基于自适应小波偏微分方程的蝗虫切片图像去噪OA北大核心CSCDCSTPCD
Image de-noising of locust sections based on adaptive wavelet and partial differential equation method
蝗虫显微切片图像在获取的过程中不可避免地会受到噪声污染,其纹理、边缘与噪声又都属于高频分量,单独使用小波变换或偏微分方程(partial differential equation,PDE)扩散的方法都不能在有效去噪的同时保持边缘、纹理等.针对这一问题,提出了基于自适应小波PDE的去噪算法.首先对蝗虫切片含噪图像进行sym5小波软阈值去噪,分解层数根据去噪后图像的PSNR(peak signal to noise ratio)值自适应地选择,阈值…查看全部>>
Noise pollution on locust micro-section images is always unavoidable during the acquisition of the images. However, few researches have been devoted to the de-noise processing of locust section images. The locust section image is generally characterized by rich textures, smooth regions and well-defined edges. Since the textures, the edges and noises of the images are high-frequency components, wavelet transformation can't successfully get rid of noise on the…查看全部>>
李丽;张楠楠;梅树立;李晓飞
中国农业大学信息与电气工程学院,北京 100083中国农业大学信息与电气工程学院,北京 100083中国农业大学信息与电气工程学院,北京 100083中国农业大学信息与电气工程学院,北京 100083
信息技术与安全科学
切片图像小波蝗虫切片图像去噪PM模型结构相似性
sectionimagewaveletlocust sectionimage de-noisingPerona-Malik modelstructural similarity image measurement (SSIM)
《农业工程学报》 2015 (20)
基于高分辨率遥感数据的农作物纹理特征表达及其类型识别研究
172-177,6
国家自然科学基金(41171337)
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