Python图像处理（5）：直方图

快乐虾

http://blog.csdn.net/lights_joy/

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直方图的计算采用OpenCV的calcHist完成。

OpenCV的C++接口中calcHist有三种形式：

//! computes the joint dense histogram for a set of images.CV_EXPORTS void calcHist( const Mat* images, int nimages,                          const int* channels, InputArray mask,                          OutputArray hist, int dims, const int* histSize,                          const float** ranges, bool uniform=true, bool accumulate=false );//! computes the joint sparse histogram for a set of images.CV_EXPORTS void calcHist( const Mat* images, int nimages,                          const int* channels, InputArray mask,                          SparseMat& hist, int dims,                          const int* histSize, const float** ranges,                          bool uniform=true, bool accumulate=false );CV_EXPORTS_W void calcHist( InputArrayOfArrays images,                            const vector<int>& channels,                            InputArray mask, OutputArray hist,                            const vector<int>& histSize,                            const vector<float>& ranges,                            bool accumulate=false );

但导出的Python接口却只有一个：

static PyObject* pyopencv_calcHist(PyObject* , PyObject* args, PyObject* kw){    PyObject* pyobj_images = NULL;    vector_Mat images;    PyObject* pyobj_channels = NULL;    vector_int channels;    PyObject* pyobj_mask = NULL;    Mat mask;    PyObject* pyobj_hist = NULL;    Mat hist;    PyObject* pyobj_histSize = NULL;    vector_int histSize;    PyObject* pyobj_ranges = NULL;    vector_float ranges;    bool accumulate=false;    const char* keywords[] = { "images", "channels", "mask", "histSize", "ranges", "hist", "accumulate", NULL };    if( PyArg_ParseTupleAndKeywords(args, kw, "OOOOO|Ob:calcHist", (char**)keywords, &pyobj_images, &pyobj_channels, &pyobj_mask, &pyobj_histSize, &pyobj_ranges, &pyobj_hist, &accumulate) &&        pyopencv_to(pyobj_images, images, ArgInfo("images", 0)) &&        pyopencv_to(pyobj_channels, channels, ArgInfo("channels", 0)) &&        pyopencv_to(pyobj_mask, mask, ArgInfo("mask", 0)) &&        pyopencv_to(pyobj_hist, hist, ArgInfo("hist", 1)) &&        pyopencv_to(pyobj_histSize, histSize, ArgInfo("histSize", 0)) &&        pyopencv_to(pyobj_ranges, ranges, ArgInfo("ranges", 0)) )    {        ERRWRAP2( cv::calcHist(images, channels, mask, hist, histSize, ranges, accumulate));        return pyopencv_from(hist);    }    return NULL;}

因此Python的接口看起来有点奇怪：

hist = cv2.calcHist([src], [0], None, [256], [0, 255])

即使是只对一张图片进行操作，也必须使用数组的形式进行参数传递。

写个简单的Python程序，获取单个通道的直方图：

# -*- coding: utf-8 -*- import cv2import numpy as npimport matplotlib.pyplot as plt# 单通道直方图测试src = cv2.imread('f:\\tmp\\cotton.jpg')cv2.imshow('src', src)hist = cv2.calcHist([src], [0], None, [256], [0, 255])plt.plot(hist)plt.show()cv2.waitKey()

结果如下：

符合我们对直方图的预期。