roi

稀疏矩阵字典的优化KSVD，本人已进行测试，效果甚佳,可以用在图像，数据的压缩和分类(Sparse dictionary optimization KSVD, I have been tested, very good results)

1.运用Laplacian算子，基于二阶微分的图像增强，即拉氏变换法进行图像平滑 2.利用邻域平均法实现图像的平滑处理 3.利用Robert算子做锐化处理(1. The use of Laplacian operator, based on second-order differential of the image enhancement, that is, Laplace transform method for image smoothing 2. The use of neighborhood average method of smoothing image 3. The use of Robert sharpening operator to do)

说明：  提取纹理图像特征，包括平均值、标准差、平滑度、三阶矩、一致性、和熵。(Extract texture features, including mean, standard deviation, smoothness, third moment, consistency, and entropy.)

不规则窗体

说明：  经典图论，其中叙述了图论的经典算法等，如最大流、最小割等相关算法。(Classical graph theory, graph theory, which describes the classical algorithms, such as maximum flow, minimum cut, and other related algorithms.)

Image Indexing Using Color Correlogram

实现地震资料的多次波处理,实现相同点的叠加，进而切除(to complish the goal that the noise can be suppressed in the seismic data)

说明：  独立分量分析，快速独立分量分析，FAST-ICA可以用(Independent component analysis)

深度图像处理,主要的是对深度图像进行区域分割(depth map)

SURF算法作为一种新近出现的特征提取方法，在重复度、独特性、鲁棒性3个方面，均超越或接近以往提出的同类方法，并在计算效率上具有明显的优势。本代码采用SURF算法检测图像并进行坐标变换与图像拼接。 采用SURF算法对图像进行检测，其主要是用Hessian矩阵对图像进行检测，对图像的特征提取之后找到图像的特征点。之后采用最近临快速匹配（NN）、随机抽样一致性（RANSAC）算法和最小二乘法参数优化（LM）对特征点进行提纯匹配。最后在两幅图像中进行坐标变换，达到统一坐标系和图像拼接的效果。 (SURF（Speeded Up Robust Features） as a method of feature extraction which newly appeared is over or nearly previous method on duplication, uniqueness, and robustness and have a clear advantage on computational efficiency. This code uses the SURF and coordinate transformation algorithm to detect image and image matching. This code uses the SURF algorithm of image detection, the main is to use the Hessian matrix of image for testing, to find the image after image feature extraction of feature points. After we used Nearest Neighbor (NN), Random Sample Consensus (RANSAC) algorithm and least square parameter optimization for purification of matching feature points. Coordinate transformation in the last two images, to coordinate system to achieve the same image stitching. )