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- W4200435641 abstract "With the development of semiconductor technology, the performance of many new image sensors, such as infrared focal planes and CMOS image sensors, have been improved. Also, it is an alternative choice of CCD, vacuum tube or other equipment that promotes this kind of sensors to become the mainstream of the market. However, this kind of image sensors has a weakness that is the stripe noise, due to the inconsistent readout circuit response. This noise influences the quality of image directly, as a result, the poor image quality in-benefits for recognition and classification. Thus, how to remove the stripe noise arises the interests for many researchers. Most of them only focus on one certain type of stripe features, instead of combining different features together, leading to the poor performance of denoising. This paper proposes a method of removing stripes that combines feature extraction and function fitting. Firstly, extract the statistics and spatial position of the stripes, and then perform two steps of rough processing and fine processing on the image. The PSNR, SSM value show that the algorithm meets the design expectations and has a certain degree of robustness." @default.
- W4200435641 created "2021-12-31" @default.
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- W4200435641 date "2021-11-01" @default.
- W4200435641 modified "2023-09-27" @default.
- W4200435641 title "An image destriping method combining feature extraction and nonlinear fitting" @default.
- W4200435641 doi "https://doi.org/10.1109/ccisp52774.2021.9639372" @default.
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