High precision and fast disparity estimation via parallel phase correlation hierarchical framework

Videocapillaroscopy is a convenient and non-invasive method of blood flow parameters recovery in the capillaries. Capillaries position can vary at recorded video sequences due to the registration features of capillary blood flow. Stabilization algorithm of video capillary blood flow based on phase correlation is proposed and researched. This algorithm is compared to the known algorithms of video frames stabilization with full-frame superposition and with key points. Programs, based on discussed algorithms, are compared under processing the experimentally recorded video sequences of human capillaries and under processing of computer-simulated sequences of video frames with the specified offset. The full-frame superposition algorithm provides high quality of stabilization; however, the program based on this algorithm requires significant computational resources. Software implementation of the algorithm based on the detection of the key points is characterized by good performance, but provides low quality of stabilization for video sequences capillary blood flow. Algorithm based on phase correlation method provides high quality of stabilization and program realization of this algorithm requires minimal computational resources. It is shown that the phase correlation algorithm is the most useful for stabilization of video sequences for capillaries blood flow. Obtained findings can be used in the software for biomedical diagnostics.

This article describes the aircraft image recognition system implemented using the phase correlation technique in Matlab environment. The phase correlation is computed by using the normalized cross-power spectrum between the database and the template test image. The main objective of this article is to develop methods for static analysis of aircraft images. An unknown fighter aircraft is recognized by comparing its static image with those from a database of images of aircraft. This work is a research initiative involving the use of image processing techniques to detect three-dimensional (3D) aircraft object based on their 2D images, providing feedback information for strategic purposes. The phase correlation technique is found to give a better recognition result for the set of database and test images considered, compared with the invariant moments. The phase correlation method is also used in other areas such as image registration. Aircraft images used include those from AeroIndia 2011 held at Bangalore, India.

Analyzing and interpreting of thermograms have been increasingly employed in the diagnosis and monitoring of diseases thanks to its non-invasive, non-harmful nature and low cost. This paper presents a thermal image analysis system based on image registration for morphoea disease diagnosis. A novel system is proposed to improve the diagnosis and monitoring of morphoea based on integration with the published lines of Blaschko. In this application, image registration based on global and local registration methods are found inevitable. A modified normalized gradient cross-correlation (NGC) method to reduce large geometrical differences between two multimodal images of different subjects that are represented by smooth gray edge maps is proposed for the global registration approach. It is shown in this paper that the NGC method outperforms phase correlation (PC) method by a lower rate of misregistration. This demonstrates that by using the gradients of the gray edge maps, the performance of the PC based image registration method can be greatly improved.

Frequency domain subpixel registration using HOG phase correlation

In this letter, an improved phase correlation (PC) method based on 2-D plane fitting and the maximum kernel density estimator (MKDE) is proposed, which combines the idea of Stone's method and robust estimator MKDE. The proposed PC method first utilizes a vector filter to minimize the noise errors of the phase angle matrix and then unwraps the filtered phase angle matrix by the use of the minimum cost network flow unwrapping algorithm. Afterward, the unwrapped phase angle matrix is robustly fitted via MKDE, and the slope coefficients of the 2-D plane indicate the subpixel shifts between images. The experiments revealed that the improved method can effectively avoid the impact of outliers on the phase angle matrix during the plane fitting and is robust to aliasing and noise. The matching accuracy can reach 1/50th of a pixel using simulated data. The real image sequence tracking experiment was also undertaken to demonstrate the effectiveness of the proposed PC method with a registration accuracy of root-mean-square error better than 0.1 pixels.

Subpixel translation estimation using phase correlation is a fundamental task for numerous applications in the remote sensing community. The major drawback of the existing subpixel phase correlation methods lies in their sensitivity to corruption, including aliasing and noise, as well as the poor performance in the case of practical remote sensing data. This paper presents a novel subpixel phase correlation method using singular value decomposition (SVD) and the unified random sample consensus (RANSAC) algorithm. In the proposed method, SVD theoretically converts the translation estimation problem to one dimensions for simplicity and efficiency, and the unified RANSAC algorithm acts as a robust estimator for the line fitting, in this case for the high accuracy, stability, and robustness. The proposed method integrates the advantages of Hoge's method and the RANSAC algorithm and avoids the corresponding shortfalls of the original phase correlation method based only on SVD. A pixel-to-pixel dense matching scheme on the basis of the proposed method is also developed for practical image registration. Experiments with both simulated and real data were carried out to test the proposed method. In the simulated case, the comparative results estimated from the generated synthetic image pairs indicate that the proposed method outperforms the other existing methods in the presence of both aliasing and noise, in both accuracy and robustness. Moreover, the pixel locking effect that commonly occurs in subpixel matching was also investigated. The degree of pixel locking effect was found to be significantly weakened by the proposed method, as compared with the original Hoge's method. In the real data case, experiments using different bands of ZY-3 multispectral sensor-corrected images demonstrate the promising performance and feasibility of the proposed method, which is able to identify seams of the image stitching between sub-charge-coupled device units.

The relationship between visual comfort and parallax distribution for stereoscopic HDTV has been studied. In this study, we first examined a method for measuring this parallax distribution. As it is important to understand the characteristics of the distribution in a frame or temporal changes of the characteristics, rather than having detailed information on the parallax at every point, we propose a method to measure the parallax based on the phase correlation. It includes a way of reducing the measurement error depending on the phase correlation method. The method was used to measure stereoscopic HDTV images with good results. Secondly, we conducted a subjective evaluation test of visual comfort and sense of presence using 48 different stereoscopic HDTV pictures, and compared the results with the parallax distributions in these pictures measured by the proposed method. The comparison showed that the range of parallax distribution and the average parallax distribution significantly affect visual comfort when viewing stereoscopic HDTV images. It is also suggested that the range of parallax distribution in many of the images that were judged comfortable to view is located within approximate 0.3Diopter.

This paper shows that the accuracy of azimuth angle measurement for an interferometric localization system used to locate tags in its Line-of-Sight (LoS) can be improved by exploiting Impulse Radio-Ultra WideBand (IR-UWB) signals and without increasing the frequency bandwidth. This solution uses a Phase Correlation (PC) method, initially applied for Continuous Wave (CW) signals, adapted for Ultra WideBand (UWB) pulse signals. The obtained results are compared to those computed by a classical Energy Detection (ED) method where it becomes impossible to estimate azimuth angles for tag positions close to the orthogonal centered axis of the localization system baseline.

When using fixed-window phase correlation (PC) to estimate the disparity of stereo images, the precision is usually rather poor due to large depth differences of scenes and noise, and this problem is specially severe when using unmanned aerial vehicle (UAV) image pairs to extract the digital elevation model of mountain land. To tackle this problem, this paper proposes a hierarchical and adaptive PC, which includes three steps: First, PC with the initialized window is performed to coarsely estimate a disparity value, along with the peak of the Dirichlet function for each pixel; then, an additional round of PC is performed for each pixel using the window of smaller size and with being guided by the coarsely estimated disparity; finally, the previous two steps are iteratively performed until convergence. In particular, using the peak of the Dirichlet function of each pixel in step two, we can drop out the influence of dramatically changing areas such as river; moreover, the scheme can minimize the influence of boundary overreach. The novel scheme has been tested on a large number of UAV images captured at mountainous regions in southwest China, showing that the proposed method is superior to the state-of-the-art methods, especially in handling UAV images of the high mountains and rivers.

One way to identify human faces is by using facial features or facial patterns based on visible images. However, this approach depends on the lighting conditions. In a poor illumination environment, it is difficult to recognize the face images. Thermal images do not rely on the illumination condition; thus can overcome this problem. Unlike the visible image, the thermal images lack visual information. Therefore, matching between the thermal and visible images (cross-spectral matching) is vital in face recognition. This paper proposed a phase correlation method, namely phase-only correlation (POC) and band-limited POC (BLPOC), for a cross-spectral matching of face images. First, the Fourier transform was applied to face images in both spectral domains, and the phase correlation between the two images was calculated. The experimental results showed that, from 100 visible and thermal image (acquired by FLIR C2 camera) pairs, the BLPOC resulted in significant correlation values compared to POC.

The Unmanned Aerial System (UAS) is more and more widely used in modern warfare, and its problem of support mode is becoming more and more prominent. The support mode of UAS refers to the standard mode to ensure the operation and maintenance of UAS which mainly composed of maintenance level, organization structure and contractor logistical support system. In most cases the support mode of UAS draws lesson from manned vehicles’. For the research and application of support model of UAS is relatively lagging, for example, the division of maintenance level is not clear; the allocation of support resources is redundant; military force lacks maintenance support capability; logistical support professional setting is not reasonable; the contractor logistics support system is not normative. So, there is no a set of effective, reasonable and normative support mode to support the operation and maintenance of UAS, resulting in the operational readiness of UAS is not high and maintenance process wastes a lot of manpower and material and money, which greatly restricts the operation and development of UAS. Combined with the UAS support requirements and features under the military trade, this paper analyses the status of the redundant and inefficient support mode. Aiming at these problem, a new support model of UAS will be researched from three aspects including the allocation of maintenance level, the adjustment of military maintenance organization structure, and the establishment of contractor logistical support system. By applying the new support mode to user, the operation and support of UAS will be more effective and reasonable which will greatly promote the development of UAS.

The research target is the technology of applying liquid agents used in crop growing by using an unmanned quadcopter-type aerial system. Spring wheat was treated by using the XAG P100 quadcopter with centrifugal nozzles. The coverage area of a plant leaf with a sprayed liquid was taken as an optimization criterion. The influence of the following factors was evaluated: flight altitude, flight speed, drop diameter, application rate, and the distance from the axis of the flight path to the material selection point (operating width). The effectiveness of spraying was evaluated by the surface area of the wheat leaf sprayed with the solution using DropSight® technology. A coloring agent that fluoresces in the ultraviolet spectrum was added to the water. The leaves of the plants covered with the solution after the flight of the quadcopter with the nozzles turned on were collected and placed in a special chamber equipped with an ultraviolet lamp. Photographs of the leaves were taken from both sides - top and bottom. The obtained photographs were processed using special software that evaluated the area of the leaf covered with the solution as a percentage of the total area. Based on the result of the experiment, a regression equation was obtained, the significance of the factors was assessed, and the possible theoretical maximum of the optimization criterion was obtained. The most significant of the five factors were two: the rate of the agent and the distance from the axis of the flight path to the sampling point. The greatest uniformity of the solution distribution over the operating width is achieved with the minimum values of all factors at their levels used in the experiment. The values of the factors at which the maximum value of the optimization criterion is achieved are given.

For pt.II see ibid., vol.16, no.16, p.2871 (1983). The circular orbit method (COM) which has been proposed in parts I and II is extended to coupled oscillator systems. The authors also develop a new method (they call it the phase correlation method (PCM)) which enables one to calculate a particular state manifold. They apply the COM and PCM to calculations of state energy in the Henon-Heiles and Barbanis potential systems and examine the efficiency of them.

We present a new image registration algorithm that employs Phase Correlation Method (PCM) to align rotated and translated 3D images. First, we use PCM and cylindrical coordinate transform to estimate rotation angle that aligns two images that are mutually rotated around known axis. An improvement of this technique is given to eliminate influence of noise and image differences in non-ideal conditions. Finally, an iterative optimization procedure is proposed which uses these techniques in rigid body registration tasks. We study the performance of the algorithm in simulated experiment on MRI brain image.KeywordsImage RegistrationPhase CorrelationImage Registration MethodImage Registration AlgorithmCorrelation SurfaceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

As a result of the FAA Modernization and Reform Act of 2012, Unmanned Aerial Systems (UAS) are expected to be integrated into the National Airspace System (NAS) by 2015. Several human factors challenges need to be addressed before UAS can safely and routinely fly in the NAS with manned aircraft. Perhaps the most significant challenge is for the UAS to be non-disruptive to the air traffic management system. Another human factors challenge is how to provide UAS pilots with intuitive traffic information in order to support situation awareness (SA) of their airspace environment as well as a see-and-avoid capability comparable to manned aircraft so that a UAS pilot could safely maneuver the aircraft to maintain separation and collision avoidance if necessary. A simulation experiment was conducted to examine baseline compliance of UAS operations in the current airspace system. Researchers also examined the effects of introducing a Cockpit Situation Display (CSD) into a UAS Ground Control Station (GCS) on UAS pilot performance, workload and situation awareness while flying in a positively controlled sector. Pilots were tasked with conducting a highway patrol police mission with a Medium Altitude Long Endurance (MALE) UAS in L.A. Center airspace with two mission objectives: 1) to reroute the UAS when issued new instructions from their commander, and 2) to communicate with Air Traffic Control (ATC) to negotiate flight plan changes and respond to vectoring and altitude change instructions. Objective aircraft separation data, workload ratings, SA data, and subjective ratings regarding UAS operations in the NAS were collected. Results indicate that UAS pilots were able to comply appropriately with ATC instructions. In addition, the introduction of the CSD improved pilot SA and reduced workload associated with UAS and ATC interactions.