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Alternative TitleResearch of Single-frame-based Noise Removal Method for Infrared Images
Thesis Advisor赵耀宏
Keyword非均匀性校正 条纹噪声 随机噪声 单帧图像 非局部均值
Degree Discipline模式识别与智能系统
Degree Name硕士
Degree Grantor中国科学院沈阳自动化研究所
Place of Conferral沈阳
Other AbstractThis topic mainly studies single-frame-based infrared image noise removal methods. The purpose is to improve the signal-to-noise ratio of infrared images, and provide a good foundation for the subsequent detection, recognition and tracking of infrared images. This paper first introduces the stripe and random noise model of infrared image, and analyzes the properties of stripe noise caused by temperature drift in uncooled infrared imaging system based on a set of blackbody experimental images. The vertical linear model is used to construct the noisy image observation model. On this basis, the colored Gaussian model is used to describe the stripe and random mixed noise in the image patches, and a stripe noise intensity estimation method based on image gradient is proposed. In this paper, a method of stripe noise removal based on weighted least squares is proposed. The algorithm firstly filters the noisy image with horizontal one-dimensional weighted least squares filtering as a preliminary estimate of real image information. Then, the stripe correction coefficients are regressed by the vertical direction local weighted ridge regression. The weight in the weighted ridge regression comes from the image local variance as the edge detection operator. This method can effectively reduce the erroneous estimation of the stripe correction term. Aiming at the problems of traditional white noise removal algorithm in dealing with stripe and random mixed noise, such as residual stirpes and filtering quality degradation, this paper analyzes the traditional non-local means denoising algorithm and proposes a improved algorithm. A block similarity measure method that improves the Mahalanobis distance is used, and the distance function in the measure method is adaptively adjusted to the local complexity of the image. The experimental results of simulated noisy data and real data showed that our single-frame-based destriping algorithm can effectively avoid the residual stripe phenomenon compared with the traditional method. Compared with the traditional single-frame-based white noise removal method, the improved non-local means algorithm can remove mixed noise better in both complex and flat regions.
Contribution Rank1
Document Type学位论文
Recommended Citation
GB/T 7714
李方舟. 单帧红外图像噪声去除方法研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2019.
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单帧红外图像噪声去除方法研究.pdf(26070KB)学位论文 开放获取CC BY-NC-SAApplication Full Text
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