1.opencv插值介紹

opencv提供resize函數用來做圖像縮放，該函數有6個參數：

（1）輸入圖像，Mat型

（2）輸出圖像，Mat型

（3）輸出圖像大小，可用cv::Size(out_img_width, out_img_height)來表示，如果該值為0，則輸出大小由第4，5兩個參數fx、fy決定

（4）水平縮放因子，如果該值為0，則會按照(double)dsize.width/src.cols來計算

（5）重直縮放因子，如果該值為0，則會按照(double)dsize.height/src.rows來計算

（6）插值算法，可以選擇各種插值算法，INTERNEAREST效果較差，優點是速度快，INTER

2.插值參數選擇

opencv文檔及代碼寫的很清楚了，這里就不再細說，實際使用上，對于放大場景來說，雙立方插值INTER_CUBIC與lanczos插值INTER_LANCZOS4效果較好，而縮小場景，效果最好的算法為INTER_AREA。

• INTER_NEAREST - a nearest-neighbor interpolation
• INTER_LINEAR - a bilinear interpolation (used by default)
• INTER_AREA - resampling using pixel area relation. It may be a preferred method for image decimation, as it gives moire’-free results. But when the image is zoomed, it is similar to the INTER_NEAREST method.
• INTER_CUBIC - a bicubic interpolation over 4x4 pixel neighborhood
• INTER_LANCZOS4 - a Lanczos interpolation over 8x8 pixel neighborhood

enum InterpolationFlags{/** nearest neighbor interpolation */INTER_NEAREST = 0,/** bilinear interpolation */INTER_LINEAR = 1,/** bicubic interpolation */INTER_CUBIC = 2,/** resampling using pixel area relation. It may be a preferred method for image decimation, asit gives moire'-free results. But when the image is zoomed, it is similar to the INTER_NEARESTmethod. */INTER_AREA = 3,/** Lanczos interpolation over 8x8 neighborhood */INTER_LANCZOS4 = 4,/** Bit exact bilinear interpolation */INTER_LINEAR_EXACT = 5,/** mask for interpolation codes */INTER_MAX = 7,/** flag, fills all of the destination image pixels. If some of them correspond to outliers in thesource image, they are set to zero */WARP_FILL_OUTLIERS = 8,/** flag, inverse transformationFor example, #linearPolar or #logPolar transforms:- flag is __not__ set: f$dst( rho , phi ) = src(x,y)f$- flag is set: f$dst(x,y) = src( rho , phi )f$*/WARP_INVERSE_MAP = 16 };

3.demo

img_decode為輸入圖像，img_resize為輸出圖像

resize(img_decode, img_resize, Size(img_dst_width, img_dst_height), 0, 0, INTER_LANCZOS4);

下面為縮小case，原圖分辨率為633x773，目標分辨率為286x350，如下分別為面積插值、雙線性、lanczos效果，縮小時面積關聯法效果最佳：

參考

[1] https://docs.opencv.org/2.4/modules/imgproc/doc/geometric_transformations.html?highlight=resize

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