从灰度图片创建彩色图片 [英] Create colour picture from greyscale picture

问题描述

我有一个值从0到1000的矩阵，我可以轻松地将值缩放到0〜255范围，如果我在Python的opencv中显示矩阵，那是一张灰度图片.

I have a matrix with values from 0 to 1000, I can easily scale the values to the 0~255 range, and that is a greyscale picture if I show the matrix in opencv from Python.

问题是，如何将矩阵{Dimensions =(m，n)}转换为三层矩阵数组{Dimensions =(m，n，3)}?

The question is, how do I convert the Matrix {Dimensions = (m, n)} to a 3-layer matrix array {Dimensions = (m, n, 3)}?

这是如何将灰度图片转换为彩色图片?

This is, how to convert a greyscale picture to a colour picture?

我已经完成了此功能，但无法正常工作

I have made this function but it is not working

 import matplotlib.pyplot as plt
 from itertools import product  

 def convertPicturetoColor(self, image, cmap=plt.get_cmap('rainbow')):
     '''
     Converts a greyscale [0~255] picture to a color picture
     '''
     a, b = np.shape(image)
     m = np.zeros((a, b, 3))
     for i, j in product(xrange(a), xrange(b)):
         m[i,j,:] = np.array(cmap(image[i,j]))[0:3]
     return m

推荐答案

>>> help(cv2.applyColorMap)
Help on built-in function applyColorMap:

applyColorMap(...)
    applyColorMap(src, colormap[, dst]) -> dst

这是地图枚举:

COLORMAP_AUTUMN = 0
COLORMAP_BONE = 1
COLORMAP_COOL = 8
COLORMAP_HOT = 11
COLORMAP_HSV = 9
COLORMAP_JET = 2
COLORMAP_OCEAN = 5
COLORMAP_PINK = 10
COLORMAP_RAINBOW = 4
COLORMAP_SPRING = 7
COLORMAP_SUMMER = 6
COLORMAP_WINTER = 3

所以，简单地:

dst = cv2.applyColorMap(src, cv2.COLORMAP_RAINBOW)

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