The result of the extraction of the edge and contour information of the multifunctional digital ship image directly affects the evaluation and recognition of the subsequent image quality. At present, the common method used to extract the edge contour information is based on the Canny operator, and there is a problem that the edge is not clear.In order to obtain more accurate edge information, a method of extracting edge and contour information of multimedia digital image based on multi-scale morphology is proposed. Firstly, the digital ship image is made double filter and the fuzzy threshold segmentation, and then the edge and contour information is extracted by multi-scale morphology. Experiments show that the proposed method can obtain more accurate edge information compared with the other methods.
Known-plaintext attack is considered for decrypting the image generated by iterative random phase encoding in fractional Fourier transform domains. The double random phase encoding in Fourier domains is introduced to design the known-plaintext attack procedure. The decryption test is explored without both fractional order and these random phase masks. Some numerical simulations are made to demonstrate the validity of the known-plaintext attack.
This paper proposes an improved method of solving the permutation problem inherent in frequency-domain of convolutive blind source separation (BSS). It combines a novel inter-frequency dependence measure: the power ratio of separated signals, and a simple but effective bin-wise permutation alignment scheme. The proposed method is easy to implement and surpasses the conventional ones. Simulations have shown that it can provide an almost ideal solution of the permutation problem for a case where two or three sources were mixed in a room with a reverberation time of 130 ms.
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