Weiping Yang

The application of difference method to dim point target detection in infrared images

This paper deals with the detection of dim point targets in infrared images. Dim point targets detection is always a difficulty in information processing. Researchers have proposed many effective methods; this paper introduces a new method. Whereas difference method has obtained good result in one dimensional signal processing, this paper manages to apply it to two dimensional signal processing, that is to say, dim point targets detection in infrared images of low SNR. The image background is color noise, and its column correlation is strong. So, ordinary methods probably lose the true targets because of the strong color noise, but unlike them, difference method can overcome this shortcoming, it can eliminate correlation noise and enhance useful information, finally pick out the probable targets from noise background. In the paper, the method was given a more extensive account. In order to improve the detection effect, we utilize prefilter. The prefilter is realized by the alpha filter. Because the same targets have same location in more than three frames, using alpha filter can utilize the information of adjacent frames, increase the SNR of the raw data and reduce the noise of the images.<<ETX>>

A real-time gray projection algorithm for electronic image stabilization

Electronic digital image stabilization technique plays important roles in video surveillance or object acquisition. Researchers have presented many useful algorithms, which can be classified to three kinds: gray based methods, transformation based methods and feature based methods. When scenario is simple or flat, feature based methods sometimes have imperfect results. Transformation based methods usually accompany large computation cost and high computation complexity. Here we presented an algorithm based on gray projection which divided the whole image into four sub-regions: the upper one, the bottom one, the left one and the right one. For making the translation estimation easier, a central region is also chosen. Then the gray projections of the five sub-regions were counted. From the five pairs of gray projections five group offsets including rotation and translation were obtained via cross correlation between current frame and reference frame gray projections. Then according to the above offsets, the required parameters can be estimated. The expected translation parameters(x axis offset and y axis offset) can be estimated via the offsets from the central region image pair, the rotation angle can be calculated from the left four groups offsets. Finally, Kalman filter was adopted to compute the compensation. Test results show that the algorithm has good estimation performance with less than one pixel translation error and 10 percent rotation error. Based on this kind of gray projection algorithm, a real-time electronic digital image stabilization system has been designed and implemented. System tests demonstrate the system performance reaches the expected aim.

Application of difference method to dim point target detection in infrared images

This paper deals with the detection of dim point targets in infrared images. Dim point targets detection is always a difficulty in information processing. Researchers have proposed many effective methods in this aspect, this paper no longer mentions them but will introduce a new method. Whereas difference method has obtained good results in 1D signal processing, this paper manages to apply it to 2D signal processing, that is to say, dim point targets detection in infrared images of low SNR.

Small target detection in noisy image sequences

This paper presents a new approach for detecting small, moving targets in noisy image sequences. This approach takes the following steps: 1) clutter suppressing, 2) adaptive thresholding, and 3) recursive maximum similarity filter. Among these processes, clutter suppressing algorithm and recursive maximum similarity (RMS) filter are a main contribution of this paper. Both of them can be implemented by fully parallel algorithm, and real-time is possible for image sequences at high frame rate. Test results show that the approach has ability to detect small low-contrast moving targets whose positions and trajectories are unknown.

Registration of infrared and visual images based on phase grouping and mutual information of gradient orientation

This paper presents a novel infrared and visual image registration method based on phase grouping and mutual information of gradient orientation. The method is specially designed for infrared image navigation, which is different from familiar multi-sensor image registration methods in the field of remote sensing. The central idea is to firstly extract common salient structural features from visual and infrared images through phase grouping, then registering infrared image to visual image and estimating the exterior parameters of the infrared camera. Two subjects are involved in this reports: (1) In order to estimate image gradient orientation accurately, a new method based on Leguerre-Gauss filter is presented. Then the image are segmented by grouping of pixels based on their gradient orientations and ling support regions are extracted as common salient structural features from infrared and visual images of the same ground scene. (2)In order for registering infrared and visual image, coordinate systems are constructed, coordinate transformations are formularized, and the new similarity measures based on orientation mutual information is presented. Quantitative evaluations on real and simulated image data reviews that the proposed method can provide registration results with improved robustness and accuracy.

Using segmentation for precision tracking

This paper will not only discuss the precision tracking using segmentation in infrared (IR) images, but also describe how to avoid using the a priori information in implementing the precision tracking with segmentation. The method presented above is not limited to single target case, it can be extended to multiple target tracking, too. For the two cases, we have done Monte Carlo simulations. The considerable simulation tests show that this tracking method is successful not only in recognizing and tracking targets automatically but also in tracking the specified target. Though the noise background is complicated, they all have good effect and high precision.

Recognizing and tracking airport runway target in infrared images

In this paper, we show how to detect the airport runway target and how to recognize and track it. Therefore we present an edge sharpening method based on Sobel and Robert operators to detect the runway from the complicated background. Then we use certain characteristics to recognize it and implement effective tracking for it.

An estimation method based on wavelet transformation for infrared image noise

A method is presented for finding the accurate power spectral density of infrared detector noise. The 1/f/sup r/ random process is described by wavelet functions and a maximum likelihood method is employed to estimate the parameter r.

A novel fast median filter algorithm without sorting

As one of widely applied nonlinear smoothing filtering methods, median filter is quite effective for removing salt-andpepper noise and impulsive noise while maintaining image edge information without blurring its boundaries, but its computation load is the maximal drawback while applied in real-time processing systems. In order to solve the issue, researchers have proposed many effective fast algorithms and published many papers. However most of the algorithms are based on sorting operations so as to make real-time implementation difficult. In this paper considering the large scale Boolean calculation function and convenient shift operation which are two of the advantages of FPGA(Field Programmable Gate Array), we proposed a novel median value finding algorithm without sorting, which can find the median value effectively and its performing time almost keeps changeless despite how large the filter radius is. Based on the algorithm, a real-time median filter has been realized. A lot of tests demonstrate the validity and correctness of proposed algorithm.

Image feature extraction based multiple ant colonies cooperation

This paper presents a novel image feature extraction algorithm based on multiple ant colonies cooperation. Firstly, a low resolution version of the input image is created using Gaussian pyramid algorithm, and two ant colonies are spread on the source image and low resolution image respectively. The ant colony on the low resolution image uses phase congruency as its inspiration information, while the ant colony on the source image uses gradient magnitude as its inspiration information. These two ant colonies cooperate to extract salient image features through sharing a same pheromone matrix. After the optimization process, image features are detected based on thresholding the pheromone matrix. Since gradient magnitude and phase congruency of the input image are used as inspiration information of the ant colonies, our algorithm shows higher intelligence and is capable of acquiring more complete and meaningful image features than other simpler edge detectors.