研究目的
To propose a new infrared image denoising method based on steering kernel regression image guided filter that can retain image details and acquire better visual experience compared to traditional methods.
研究成果
The proposed algorithm can remove noise in the infrared image better than classical algorithms, with better preservation and reconstruction of edges, texture, and other details.
研究不足
Not explicitly mentioned in the provided text.
1:Experimental Design and Method Selection:
The method involves determining the shape and size of the steering kernel according to the local gradient information of the image, obtaining the filtering weight by steering kernel regression, and modifying the analysis window of image guided filtering.
2:Sample Selection and Data Sources:
A synthetic infrared image mixed with Gaussian noise is used.
3:List of Experimental Equipment and Materials:
Not explicitly mentioned.
4:Experimental Procedures and Operational Workflow:
The algorithm's flow includes calculating gradients, local gradient parameters, main direction axis and tensile coefficient, matrix calculation, filtering weight calculation, and image estimation.
5:Data Analysis Methods:
Peak Signal to Noise Ratio (PSNR) is used as an objective evaluation index.
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