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Research on Dim Small Targets Detection in Infrared Images

Author: HuangHeZuo
Tutor: JinZuo
School: Zhejiang University
Course: Electronic Science and Technology
Keywords: dim small target adjacent relevant pixels noise suppression high SNR gain
CLC: TP391.41
Type: Master's thesis
Year: 2012
Downloads: 82
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Abstract


Infrared small targets detection technology is widely used in many modern applications, however, the detection is a tough work. Such information as the shape, size and texture of infrared targets are unknown before detection because the targets are dim and surrounded by complex environment. It makes detection even more difficult if the infrared images are polluted by noise, as is often the case. The detecting algorithm must deal with such problems and ensure the detecting ability of the infrared systems, so it’s a crucial technique.This paper first analyses the characteristics of infrared imaging, and summaries the difficulties in detection. Then the current researching status is introduced by studying some major detecting algorithms in detail.As many infrared images show, there are obvious characteristics as the bright pixels form small targets. Besides the difference of intensity, they always assemble in target region. The tendency of gathering is a unique feature. To take advantage of this, we propose a detecting algorithm which is Adjacent Relevant Pixels Detection. In background estimation, we utilize a set of four filters to get a more accurate result than conventional ways. Then, according to the distribution of bright pixels, the assembling targets pixels are enhanced while the discrete noise pixels are eliminated. Experiments show that, the target point in images processed by ARPD method received high SNR gain, and the noise is well suppressed.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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