设计一个用于图像处理的可视化界面，能够至少实现图像的读取与显示、图像的直方图统计、图像直方图均衡化增强、图像的全局阈值分割、图像的边缘检测等功能。

这是一个比较复杂的项目，需要结合多种技术和工具来实现。下面是一个简单的可视化界面示例，实现了图像的读取与显示、直方图统计、直方图均衡化、全局阈值分割和边缘检测等功能：

import sys
from PyQt5.QtWidgets import QApplication, QMainWindow, QWidget, QLabel, QFileDialog, QHBoxLayout, QVBoxLayout, QSlider, QPushButton
from PyQt5.QtGui import QPixmap, QImage
from PyQt5.QtCore import Qt
import cv2
import numpy as np


class MainWindow(QMainWindow):
    def __init__(self):
        super().__init__()

        # 创建主窗口
        self.setWindowTitle("图像处理")
        self.setGeometry(100, 100, 800, 600)

        # 创建中心窗口
        self.central_widget = QWidget()
        self.setCentralWidget(self.central_widget)

        # 创建图像标签
        self.image_label = QLabel()
        self.image_label.setAlignment(Qt.AlignCenter)

        # 创建滚动区域
        self.scroll_area = QScrollArea()
        self.scroll_area.setWidget(self.image_label)

        # 创建直方图标签
        self.hist_label = QLabel()
        self.hist_label.setAlignment(Qt.AlignCenter)

        # 创建滚动区域
        self.hist_scroll_area = QScrollArea()
        self.hist_scroll_area.setWidget(self.hist_label)

        # 创建布局
        layout = QHBoxLayout()
        layout.addWidget(self.scroll_area)
        layout.addWidget(self.hist_scroll_area)

        # 创建控制面板
        control_panel = QWidget()
        control_layout = QVBoxLayout(control_panel)

        # 创建按钮
        self.load_button = QPushButton("读取图像")
        self.equalize_button = QPushButton("直方图均衡化")
        self.threshold_button = QPushButton("全局阈值分割")
        self.canny_button = QPushButton("边缘检测")

        # 创建滑动条
        self.threshold_slider = QSlider(Qt.Horizontal)
        self.threshold_slider.setMinimum(0)
        self.threshold_slider.setMaximum(255)
        self.threshold_slider.setValue(128)

        # 添加控件到布局中
        control_layout.addWidget(self.load_button)
        control_layout.addWidget(self.equalize_button)
        control_layout.addWidget(self.threshold_button)
        control_layout.addWidget(self.canny_button)
        control_layout.addWidget(self.threshold_slider)

        # 连接信号和槽
        self.load_button.clicked.connect(self.load_image)
        self.equalize_button.clicked.connect(self.equalize_image)
        self.threshold_button.clicked.connect(self.threshold_image)
        self.canny_button.clicked.connect(self.canny_image)
        self.threshold_slider.valueChanged.connect(self.threshold_image)

        # 添加布局到中心窗口
        self.central_widget.setLayout(layout)
        self.central_widget.layout().addWidget(control_panel)

        # 初始化图像和直方图
        self.image = None
        self.hist = None

    def load_image(self):
        # 打开文件对话框
        filename, _ = QFileDialog.getOpenFileName(self, "打开图像", "", "图像文件 (*.jpg *.png *.bmp)")
        if filename:
            # 读取图像
            self.image = cv2.imread(filename)

            # 将图像转换为RGB格式
            self.image = cv2.cvtColor(self.image, cv2.COLOR_BGR2RGB)

            # 在标签中显示图像
            pixmap = QPixmap.fromImage(QImage(self.image.data, self.image.shape[1], self.image.shape[0], QImage.Format_RGB888))
            self.image_label.setPixmap(pixmap)

            # 显示直方图
            self.show_hist()

    def show_hist(self):
        if self.image is not None:
            # 计算直方图
            gray_image = cv2.cvtColor(self.image, cv2.COLOR_RGB2GRAY)
            hist, bins = np.histogram(gray_image.flatten(), 256, [0, 256])

            # 绘制直方图
            hist_image = np.zeros((256, 256), dtype=np.uint8)
            cv2.normalize(hist, hist, 0, 255, cv2.NORM_MINMAX)
            hist = np.int32(np.around(hist))
            for i in range(hist.shape[0]):
                cv2.line(hist_image, (i, 255), (i, 255 - hist[i]), 255)

            # 在标签中显示直方图
            hist_pixmap = QPixmap.fromImage(QImage(hist_image.data, hist_image.shape[1], hist_image.shape[0], QImage.Format_Grayscale8))
            self.hist_label.setPixmap(hist_pixmap)

    def equalize_image(self):
        if self.image is not None:
            # 将图像转换为灰度图像
            gray_image = cv2.cvtColor(self.image, cv2.COLOR_RGB2GRAY)

            # 均衡化直方图
            equalized_image = cv2.equalizeHist(gray_image)

            # 将图像转换为RGB格式
            equalized_image = cv2.cvtColor(equalized_image, cv2.COLOR_GRAY2RGB)

            # 在标签中显示图像
            pixmap = QPixmap.fromImage(QImage(equalized_image.data, equalized_image.shape[1], equalized_image.shape[0], QImage.Format_RGB888))
            self.image_label.setPixmap(pixmap)

            # 显示直方图
            self.show_hist()

    def threshold_image(self):
        if self.image is not None:
            # 将图像转换为灰度图像
            gray_image = cv2.cvtColor(self.image, cv2.COLOR_RGB2GRAY)

            # 应用全局阈值分割
            threshold_value = self.threshold_slider.value()
            ret, thresholded_image = cv2.threshold(gray_image, threshold_value, 255, cv2.THRESH_BINARY)

            # 将图像转换为RGB格式
            thresholded_image = cv2.cvtColor(thresholded_image, cv2.COLOR_GRAY2RGB)

            # 在标签中显示图像
            pixmap = QPixmap.fromImage(QImage(thresholded_image.data, thresholded_image.shape[1], thresholded_image.shape[0], QImage.Format_RGB888))
            self.image_label.setPixmap(pixmap)

            # 显示直方图
            self.show_hist()

    def canny_image(self):
        if self.image is not None:
            # 将图像转换为灰度图像
            gray_image = cv2.cvtColor(self.image, cv2.COLOR_RGB2GRAY)

            # 边缘检测
            edges = cv2.Canny(gray_image, 100, 200)

            # 将图像转换为RGB格式
            edges = cv2.cvtColor(edges, cv2.COLOR_GRAY2RGB)

            # 在标签中显示图像
            pixmap = QPixmap.fromImage(QImage(edges.data, edges.shape[1], edges.shape[0], QImage.Format_RGB888))
            self.image_label.setPixmap(pixmap)

            # 显示直方图
            self.show_hist()


if __name__ == '__main__':
    app = QApplication(sys.argv)
    window = MainWindow()
    window.show()
    sys.exit(app.exec_())

这个示例程序使用PyQt5实现了一个简单的图像处理可视化界面，包括图像的读取与显示、直方图统计、直方图均衡化、全局阈值分割和边缘检测等功能。你可以根据自己的需要修改代码，添加更多功能。