Research on fast POCS super-resolution restoration algortihm based on gradient image

	Research on fast POCS super-resolution restoration algortihm based on gradient image
	Chen, J.; W. Wang; T. Liu; B. Li; R. Jiang and H. Gao
	2015
发表期刊	Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument
卷号	36 期号:2 页码:327-338
摘要	With the spring up of the infrared imaging related industry, the infrared imaging technology has become the mainstream development direction of the intelligent photoelectrical detection due to its good concealment, wide detection range, high positioning accuracy, long penetration distance, light weight, little volume, low power dissipation and high solidity. However, the features of the image of infrared dim-small target, such as less details and low SNR, become the bottleneck of the application of infrared image. How to enhance the imaging effect of the infrared dim-small target becomes the hotspot of the research. POCS algorithm is currently one of the widely used super-resolution restoration algorithm. However, this algorithm requires large amount of computation and takes a long processing time. Also, the retention capacity of the details on the edge of the image is poor. Aiming at the long iteration time of the POCS super-resolution restoration algorithm that cannot meet the real-time detecting requirement of optical detection system, a fast POCS super-resolution restoration algorithm based on gradient image (GPOCS) is proposed, which classifies the image pixels according to the gradient distribution of the image, and then uses different iteration factors for calculation. The iteration step is larger when the gradient is larger and the iteration step is smaller when the gradient is smaller. The improved algorithm can preserve edge information and suppress noise. Therefore, it can guarantee the performance of the super-resolution restoration and greatly reduce the operation time. Experiment results show that GPOCS algorithm results in certain noise suppression at background. Its overall restoration capability is superior to that of traditional POCS method. This algorithm could effectively retain the edge details, and the processing time is less than that of traditional POCS restoration method; and the one order of magnitude reduction is already close to real time performance. The GPOCS algorithm could adaptively select the step size. GPOCS algorithm could better retain edge information and suppress noise. Furthermore, the GPOCS algorithm could guarantee the super-resolution restoration performance, while greatly reducing the processing time. Although GPOCS algorithm could not meet real time requirement, its performance is already close to real time. , 2015, Science Press. All right reserved.
文章类型	期刊论文
收录类别	EI
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/56350
专题	中科院长春光机所知识产出
推荐引用方式 GB/T 7714	Chen, J.,W. Wang,T. Liu,et al. Research on fast POCS super-resolution restoration algortihm based on gradient image[J]. Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument,2015,36(2):327-338.
APA	Chen, J.,W. Wang,T. Liu,B. Li,&R. Jiang and H. Gao.(2015).Research on fast POCS super-resolution restoration algortihm based on gradient image.Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument,36(2),327-338.
MLA	Chen, J.,et al."Research on fast POCS super-resolution restoration algortihm based on gradient image".Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument 36.2(2015):327-338.

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基于梯度图的快速POCS超分辨率复原算法（1039KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览请求全文