The research of multi-frame target recognition based on laser active imaging

Can-jin Wang; Tao Sun; Tin-feng Wang; Juan Chen

doi:10.1117/12.2033015

19 September 2013 The research of multi-frame target recognition based on laser active imaging

Can-jin Wang, Tao Sun, Tin-feng Wang, Juan Chen

Proceedings Volume 8905, International Symposium on Photoelectronic Detection and Imaging 2013: Laser Sensing and Imaging and Applications; 89050P (2013) https://doi.org/10.1117/12.2033015
Event: ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging, 2013, Beijing, China

Abstract

Laser active imaging is fit to conditions such as no difference in temperature between target and background, pitch-black night, bad visibility. Also it can be used to detect a faint target in long range or small target in deep space, which has advantage of high definition and good contrast. In one word, it is immune to environment. However, due to the affect of long distance, limited laser energy and atmospheric backscatter, it is impossible to illuminate the whole scene at the same time. It means that the target in every single frame is unevenly or partly illuminated, which make the recognition more difficult. At the same time the speckle noise which is common in laser active imaging blurs the images . In this paper we do some research on laser active imaging and propose a new target recognition method based on multi-frame images . Firstly, multi pulses of laser is used to obtain sub-images for different parts of scene. A denoising method combined homomorphic filter with wavelet domain SURE is used to suppress speckle noise. And blind deconvolution is introduced to obtain low-noise and clear sub-images. Then these sub-images are registered and stitched to combine a completely and uniformly illuminated scene image. After that, a new target recognition method based on contour moments is proposed. Firstly, canny operator is used to obtain contours. For each contour, seven invariant Hu moments are calculated to generate the feature vectors. At last the feature vectors are input into double hidden layers BP neural network for classification . Experiments results indicate that the proposed algorithm could achieve a high recognition rate and satisfactory real-time performance for laser active imaging.

Citation Download Citation

Can-jin Wang, Tao Sun, Tin-feng Wang, and Juan Chen "The research of multi-frame target recognition based on laser active imaging", Proc. SPIE 8905, International Symposium on Photoelectronic Detection and Imaging 2013: Laser Sensing and Imaging and Applications, 89050P (19 September 2013); https://doi.org/10.1117/12.2033015

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KEYWORDS

Target recognition

Denoising

Speckle

Wavelets

Imaging systems

Image processing

Neural networks

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