A texture segmentation method for high resolution remote sensing image Combining gray edge information is proposed. Firstly, an initial segmentation strategy based on gray edge detection is proposed to segment the image initially. Then the texture features of the image are extracted by using the Gauss Markov random field model. In the feature space, the mean values of each class of features in the initial segmentation are obtained, and then the feature vectors are clustered as initial points to complete the segmentation. This method solves two drawbacks of the standard fuzzy C-means clustering algorithm in image segmentation: slow operation speed and large dependence on the initial value. The real remote sensing image is segmented by this algorithm. Experiments show that this method has faster speed and better stability.
According to the robustness of digital watermarking, a robust blind watermarking algorithm based on RS coding technology is proposed and implemented. Before embedding watermark signal, RS channel encoding is carried out. When embedding and extracting the watermark, the relevance of the wavelet transform coefficients are calculated to extract and enhance the robustness. The experimental results show that the gain of 12dB is comparable with that of non coding.
An image denoising and enhancement algorithm based on fractal coding in wavelet domain is presented. Among them, A lemma is introduced first, and the advantages of fractal coding in wavelet domain are analyzed. Then, the denoising algorithm and experimental results based on fractal coding in wavelet domain are given in detail, and the experimental results are analyzed. When the noise level is high, the denoising effect of this method is better than that of the general method, and has higher logarithmic signal-to-noise ratio and peak logarithmic signal-to-noise ratio. At the same time, the calculation amount of this algorithm is smaller and the precision is higher.
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