opencv 缩小放大用哪种插值更好??

If you are enlarging the image, you should prefer to use INTER_LINEAR or INTER_CUBIC interpolation. If you are shrinking the image, you should prefer to use INTER_AREA interpolation.

Cubic interpolation is computationally more complex, and hence slower than linear interpolation. However, the quality of the resulting image will be higher.

为了克服这个问题，您应该找出可以进行插值的给定图像的新尺寸。并在目标图像上复制插值采样图像，如：

# create target image and copy sample image into it
(wt, ht) = imgSize # target image size
(h, w) = img.shape # given image size
fx = w / wt
fy = h / ht
f = max(fx, fy)
newSize = (max(min(wt, int(w / f)), 1),
           max(min(ht, int(h / f)), 1))  # scale according to f (result at least 1 and at most wt or ht)
img = cv2.resize(img, newSize, interpolation=cv2.INTER_CUBIC) #INTER_CUBIC interpolation
target = np.ones([ht, wt]) * 255  # shape=(64,800)
target[0:newSize[1], 0:newSize[0]] = img

 有关每个插值的结果，cv2 resize interpolation methods - Chadrick's Blog

一 

openCV中一些可能的插值是：

• INTER_NEAREST – 最近邻插值
• INTER_LINEAR – 双线性插值（默认使用）
• INTER_AREA – 使用像素区域关系重采样。它可能是图像抽取的首选方法，因为它可以提供无莫尔条纹的结果。但是当图像被缩放时，它类似于 INTER_NEAREST 方法。
• INTER_CUBIC – 4×4 像素邻域的双三次插值
• INTER_LANCZOS4 – 8×8 像素邻域的 Lanczos 插值