Effects of threshold on single-target detection by using modified amplitude-modulated joint transform correlator

Kaewkasi, Pitchaya; Widjaja, Joewono; Uozumi, Jun

doi:10.1016/j.optcom.2006.10.002

Cited by 12 publications

(2 citation statements)

References 8 publications

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“…It is difficult to select optimal parameters using a recursive Bayesian method [7], wavelet-based algorithm [8,9], and binary template matching [10], even though they are not very sensitive to the evolving climate data. Likewise, a genetic algorithm (GA) and neural network (NN) [11,12], an expectation maximization algorithm [13], and a joint transform correlator algorithm [14] can be used to intelligently suppress the effect of clutter in some cases, but organizing an effective training set is required, which can be challenging.…”

Section: Introductionmentioning

confidence: 99%

Adaptive method of dim small object detection with heavy clutter

2013

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This paper investigates an adaptive method of dim small target detection in infrared images with a complex background. We analyze in depth the characteristics of the background, the target, and the noise in the gray intensity, space and frequency domain of the images. The modified top-hat transformation using interrelated structuring elements is adopted to adaptively detect the darker and the brighter targets and greatly suppress the cluttered background. Lateral pattern inhibition enhances the local contrast ratio and simultaneously identifies the targets of interest. The automatic threshold is used to enhance real dim targets in the cluttered background. A simulation based on the proposed algorithm is carried out and the results prove that the algorithm is effective and valid.

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Section: Introductionmentioning

confidence: 99%

Adaptive method of dim small object detection with heavy clutter

2013

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“…Due to its popularity there are many target recognition studies recently, the commonly used methods include the recognition algorithms based on particle filter [1] , mean shift method [2] , and correlation method [3] . Optical correlation method using HOJTC, as a kind of correlation recognition method, has the merits of parallel, large capacity and high-speed [4,5] . So it is more suitable for moving target detection and recognition.…”

Section: Introductionmentioning

confidence: 99%

Optical Correlation Recognition Technology of Small Moving Target Based on Wavelet Multi-Scale Edge Fusion

Zhang

Wang

et al. 2013

KEM

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Moving target recognition has a wide application in varieties of domains and has received more attention in recent years. Among all the recognition methods, optical correlation technology, using hybrid optoelectronic joint transform correlator (HOJTC), has the merits of parallel, large capacity and high-speed, so it is considered as one of the most effective methods for moving target detection. But in the course of detecting, some targets are too small to be recognized by HOJTC. These small targets in cluttered background and strong noise may affect the brightness of the correlation peaks and have a serious influence on target recognition results. In order to solve this problem, this paper applies a wavelet multi-scale edge fusion algorithm which firstly extracts the edge at different scales by wavelet modulus maximum method, and then fuses the detected edge to obtain more edge information of the target. In addition, for the moving distortion problems, taking temporal state of the target as the template can achieve the template update. To prove this method, many detection experiments of small moving targets have been performed with optical correlation method. As an example a small target “boat” taking up only pixels is presented. The recognition results show that the brightness of the correlation peaks is enhanced and the target recognition ratio is increased. The conclusion can be drawn that applying this algorithm in optical correlation method can realize the small moving target recognition successfully and expand the application to scope of optical correlation technology.

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Noisy face recognition using compression-based joint wavelet-transform correlator

Widjaja

2012

Optics Communications

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Effects of threshold on single-target detection by using modified amplitude-modulated joint transform correlator

Cited by 12 publications

References 8 publications

Adaptive method of dim small object detection with heavy clutter

Adaptive method of dim small object detection with heavy clutter

Optical Correlation Recognition Technology of Small Moving Target Based on Wavelet Multi-Scale Edge Fusion

Noisy face recognition using compression-based joint wavelet-transform correlator

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