Image Sparse Inpainting Based on Directional Wavelet Transform

图像修复有着重要的应用价值,稀疏表示作为前沿的信号处理方法,也已经使用在图像修复中。但是,传统方法在稀疏图像的时候利用的是预先给定的图像基,不能自适应图像,因此稀疏表示能力有限。文中提出从参考图中估计出图像的最佳几何方向使得稀疏变换能自适应图像几何信息,提供更稀疏的图像表示方法。稀疏修复通过最小化1范数模型进行求解。实验结果表明,所提方法较传统的二维小波变换可以更好地保留图像中边缘和纹理,获得更高的峰值信噪比。Image inpainting plays an improtant role in application area.As an advanced signal processing method,sparse representation has been used in image inpainting.However given image bases are adopted in trad tional methods at the process of inpainting sparse images,it has no adaptive capability and sparse representation capability is limited.The best geometry direction is estimated according to reference images so that sparse trans form is adaptive to geometry informations of images.And a representation method of sparser images is provided.Sparse inpainting is calculated by a minimized norm model such as l1.Experimental results show that edges and texture in images are preserved more perfectly comparing with traditional 2D wavelet transform methods.So higher peak signal to noise ratio is got.广东省数字信号与图像处理技术重点实验室开放基金(54600321); 福建省高校产学合作科技重大项目(2011H6025

Magnetic resonance image reconstruction using trained geometric directions in 2D redundant wavelets domain and non-convex optimization

Reducing scanning time is significantly important for MRI. Compressed sensing has shown promising results by undersampling the k-space data to speed up imaging. Sparsity of an image plays an important role in compressed sensing MRI to reduce the image artifacts. Recently, the method of patch-based directional wavelets (PBDW) which trains geometric directions from undersampled data has been proposed. It has better performance in preserving image edges than conventional sparsifying transforms. However, obvious artifacts are presented in the smooth region when the data are highly undersampled. In addition, the original PBDW-based method does not hold obvious improvement for radial and fully 2D random sampling patterns. In this paper, the PBDW-based MRI reconstruction is improved from two aspects: 1) An efficient non-convex minimization algorithm is modified to enhance image quality; 2) PBDW are extended into shift-invariant discrete wavelet domain to enhance the ability of transform on sparsifying piecewise smooth image features. Numerical simulation results on vivo magnetic resonance images demonstrate that the proposed method outperforms the original PBDW in terms of removing artifacts and preserving edges

甲基睾丸酮诱导鲫鱼雌核发育子代性转化的研究

本文介绍了用甲基睾丸酮诱导鲫鱼雌核发育子代性转化的研究结果。对孵化后3天的人工雌核发育的红鲫仔鱼和天然雌核发育的银鲫仔鱼,以含有不同量的甲基睾丸酮激素饵料喂养90天,再用一般饵料喂养直到可以剖腹鉴别性别。结果是:1,喂用每克 MT_(25-30μg)激素饵料的,除 1尾发育为精卵巢外.全部试验鱼都发育成雄性;2,喂用每克含 MT_(50-100μg)激素饵料的,没有雄性鱼出现。此外,用 1ml 工业酒精同 1g饵料配制的混合饵料,喂养90天的试验鱼,有60—84.6％的个体发育成雄性。不加激素和酒精的饵

鲫鱼的人工和天然雌核发育

用照射处理的草鱼或华南鲤的精液授精的鲫鱼卵为单倍体雌核发育;所有单倍体胚胎都是畸形,并在孵化前死亡。如果用照射精液授精的鲫鱼卵在18—19℃的水中放置2分钟,然后在0—3℃的冰水中放置20分钟,再放回室温水中孵化,可以从每百颗受精卵中得到4.5—11.9(平均8.34)尾成活的二倍体仔鱼。根据38尾银鲫(其中33尾捕自黑龙江省方正县双凤水库)的细胞学和胚胎学检查,证实它们是雌核发育繁殖的

基于人机混合智能的地铁列车无人驾驶系统研究

基于国内外地铁列车驾驶技术的发展现状，阐述了地铁列车智能驾驶发展及研究的必要性。针对当前无人驾驶采用的机器学习算法可解释性差的缺陷，引入模糊系统，提出了基于人机混合智能的地铁列车无人驾驶系统，以两种方式实现人机混合智能。探索了结合认知系统的地铁列车无人驾驶系统，为实现真正意义上的强人工智能地铁列车无人驾驶系统提供了一种面向未来的解决方案