Due to extended objects are influenced by occluded and blurred edge, the stability of target tracking is not good by the figure algorithms or the corner algorithms. In order to solute this problem, an improved multi-resolution(MR) fuzzy clustering algorithm based on Markov random field(MRF) is firstly used to segment the candidate targets of the extended objects from the observed images, then a new proposed target tracking structure algorithm, based on the stabilization of the extended objects’ skeletons and the partially un-occluded and un-blurred edge feature of the extended objects, is applied to extract the skeletons, corners, intersection points and their spatial location relationship of the candidate extended targets to determine the true tracking target or not. The experimental results show that the established algorithm can effectively complete the segmentation and extraction of the partially occluded and blurred extended objects with a very satisfied reliability and robustness.
An ordinary space optical remote sensing camera is an optical diffraction-limited system and a low-pass filter from the theory of Fourier Optics, and all the digital imaging sensors, whether the CCD or CMOS, are low-pass filters as well. Therefore, when the optical image with abundant high-frequency components passes through an optical imaging system, the profuse middle-frequency information is attenuated and the rich high-frequency information is lost, which will blur the remote sensing image. In order to overcome this shortcoming of the space optical remote sensing camera, an online compensating approach of the Modulation Transfer Function in the space cameras is designed. The designed method was realized by a hardware analog circuit placed before the A/D converter, which was composed of adjustable low-pass filters with a calculated value of quality factor Q. Through the adjustment of the quality factor Q of the filters, the MTF of the processed image is compensated. The experiment results display that the realized compensating circuit in a space optical camera is capable of improving the MTF of an optical remote sensing imaging system 30% higher than that of no compensation. This quantized principle can efficiently instruct the MTF compensating circuit design in practice.
Proc. SPIE. 9449, The International Conference on Photonics and Optical Engineering (icPOE 2014)
KEYWORDS: Image processing algorithms and systems, Digital signal processing, Image segmentation, Image processing, Interfaces, Field programmable gate arrays, Parallel processing, Data acquisition, Data processing, Data communications
In order to realize the real-time segmentation processing of multi spectral images in practice, a real-time multi-spectral images segmentation system composed of four TMS320C6455 DSPs, two Virtex-4（V4 XC4VLX80）FPGAs and one Virtex-2 Pro（V2 Pro20）FPGA is designed. Through the optimization of the cooperation processing of the multi DSP and multi FPGA, the parallel multitask processing ability of the DSPs and the effective interface coordination ability of the FPGAs in the built system are used fully. In order to display the processing ability, the segmentation test experiments of 10 spectra visible images, with 1024×1024, segmented by the Multi-scale Image Segmentation Method, was done in the built multi spectral images segment system. The experiment results prove that the multi DSP and multi FPGA multi spectral images processing system designed in this paper satisfies the real-time processing requirement in engineering practice.