INSARjiechanchao

MNIST数据集中图像数据文件， 60000个训练集(The MNIST dataset image data files, 60000 training set)

说明：  实现图像分类，可完成对图像的多分类问题，效果较好(Realize image classification, can complete the multi-classification of images, the effect is better)

用Visual C编的用于语音的频频谱的检测，能显示出来语音的频谱图。 (Visual C series of the spectrum for voice detection, displayed the frequency spectrum of the voice.)

本文实现了Retinex算法，支持对图像的去雾灯操作，是一种图像增强的方法。(this paper present a new image strength method-Retinex impliment by opencv)

实现ICM算法（条件迭代模型）对于灰度图像的分割(Achieve ICM algorithm (iterative model conditions) for the gray-scale image segmentation)

按照夹角余弦距离计算待测样品与样品库的样品相似度(Cosine distance calculation in accordance with the test sample and the sample database sample similarity)

antenna dipole of 3d antenna

运用Perona-Malik各项异性扩散模型对二维图像进行去噪处理。该方法在有效的抑制噪声的同时能够保护图像的边缘。(The use of Perona-Malik Anisotropic Diffusion Model for the treatment of two-dimensional image denoising. The method in the effective suppression of noise at the same time to protect the edge of the image.)

于轻小型光学成像系统，小孔径限制了 图像的极限分辨率，衍射退化造成了截止频率外信息的丢失成像系统所期望的 大视场不可避免的带来边缘视场的像差恶化，各视场退化情况不同，影响信息的 判读 (Small light optical imaging system, the small aperture limit the ultimate resolution of the image, diffraction degradation aberration deterioration of the desired cutoff frequency outside the loss of information imaging system field of view inevitably bring the edge of the visual field, each referred to as field degradation, affecting the interpretation of the information)

自适应正则化超分辨率重建 是： M. G. Kang这人写的IEEE上发表的论文 可以参考下算法( General Choiceof the Regularization Functional in Regularized Image Restoration)