A method for fusing a pair of images in the JPEG domain

We present an efficient algorithm for fusing a pair of long- and short-exposure images that work in the JPEG domain. The algorithm uses the spatial frequency analysis provided by the discrete cosine transform within JPEG to combine the uniform regions of the long-exposure image with the detailed regions of the short-exposure image, thereby reducing noise while providing sharp details. Two additional features of the algorithm enable its implementation at low cost, and in real time, on a digital camera: the camera’s response between exposures is equalized with a look-up table implementing a parametric sigmoidal function; and image fusion is performed by selective overwriting during the JPEG file save operation. The algorithm requires no more than a single JPEG macro-block of the short-exposure image to be maintained in RAM at any one time, and needs only a single pass over both long- and short-exposure images. The performance of the algorithm is demonstrated with examples of image stabilization and high dynamic range image acquisition.     

Evaluation of visual saliency analysis algorithms in noisy images

Most existing visual saliency analysis algorithms assume that the input image is clean and does not have any disturbances. However, this situation is not always the case. In this paper, we provide an extensive evaluation of visual saliency analysis algorithms in noisy images. We analyze the noise immunity of saliency analysis algorithms by evaluating the performances of the algorithms in noisy images with increasing noise scales and by studying the effects of applying different denoising methods before performing saliency analysis. We use 10 state-of-the-art saliency analysis algorithms and 7 typical image denoising methods on 4 eye fixation datasets and 2 salient object detection datasets. Our experiments show that the performances of saliency analysis algorithms decrease with increasing image noise scales in general. An exception is that the nonlinear features (NF) integrated algorithm shows good noise immunity. We also find that image denoising methods can greatly improve the noise immunity of the algorithms. Our results show that the combination of NF and Median denoising method works best on eye fixation datasets and the combination of saliency optimization (SO) and color block-matching and 3D filtering (C-BM3D) method works best on salient object detection datasets. The combination of SO and Average denoising method works best for applications wherein time efficiency is a major concern for both types of datasets.     

Determining the parameters of emotion by analyzing environmental images captured by a mobile device

Multimedia Tools and Applications - This paper proposes a method to quantitatively extract human emotions by analyzing images of the surrounding environment captured by a smartphone camera in real...     

Dynamic compensation by fusing a high-speed actuator and high-speed visual feedback with its application to fast peg-and-hole alignment

This paper presents a dynamic compensation concept to grapple with the dynamic defects of a traditional robot arm, especially while performing high-speed endpoint regulations. The proposed high-speed dynamic compensation concept offers a new point of view for cooperating with a traditional manipulator to realize highly dexterous performance of manipulations. The concept is realized through adoption of a high-speed light-weight actuator as well as endpoint closed loop configured high-speed cameras. The dynamic compensation is analyzed experimentally with 1000 Hz visual feedback and a high-speed finger for a robot arm in the case of one degree of freedom. The advantage of the proposed approach is that the modeling for the robot system’s dynamics is not needed, whereas it is necessary and trivial in order to realize high-speed regulations by traditional approaches. Thus, the control issue becomes easier with the proposed approach. As an application for this concept, fast peg-and-hole alignment with large position and attitude uncertainty is studied. The alignment algorithm is based on a visual compliance strategy. Alignment experiments show that with the proposed concept of dynamic compensation as well as visual compliant motion control, robust and fast convergence was realized for most cases.     

Observability analysis of rotation estimation by fusing inertial and line-based visual information: A revisit

This note presents a simple approach to the observability analysis of the rotation estimation using line-based dynamic vision and inertial sensors. The problem was originally raised and formulated in Rehbinder, and Ghosh [2003. Pose estimation using line-based dynamic vision and inertial sensors. IEEE Transactions on Automatic Control, 48(2), 186-199.] where the unobservable subgroup was derived using complex matrix manipulations. By solving linear quaternion equations and using set operations, we not only successfully obtain the same result but also naturally extend it for the case with linearly dependent lines. The development in this note is more straightforward and gives rise to a clearer picture of the problem.     

BFCNet: a CNN for diagnosis of ductal carcinoma in breast from cytology images

Pattern Analysis and Applications - Fine Needle Aspiration Cytology (FNAC) is a quick and minimally invasive technique used to diagnose breast cancer, specifically ductal carcinoma. The incidence...     

Data hiding in grayscale images by dynamic programming based on a human visual model

A new method for data hiding in grayscale images based on a human vision model with distortion-minimizing capabilities is proposed. Each of the eight bit planes of an input grayscale image is viewed as a binary image, into which message data are embedded horizontally. Two optimization techniques, namely, block pattern coding and dynamic programming, are proposed for image distortion minimization. Experimental results show good performs of the proposed method.     

On the security of a visual cryptography scheme for color images

Hou [Visual cryptography for color images, Pattern Recognition 36 (2003) 1619-1629] proposed a four-share visual cryptography scheme for color images. The scheme splits a dithered eight-color secret image into four shares: the black mask and other three shares. It was claimed that without knowing the black mask, no information about the secret image can be obtained even if all the other three shares are known. In this paper, we show that this may be true for a few specific two-color secret images only. In all other cases, however, security cannot be guaranteed. We show that an attacker can compromise a randomly chosen two-color secret image from any two of the other three shares with probability by completely recovering the shape and pattern of the secret image. The advantage will increase to if all the three shares are known. If the secret image has three or four colors, we show that the attacker can compromise it with probability and , respectively. Finally, we show that our technique can be extended to compromising secret images with more than four colors.     

Learning invariance from natural images inspired by observations in the primary visual cortex

The human visual system has the remarkable ability to largely recognize objects invariant of their position, rotation, and scale. A good interpretation of neurobiological findings involves a computational model that simulates signal processing of the visual cortex. In part, this is likely achieved step by step from early to late areas of visual perception. While several algorithms have been proposed for learning feature detectors, only few studies at hand cover the issue of biologically plausible learning of such invariance. In this study, a set of Hebbian learning rules based on calcium dynamics and homeostatic regulations of single neurons is proposed. Their performance is verified within a simple model of the primary visual cortex to learn so-called complex cells, based on a sequence of static images. As a result, the learned complex-cell responses are largely invariant to phase and position.     

Mapping daily leaf area index at 30 m resolution over a meadow steppe area by fusing Landsat,Sentinel-2A and MODIS data

ABSTRACT

The leaf area index (LAI) is a key vegetation canopy structure parameter and is closely associated with vegetation photosynthesis, transpiration, and energy balance. Developing a landscape-scale LAI dataset with a high temporal resolution (daily) is essential for capturing rapidly changing vegetation structure at field scales and supporting regional biophysical modeling efforts. In this study, two daily 30 m LAI time series from 2014 to 2016 over a meadow steppe site in northern China were generated using a spatial and temporal adaptive re?ectance fusion model (STARFM) combined with an LAI retrieval radiative transfer model (PROSAIL). Gap-filled Landsat 7, Landsat 8 and Sentinel-2A surface reflectance (SR) images were used to generate fine-resolution LAI maps with the PROSAIL look-up table method. Two daily 500 m moderate-resolution imaging spectroradiometer (MODIS) LAI product-the existing MCD15A3H LAI product and one was generated from the MCD43A4 SR product and the PROSAIL model, were used to provide temporally continuous LAI variations. The STARFM model was then used to fuse the fine-resolution LAI maps with the two 500 m LAI products separately to generate two daily 30 m LAI time series. Both results were assessed for three types of pasture (mowed pasture, grazing pasture, and fenced pasture) using ground measurements from 2014–2015. The results showed that the PROSAIL-generated LAI maps all exhibited a high accuracy, and the root mean squared errors (RMSEs) for the Landsat 7 LAI and Landsat 8 LAI compared to the ground-measured LAI were 0.33 and 0.28 respectively. The Landsat LAI maps also showed good agreement and similar spatial patterns with the Sentinel-2A LAI with mean differences between ± 0.5. The MCD43A4_PROSPECT LAI product exhibited similar seasonal variability to the ground measurements and to the Landsat and Sentinel-2A LAIs, and these data are also smoother and contain fewer noisy points than the gap-filled MCD15A3H LAI product. Compared to the ground measurements, the daily 30 m LAI time series fused from the fine-resolution LAI maps and PROSPECT generated MODIS LAI product demonstrated better performance with an RMSE of 0.44 and a mean absolute error (MAE) of 0.34, which is an improvement from the LAI time series fused from the fine-resolution LAI maps and the existing MCD15A3H LAI product (RMSE of 0.56 and MAE of 0.42). The latter dataset also exhibited abnormal temporal fluctuations, which may have been caused by the interpolation method. The results also demonstrated the very good performance of the STARFM model in grazing and mowed pasture with homogeneous surfaces compared to fenced pasture with smaller patch sizes. The Sentinel-2A data offers increased landscape vegetation observation frequency and provides temporal information about canopy changes that occur between Landsat overpass dates. The scheme developed in this study can be used as a reference for regional vegetation dynamic studies and can be applied to larger areas to improve grassland modeling efforts.     

Measurement of information processing load and visual load on a dynamic information processing task

A dynamic visual information processing task was designed to investigate time-based and intensity-based factors on an operator's information processing load as measured by reaction time, pupil diameter, and eye movement parameters. The time-based factor was manipulated by the target rate and scanning rate while the intensity-based factor was manipulated by the difference between a simple reaction task and a physical matching (choice reaction) task. Nine participants tracked the scanning line at two different scanning rates and were required to respond to two designated targets presented singly at two different temporal frequencies. The results indicated that task difficulty (the intensity-based factor) had a significant effect on the reaction time. Target rate and scanning rate were integrated as one time-based factor in terms of three sweeping angles. The time-based factor was found to have a significant effect on the fixation time, saccade amplitude, fixation frequency, eye movement speed, reaction time and hit rate. No interaction effect was found between time-based and intensity-based factors. The time pressure (defined by the time required divided by the time available) based on a model human processor was positively related to scanning rate, target rate and task difficulty. It was found to be the most objective and reliable if time required can be reliably predicted based on a predictive model approach.     

Terrain resources surveys by visual monoscopic and stereoscopic interpretation of FGEOS images

Abstract

Monoscopic and stereoscopic interpretation of FGEOS (First Generation Earth Observation Satellites) images were applied comparatively in order to divide the region of Central Peloponnesos (Greece) into physiographic units for thematic mapping concerning geomorphology, soils and land use. A stereo pair of Landsat-1 black and white prints and a false-colour print at 1:250000 scale were used in order (1) to construct a reconnaissance physiographic map, (2) to construct a land use map and (3) to reconsider the monoscopic interpretation techniques, because of the newly-developed SPOT stereo capability and 10 × 10 m ground resolution. The known problems reported from the FGEOS 79 × 79 m resolution could reduce the effectiveness of any interpretation method. However the results show that the stereoscopic interpretation and physiographic analysis of satellite images improve the accuracy of boundaries and increase the number of mapping units, and consequently they are expected to minimize field work, laboratory analysis, field staff and the total cost of surveying.     

Vegetation classification by satellite image processing in a dry area of north-eastern Syria

As vegetation classification on the highly diverse rangeland is an inevitable procedure in evaluating total forage resources and assessing human impact in large areas, a supervised classification was conducted by satellite image processing using geocoded bands 2, 3 and 4 of Landsat 5 Thematic Mapper (TM) images, dated 13 April 1994 in the Abdal Aziz Mountain study area in northeastern Syria. The rangeland was categorized into six classes according to the plant contacts of dominant shrubs (Artemisia herba-alba and Noaea mucronata) and herbaceous plants. In addition, cultivated fields were categorized into two classes. An average classification accuracy of 85% in the supervised processing and an average ground verification accuracy of 81% on the Landsat-estimated vegetation classes were achieved for the rangeland. These show that a 30m X 30m resolution of the Landsat TM image had the ability to recognize vegetation at six sub-divided community levels, and the successful classification was conducted on the whole rangeland of the study area. The distinctive feature of this work is that this vegetation classification using Landsat TM images was accomplished at the level of classifying a A. herba-alba and N. mucronata dominant community into six sub-community classes. This detailed vegetation classification was conducted with the final aim of forage resource estimation and human impact assessment in mind.     

Time stress and the processing of visual displays.

Selecting the appropriate display format for time-constrained tasks is the focus of the research presented in this paper. The effect of time stress on operator performance was assessed by manipulating the time available to process the display. Twenty people were trained as operators and instructed to identify the state of a system using either a digital display or a polygon display. Participants were required to reach a prespecified criterion in training and were then tested under time-constrained conditions. Time constraints were set at 100%, 50%, and 25% of each person's mean unpaced response times obtained during training. Results showed that response to the time constrained conditions was significantly affected by uncertainty and the type of display format. Discussion focuses on the effects of time stress on performance and the selection of displays for time-constrained tasks.     

视觉传感机理与数据处理进展

传统视觉感知以RGB光学图像和视频图像为主要数据源,借助计算机视觉的发展取得了巨大成功。然而,传统RGB光学成像也存在着光谱、采样速度、测量精度、可工作条件等方面的限制。近年来,视觉感知的新机理和新数据处理技术的迅速发展,为提升感知和认知能力带来了重大机遇;同时,也具有重要的理论价值和重大应用需求。本文围绕激光扫描、水声声呐成像、新体制动态成像、计算成像、位姿感知等研究方向,综述发展现状、前沿动态、热点问题和发展趋势。当前,在视觉传感研究领域,国内研究机构和团队在数据处理和应用方面取得了显著进展。整体上,国内依然要落后于欧美日等先进国家,尤其是在相关硬件的研制方面。最后,给出了发展趋势与展望,以期为相关研究者提供参考。     

Practitioner perceptions of Open Source software in the embedded systems area

There is a growing body of research to show that, with the advent of so-called professional Open Source, attitudes within many organisations towards adopting Open Source software have changed. However, there have been conflicting reports on the extent to which this is true of the embedded software systems sector—a large sector in Europe. This paper reports on attitudes towards Open Source software within that sector. Our results show a high level of acceptance of Open Source products with large, well established communities, and not only at the level of the operating system. Control over the software is seen as fundamentally important. Other key perceptions with Open Source are an easing of long-term maintenance problems and ready availability of support. The classical strengths of Open Source, namely mass inspection, ease of conducting trials, longevity and source code access for debugging, were at the forefront of thinking. However, there was an acknowledgement that more guidelines are needed for assessing Open Source software and incorporating it into products.     

Evaluation of parameters in nonlinear models by the least squares method

An iterative method for the nonlinear weighted least squares parameter estimation when all experimental data are subject to random errors has been developed. The method does not require any linearization, satisfies Deming's criteria and provides the parameter variance-covariance matrix.     

Adaptive sampling in measuring traffic parameters in a computer network using a fuzzy regulator and a neural network

Adaptive sampling using a neural network and a fuzzy regulator is described as applied to computer network traffics. The objective of this approach is to maximally reduce the amount of data to be processed with preservation of acceptable measurement accuracy. The results of experimental verification of sampling efficiency are also presented that are based on the traffic data archive of a real computer network. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 46–54, May–June 2008.     

Predicting impact of growth of a metropolitan area on the transportation system of one of its cities

This paper provides a simple methodology to analyze the effects of future growth and changes in a metropolitan area on the transportation network of a single city inside the area. In order to present the analysis process, the impact of projected regional employment and population growth on the transportation network of one suburban city in Dallas-Fort Worth metropolitan area is investigated. One of the main features of this approach is the use of the major accesses to the city to divide the rest of metropolitan area into few major zones or origin and destination which allow easier manipulation of data.