本想再用滑動窗口計算寫代碼計算局部方差，網上查了下，matlab提供stdfilt函數來計算局部方差：
matlab內的解釋是：
stdfilt
圖像的局部方差
語法
J = stdfilt(I)
J = stdfilt(I, NHOOD)
Description
J = stdfilt(I) returns thearray J, where each output pixel contains the standarddeviation of the 3-by-3 neighborhood around the corresponding pixelin the input image I. I canhave any dimension. The output image J is the samesize as the input image I.
For pixels on the borders of I, stdfilt usessymmetric padding. In symmetric padding, the values of padding pixelsare a mirror reflection of the border pixels in I.
J = stdfilt(I, NHOOD) calculatesthe local standard deviation of the input image I,where you specify the neighborhood in NHOOD. NHOOD isa multidimensional array of zeros and ones where the nonzero elementsspecify the neighbors. NHOOD's size must be oddin each dimension.
By default, stdfilt uses the neighborhood ones(3). stdfilt determinesthe center element of the neighborhood by floor((size(NHOOD)+ 1)/2).
Class Support
I can be logical or numeric and must bereal and nonsparse. NHOOD can be logical or numericand must contain zeros and/or ones. J is of classdouble.
Notes
To specify neighborhoods of various shapes, such as a disk,use the strel function to create a structuringelement object and then use the getnhood functionto extract the neighborhood from the structuring element object.
Examples
I = imread('circuit.tif');
J = stdfilt(I);
imshow(I);
figure, imshow(J,[]);
matlab就是如此強大。
針對我們的問題，我們可以這樣調用：
I = imread('E:\\110.jpg');
I = im2double(rgb2gray(I));%轉化為灰度圖像
J= stdfilt(I) ；%計算局部方差
imshow(J)%顯示圖像
dlmwrite('E:\\a.txt',J,'delimiter',' ','newline','pc'); %當然可以保存數據
但更有意思的是，我們可以在Python上模擬實現：
import cv2
import numpy as np
img = cv2.imread('fruits.jpg', True)
img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
img = img / 255.0
# c = imfilter(I,h,'symmetric');
h = np.ones((3,3))
n = h.sum()
n1 = n - 1
c1 = cv2.filter2D(img**2, -1, h/n1, borderType=cv2.BORDER_REFLECT)
c2 = cv2.filter2D(img, -1, h, borderType=cv2.BORDER_REFLECT)**2 / (n*n1)
J = np.sqrt( np.maximum(c1-c2,0) )
cv2.imshow('stdfilt', J)
cv2.waitKey(0)
cv2.destroyWindow('stdfilt')