基于Harris角点的多视角图像全景拼接算法matlab仿真

news2024/10/2 16:22:56

1.算法运行效果图预览

2.算法运行软件版本

3.部分核心程序

4.算法理论概述

4.1 Harris角点检测

4.2 图像配准

4.3 图像变换和拼接

4.4 全景图像优化

5.算法完整程序工程

1.算法运行效果图预览

2.算法运行软件版本

matlab2022a

3.部分核心程序

 
function [ImageB] = func_stitch(ImageA, ImageB)
 % 获取ImageA和ImageB的尺寸  
    RR1 = size(ImageA,1);
    CC1 = size(ImageA,2);
    RR2 = size(ImageB,1);
    CC2 = size(ImageB,2);
    %角点检测  
    jiaodian_imageB    = corner_detector(ImageB);
    %提取角点  
    [xh,yh,~]          = anms(jiaodian_imageB, 300);
    %对提取的角点计算特征描述子
    [Pcorner]          = feat_desc_geoblur(ImageB, xh, yh);

    %角点检测 
    jiaodian_imageA    = corner_detector(ImageA);
    %提取角点
    [xh2, yh2, ~]      = anms(jiaodian_imageA, 300);
    %对提取的角点计算特征描述子
    [Pcorner2]         = feat_desc_geoblur(ImageA, xh2, yh2);
    % 对两张图像的特征描述子进行匹配
    [Pmatch]           = feat_match(Pcorner2, Pcorner);

    % 提取匹配成功的点  
    X_mh1 = xh2(Pmatch ~= -1);
    Y_mh1 = yh2(Pmatch ~= -1);
    X_mh2 = xh(Pmatch(Pmatch ~= -1));
    Y_mh2 = yh(Pmatch(Pmatch ~= -1));

    % 剔除误匹配点 
    [H, ~] = ransac_est_homography(X_mh1, Y_mh1, X_mh2, Y_mh2, 10);

    % 计算两张图像到各自边界的距离  
    ImageA_dist = dist2border(ImageA);
    ImageB_dist = dist2border(ImageB);
    
    % 计算img_i四个角的映射坐标 
    ul = H*[1 1 1]'; 
    ul = ul/ul(end);

    ur = H*[CC1, 1, 1]'; 
    ur = ur/ur(end);

    bl = H*[1, RR1, 1]'; 
    bl = bl/bl(end);

    br = H*[CC1, RR1, 1]'; 
    br = br/br(end);
 
    % 根据映射坐标确定需要填充的边界  
    Edge_up    = 0;  
    Edge_L     = 0;
    Edge_dw    = 0;
    Edge_R     = 0;

    if max(br(1),ur(1)) > CC2
        Edge_R = round(max(br(1),ur(1))-CC2+30);
        ImageB = padarray(ImageB, [0, Edge_R], 'post');
    end
    if max(br(2), bl(2)) > RR2
        Edge_dw = round(max(br(2), bl(2))-RR2+30);
        ImageB = padarray(ImageB, [Edge_dw, 0], 'post');
    end
    if min(ul(1), bl(1)) <= 0 
        Edge_L = round(-min(ul(1), bl(1))+30);
        ImageB = padarray(ImageB, [0, Edge_L], 'pre');
    end
    if min(ul(2), ur(2)) <= 0
        Edge_up = round(-min(ul(2), ur(2)) + 30);
        ImageB = padarray(ImageB, [Edge_up, 0], 'pre');
    end
    % 计算单应性矩阵的逆
    H_inv = inv(H);
 
    % 创建一个网格，用于映射img_b上的每个像素到img_i上的坐标    
    [yh, xh] = meshgrid(round(Edge_up+min(ul(2), ur(2))):round(Edge_up+max(bl(2), br(2))), round(Edge_L+min(ul(1), bl(1))):round(Edge_L+max(br(1),ur(1))));
    yh = yh(:); 
    xh = xh(:);

    xy  = H_inv*[xh - Edge_L, yh - Edge_up, ones(size(xh,1),1)]';
    xh2 = int64(xy(1,:)'./xy(3,:)'); yh2 = int64(xy(2,:)'./xy(3,:)');
................................................................................
end
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