It is important for scene generation to keep the texture of infrared images in simulation of anti-ship infrared imaging
guidance. We studied the fractal method and applied it to the infrared scene generation. We adopted the method of
horizontal-vertical (HV) partition to encode the original image. Basing on the properties of infrared image with sea-sky
background, we took advantage of Local Iteration Function System (LIFS) to decrease the complexity of computation
and enhance the processing rate. Some results were listed. The results show that the fractal method can keep the texture
of infrared image better and can be used in the infrared scene generation widely in future.
KEYWORDS: Digital signal processing, Image processing, Video, Control systems, Data conversion, Clocks, Video processing, Field programmable gate arrays, Signal processing, Real time image processing
A kind of real time image processing system for target recognition and track is discussed. The system adopts master-slave DSP embedded structure in hardware, combines general DSP with special image processing circuit, and video data collection is controlled by program. This real time image processing system is designed with the high speed DSP TMS320C6201 while FPGA for image pretreatment. This paper emphasizes on introduction of real time image processing system based on DSP from the view of hardware. Experiments have been done by the system and the results are satisfactory.
Since the conventional denoising algorithms have not considered the influence of certain concrete detector, they are not very effective to remove various noises contained in the low signal-to-noise ration infrared image. In this paper, a new thinking for infrared image denoising is proposed, which is based on the noise analyses of detector with an example of L model infrared multi-element detector. According to the noise analyses of this detector, the emphasis is placed on how to filter white noise and fractal noise in the preprocessing phase. Wavelet analysis is a good tool for analyzing 1/f process. 1/f process can be viewed as white noise approximately since its wavelet coefficients are stationary and uncorrelated. So if wavelet transform is adopted, the problem of removing white noise and fraction noise is simplified as the only one problem, i.e., removing white noise. To address this problem, a new wavelet domain adaptive wiener filtering algorithm is presented. From the viewpoint of quantitative and qualitative analyses, the filtering effect of our method is compared with those of traditional median filter, mean filter and wavelet thresholding algorithm in detail. The results show that our method can reduce various noises effectively and raise the ratio of signal-to-noise evidently.
The watershed algorithm from mathematical morphology is powerful for segmentation and often produces more stable segmentation results, including continuous segmentation boundaries. However, direct application of the watershed segmentation algorithm generally leads to oversegmentation due to noise and other local irregularities of the gradient. Oversegmentation can be serious enough to render the result of the alorithm virtually useless. An approach used to control oversegmentation is based on the concept of markers. A marker is a connected component belonging to an image. In this paper, considering that there are two small but very brighter regions associated with the chimneys of ship, the topological properties of IR ship target can be used to restrict the algorithm. So, we have internal markers, associated with IR ship target, and external markers, associated with the background. Experimental results show that, when the original watershed segmentation has noisy boundaries or wrong limbs attached to the object of interest, the proposed method overcomes those drawbacks and yields a better segmentation.
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