zoukankan      html  css  js  c++  java
  • opencv实现对图像的插值操作 最近邻、双线性、双三次

    如果本文对您有帮助,请帮忙点赞、评论、收藏,感谢!

    python 为例

    一. 函数原型

            dst=cv.resize(src, dsize[, dst[, fx[, fy[, interpolation]]]])

            参数含义:

            src:input image.

            dst:output image; it has the size dsize (when it is non-zero) or the size computed from src.size(), fx, and fy; the type of dst is the same as of src.

            dsize:output image size; if it equals zero, it is computed as:

                    dsize = Size(round(fx*src.cols), round(fy*src.rows))

                    Either dsize or both fx and fy must be non-zero.

            fx :scale factor along the horizontal axis; when it equals 0, it is computed as

    (double)dsize.width/src.cols

            fy :scale factor along the vertical axis; when it equals 0, it is computed as

    (double)dsize.height/src.rows

            interpolation:interpolation method, see InterpolationFlags


    三种插值方法的 interpolation 参数
     

    二. 实验代码:

     1 import cv2
     2 import numpy as np 
     3 
     4 # 读入灰度图像
     5 im_path='../paojie_g.jpg'
     6 img = cv2.imread(im_path,0)
     7 # 注意应该先写宽度img.shape[1]*2,再写高度img.shape[0]*2
     8 NN_interpolation = cv2.resize(img,(img.shape[1]*2,img.shape[0]*2),interpolation=cv2.INTER_NEAREST)
     9 BiLinear_interpolation =  cv2.resize(img,(img.shape[1]*2,img.shape[0]*2),interpolation=cv2.INTER_LINEAR)
    10 BiCubic_interpolation = cv2.resize(img,(img.shape[1]*2,img.shape[0]*2),interpolation=cv2.INTER_CUBIC)
    11 
    12 cv2.imshow('NN_interpolation',NN_interpolation)
    13 cv2.imwrite('NN_interpolation.jpg',NN_interpolation)
    14 cv2.imshow('BiLinear_interpolation',BiLinear_interpolation)
    15 cv2.imwrite('BiLinear_interpolation.jpg',BiLinear_interpolation)
    16 cv2.imshow('BiCubic_interpolation',BiCubic_interpolation)
    17 cv2.imwrite('BiCubic_interpolation.jpg',BiCubic_interpolation)
    18 cv2.waitKey(0)
    19 cv2.destroyAllWindows()

    三. 实验结果:


    原图 ↑
     

    NN_interpolation x2 ↑
     

    BiLinear_interpolation  x2 ↑
     

    BiCubic_interpolation   x2 ↑
     

            可以看到,最近邻插值算法放大图像后,目标图像边缘出现了明显的锯齿;而双线性和双三次插值算法没有出现明显的锯齿边缘。


    四. 参考内容:

      https://www.jianshu.com/p/f360462f0db4

  • 相关阅读:
    Linux 系统启动过程
    Linux启动U盘制作
    JSONP 教程
    JSON 使用
    JSON.stringify()
    JSON.parse()
    Apache模块开发指南-APR池
    [C++基础]goto的用法
    atexit()函数
    c++ good books
  • 原文地址:https://www.cnblogs.com/wojianxin/p/12517101.html
Copyright © 2011-2022 走看看