Mahotas 简明教程

Mahotas - Histogram of Image

图像的直方图是指显示图像中像素强度分布的图形表示形式。它提供了有关图像中不同强度值出现频率的信息。

A histogram of an image refers to a graphical representation that shows the distribution of pixel intensities within the image. It provides information about the frequency of occurrence of different intensity values in the image.

直方图的水平轴（X 轴）表示图像中可能强度值的范围，而垂直轴（Y 轴）表示具有特定强度值像素的频率或数量。

The horizontal axis (X−aixs) of a histogram represents the range of possible intensity values in an image, while the vertical axis (Y−axis) represents the frequency or number of pixels that have a particular intensity value.

Histogram of Image in Mahotas

要在 Mahotas 中计算图像的直方图，我们可以使用该库提供的 fullhistogram() 函数。此函数将返回一个表示直方图值的数组。

To compute the histogram of an image in Mahotas, we can use the fullhistogram() function provided by the library. This function will return an array representing the histogram values.

直方图数组包含代表图像中可能像素值的 bin。每个 bin 都对应于一个特定的强度级，指示具有该特定值的像素的频率或计数。

A histogram array contains bins representing possible pixel values in an image. Each bin corresponds to a specific intensity level, indicating the frequency or count of pixels with that particular value.

例如，在 8 位灰度图像中，直方图数组有 256 个 bin，表示 0 到 255 的强度级。

For example, in an 8−bit grayscale image, the histogram array has 256 bins representing intensity levels from 0 to 255.

The mahotas.fullhistogram() function

Mahotas 中的 mahotas.fullhistogram() 函数以图像作为输入，并返回一个表示直方图的数组。此函数通过计算每个强度级或 bin 中的像素数来计算直方图。

The mahotas.fullhistogram() function in Mahotas takes an image as input and returns an array representing the histogram. This function calculates the histogram by counting the number of pixels at each intensity level or bin.

Syntax

以下是 mahotas 中 fullhistogram() 函数的基本语法：

Following is the basic syntax of the fullhistogram() function in mahotas −

mahotas.fullhistogram(image)

其中， 'image' 是无符号类型的输入图像。

Where, 'image' is the input image of an unsigned type.

Mahotas 只能处理此函数中的无符号整数数组

Mahotas can handle only unsigned integer arrays in this function

Example

在以下示例中，我们尝试使用 fullhistogram() 函数显示彩色图像的直方图：

In the following example, we are trying to display the histogram of a colored image using the fullhistogram() function −

import mahotas as mh
import numpy as np
from pylab import imshow, show
import matplotlib.pyplot as plt
image = mh.imread('sun.png')
hist = mh.fullhistogram(image)
plt.hist(hist)
plt.show()

执行上面的代码后，我们得到以下输出： -

After executing the above code, we get the following output −

histogram image

Grayscale Image Histogram

mahotas 中的灰度图像直方图是指灰度图像中像素强度分布的表示形式。

The grayscale image histogram in mahotas refers to a representation of the distribution of pixel intensities in a grayscale image.

灰度图像通常具有从 0（黑色）到 255（白色）的像素强度。默认情况下，Mahotas 在计算直方图时会考虑像素强度的整个范围。

The grayscale images generally have pixel intensities ranging from 0 (black) to 255 (white). By default, Mahotas considers the full range of pixel intensities when calculating the histogram.

这意味着从 0 到 255 的所有强度都包含在直方图计算中。

This means that all intensities from 0 to 255 are included in the histogram calculation.

通过考虑 256 个 bin 和像素强度的整个范围，Mahotas 提供了灰度图像中像素强度分布的全面表示。

By considering 256 bins and the full range of pixel intensities, Mahotas provides a comprehensive representation of the distribution of pixel intensities in the grayscale image.

Example

在这里，我们尝试使用 mahotas 显示灰度图像直方图：

In here, we are trying to display the grayscale image histogram using mahotas −

import mahotas as mh
import numpy as np
import matplotlib.pyplot as plt
# Convert image array to uint8 type
image = mh.imread('sun.png', as_grey=True).astype(np.uint8)
hist = mh.fullhistogram(image)
plt.hist(hist)
plt.show()

下面显示了产生的输出：

The output produced is as shown below −

grayscale histogram image

Blue Channel RGB Image Histogram

蓝色通道包含每个像素的蓝色颜色分量的信息。

The blue channel contains the information about the blue color component of each pixel.

我们将 mahotas 库与 numpy 和 matplotlib 结合使用，从 RGB 图像中提取蓝色通道。

We will use the mahotas library in conjunction with numpy and matplotlib to extract the blue channel from an RGB image.

我们可以通过使用数组切片选择第三个（索引 2）通道来从 RGB 图像中提取蓝色通道。这为我们提供了一个代表蓝色分量强度的灰度图像。

We can extract the blue channel from the RGB image by selecting the third (index 2) channel using array slicing. This gives us a grayscale image representing the blue component intensities.

然后，使用 numpy，我们计算蓝色通道的直方图。我们将蓝色通道数组展平以创建一个 1D 数组，确保在图像中的所有像素上计算直方图。

Then, using numpy, we calculate the histogram of the blue channel. We flatten the blue channel array to create a 1D array, ensuring that the histogram is computed over all the pixels in the image.

最后，我们使用 matplotlib 可视化直方图。

Finally, we use matplotlib to visualize the histogram.

Example

现在，我们尝试显示蓝色通道的 RGB 图像直方图 -

Now, we are trying to display the RGB image histogram of blue channel −

import mahotas as mh
import numpy as np
import matplotlib.pyplot as plt
# Loading RGB image
image = mh.imread('sea.bmp')
# Extracting the blue channel
blue_channel = image[:, :, 2]
# Calculating the histogram using numpy
hist, bins = np.histogram(blue_channel.flatten(), bins=256, range=[0, 256])
# Plot histogram
plt.bar(range(len(hist)), hist)
plt.xlabel('Pixel Value')
plt.ylabel('Frequency')
plt.title('Histogram of Blue Channel')
plt.show()

以下是上面代码的输出： -

Following is the output of the above code −

blue channel rgb image