图片Gaussian pyramid（一）

本文主要是介绍图片Gaussian pyramid（一），希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

简介

偶然在一个网页上发现一个Python图像处理的方法，能够进行图片的缩放。首先进行了高斯滤波，当缩放到小于30×30时break。

helpers:

# import the necessary packages
from skimage.transform import pyramid_gaussian
import cv2
from PIL import Imageimage = Image.open('./image/cat2.jpg')        
# METHOD #2: Resizing + Gaussian smoothing.
for (i, resized) in enumerate(pyramid_gaussian(image, downscale=2)):# if the image is too small, break from the loopif resized.shape[0] < 30 or resized.shape[1] < 30:break# show the resized imagecv2.imshow("Layer {}".format(i + 1), resized)cv2.waitKey(0)resized = resized*255cv2.imwrite('./'+WinName+'.jpg',resized[:,:,:])

使用Image.open效果

Layer 1 = 1024 X 768

Layer 2 = 512 X 384

Layer 3 = 256 X 192

Layer 4 = 128 X 96

Layer 5 = 64 X 48

使用cv2.imread效果

Layer 1 = 1024 X 768

Layer 2 = 512 X 384

Layer 3 = 256 X 192

Layer 4 = 128 X 96

Layer 5 = 64 X 48

参考

【1】Image Pyramids with Python and OpenCV - PyImageSearch
http://www.pyimagesearch.com/2015/03/16/image-pyramids-with-python-and-opencv/
【2】jrosebr1/imutils: A series of convenience functions to make basic image processing operations such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images easier with OpenCV and Python.
https://github.com/jrosebr1/imutils
【3】Histogram of Oriented Gradients and Object Detection - PyImageSearch
http://www.pyimagesearch.com/2014/11/10/histogram-oriented-gradients-object-detection/
【4】Module: transform — skimage v0.14dev docs
http://scikit-image.org/docs/dev/api/skimage.transform.html#pyramid-gaussian

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