procedure of the camera’s electronic shutter. The frame synchronization between the image scan and the laser beam sweep may be achieved by either the strobe lighting output pulse or the external triggering pulse of the industrial camera. Comparison between the scanning and nonscanning images shows that contrast of the underwater image can be improved by our LLS imaging techniques, with higher stability and feasibility than the mechanically controlled scanning method.

Entire frame image display employing monotonic convergent nonnegative matrix factorization

The average life spans of light-emitting diodes (LEDs) used in organic light-emitting diode displays are negatively influenced by high current operation in short duty cycles. Since the time average brightness of a pixel LED is a function only of the time integral of the delivered current, it is desirable to achieve brightness by adopting pixel addressing schemes that employ long duty cycles. Conventional addressing methods which cannot operate more than one row of pixels at a time inherently have very short duty cycles. We solve the problem by proposing entire frame addressing, made possible by a new image factorization called monotonic-nonnegative matrix factorization (M-NNMF). Using M-NNMF, we develop a converging image series representation of an arbitrary nonnegative matrix (image). Each element of the series has unit rank, which allows it to drive an entire frame simultaneously. Each application of the M-NNMF algorithm produces a dominant unit rank component for the series, and a residue image of higher rank, the input to the next iteration. We drive the display with these unit rank components, called sub-frames, each for a duration proportional to its energy. The sum of sub-frames approximates the original image and provides the same visual effect, due to inherent perceptual integration. M-NNMF, more efficient and less time complex compared to existing NNMF algorithms, is our primary contribution in this paper and is likely to find applications in many other situations. We also obtain an even faster converging series with a randomized version of M-NNMF. The proposed approach of entire frame image display is demonstrated on a wide variety of images.