From 6ed7cee4476f16486ee3ab95cc945435d641885e Mon Sep 17 00:00:00 2001 From: pos97em56 <10225101485@ecnu.stu.edu.cn> Date: Wed, 3 Jul 2024 20:18:02 +0800 Subject: [PATCH] Update noise_filter.py --- basic/noise_filter.py | 594 +++++++++++++++++++++--------------------- 1 file changed, 292 insertions(+), 302 deletions(-) diff --git a/basic/noise_filter.py b/basic/noise_filter.py index 2c6fde9..a48e114 100644 --- a/basic/noise_filter.py +++ b/basic/noise_filter.py @@ -1,303 +1,293 @@ -import tkinter as tk -from tkinter import filedialog, messagebox -from tkinter import Toplevel -from PIL import Image, ImageTk -import numpy as np -import math -import cv2 -import os - -img_path = "" # 全局变量，用于存储图像路径 -src = None # 全局变量，用于存储已选择的图像 -X = None # 用于存储第一张图像 -Y = None # 用于存储第二张图像 -img_label = None # 全局变量，用于存储显示选择的图片的标签 - -GeomeanWin = None -SortstatWin = None -SelectWin = None - -def select_image(root): - global img_path, src, img_label, edge - - img_path = filedialog.askopenfilename(filetypes=[("Image files", "*.jpg;*.png;*.jpeg;*.bmp")]) - if img_path: - # 确保路径中的反斜杠正确处理，并使用 UTF-8 编码处理中文路径 - img_path_fixed = os.path.normpath(img_path) - - # 图像输入 - src_temp = cv2.imdecode(np.fromfile(img_path_fixed, dtype=np.uint8), cv2.IMREAD_UNCHANGED) - if src_temp is None: - messagebox.showerror("错误", "无法读取图片，请选择有效的图片路径") - return - src = cv2.cvtColor(src_temp, cv2.COLOR_BGR2RGB) - - # 检查 img_label 是否存在且有效 - if img_label is None or not img_label.winfo_exists(): - img_label = tk.Label(root) - img_label.pack(side=tk.TOP, pady=10) - - img = Image.open(img_path) - img.thumbnail((160, 160)) - img_tk = ImageTk.PhotoImage(img) - img_label.configure(image=img_tk) - img_label.image = img_tk - - # 定义 edge 变量为 PIL.Image 对象，以便稍后保存 - edge = Image.fromarray(src) - else: - messagebox.showerror("错误", "没有选择图片路径") - -def show_selected_image(root): - global img_label - img_label = tk.Label(root) - img_label.pack(side=tk.TOP, pady=10) - img = Image.open(img_path) - img.thumbnail((160, 160)) - img_tk = ImageTk.PhotoImage(img) - img_label.configure(image=img_tk) - img_label.image = img_tk - -def changeSize(event, img, LabelPic): - img_aspect = img.shape[1] / img.shape[0] - new_aspect = event.width / event.height - - if new_aspect > img_aspect: - new_width = int(event.height * img_aspect) - new_height = event.height - else: - new_width = event.width - new_height = int(event.width / img_aspect) - - resized_image = cv2.resize(img, (new_width, new_height)) - image1 = ImageTk.PhotoImage(Image.fromarray(resized_image)) - LabelPic.image = image1 - LabelPic['image'] = image1 - -def savefile(): - global edge - - filename = filedialog.asksaveasfilename(defaultextension=".jpg", filetypes=[("JPEG files", "*.jpg"), ("PNG files", "*.png"), ("BMP files", "*.bmp")]) - if not filename: - return - # 确保 edge 变量已定义 - if edge is not None: - try: - edge.save(filename) - messagebox.showinfo("保存成功", "图片保存成功！") - except Exception as e: - messagebox.showerror("保存失败", f"无法保存图片: {e}") - else: - messagebox.showerror("保存失败", "没有图像可保存") - -#几何均值滤波 -def geo_mean_filter(root): - global src, GeomeanWin, edge - - # 判断是否已经选取图片 - if src is None: - messagebox.showerror("错误", "没有选择图片！") - return - - image = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY) - - # 待输出的图片 - output = np.zeros(image.shape, np.uint8) - # 遍历图像，进行均值滤波 - for i in range(image.shape[0]): - for j in range(image.shape[1]): - # 计算均值,完成对图片src的几何均值滤波 - ji = 1.0 - - # 遍历滤波器内的像素值 - for k in range(-1, 2): - if 0 <= j + k < image.shape[1]: - ji *= image[i, j + k] - - # 滤波器的大小为1*3 - geom_mean = math.pow(ji, 1 / 3.0) - output[i, j] = int(geom_mean) - - # 更新 edge 变量 - edge = Image.fromarray(output) - - # 创建Toplevel窗口 - try: - GeomeanWin.destroy() - except Exception: - print("NVM") - finally: - GeomeanWin = Toplevel() - GeomeanWin.attributes('-topmost', True) - GeomeanWin.geometry("720x300") - GeomeanWin.resizable(True, True) # 可缩放 - GeomeanWin.title("几何均值滤波结果") - - # 显示图像 - LabelPic = tk.Label(GeomeanWin, text="IMG", width=360, height=240) - image = ImageTk.PhotoImage(Image.fromarray(output)) - LabelPic.image = image - LabelPic['image'] = image - - LabelPic.bind('', lambda event: changeSize(event, output, LabelPic)) - LabelPic.pack(fill=tk.BOTH, expand=tk.YES) - - # 添加保存按钮 - btn_save = tk.Button(GeomeanWin, text="保存", bg='#add8e6', fg='black', font=('Helvetica', 14), width=20, - command=savefile) - btn_save.pack(pady=10) - - return - -#排序统计类滤波 -def sort_stat_filter(root): - global src, SortstatWin, combined, edge - - # 判断是否已经选取图片 - if src is None: - messagebox.showerror("错误", "没有选择图片！") - return - - image = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY) - - # 待输出的图片 - output_max = np.zeros(image.shape, np.uint8) - output_median = np.zeros(image.shape, np.uint8) - output_min = np.zeros(image.shape, np.uint8) - - # 遍历图像 - for i in range(image.shape[0]): - for j in range(image.shape[1]): - # 用于存储3x3邻域像素值 - neighbors = [] - for m in range(-1, 2): - for n in range(-1, 2): - if 0 <= i + m < image.shape[0] and 0 <= j + n < image.shape[1]: - neighbors.append(image[i + m, j + n]) - - # 最大值滤波 - output_max[i, j] = max(neighbors) - # 中值滤波 - output_median[i, j] = np.median(neighbors) - # 最小值滤波 - output_min[i, j] = min(neighbors) - - combined = np.hstack((output_max, output_median, output_min)) - - # 更新 edge 变量 - edge = Image.fromarray(combined) - - # 创建Toplevel窗口 - try: - SortstatWin.destroy() - except Exception: - print("NVM") - finally: - SortstatWin = Toplevel() - SortstatWin.attributes('-topmost', True) - SortstatWin.geometry("720x300") - SortstatWin.resizable(True, True) # 可缩放 - SortstatWin.title("排序统计类滤波结果") - - # 显示图像 - LabelPic = tk.Label(SortstatWin, text="IMG", width=360, height=240) - image = ImageTk.PhotoImage(Image.fromarray(combined)) - LabelPic.image = image - LabelPic['image'] = image - - LabelPic.bind('', lambda event: changeSize(event, combined, LabelPic)) - LabelPic.pack(fill=tk.BOTH, expand=tk.YES) - - # 添加保存按钮 - btn_save = tk.Button(SortstatWin, text="保存", bg='#add8e6', fg='black', font=('Helvetica', 14), width=20, - command=savefile) - btn_save.pack(pady=10) - - return - -#选择性滤波 -def selective_filter(root): - global src, SelectWin, combined, edge - - # 判断是否已经选取图片 - if src is None: - messagebox.showerror("错误", "没有选择图片！") - return - - image = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY) - - # 待输出的图片 - output_low_pass = np.zeros(image.shape, np.uint8) - output_high_pass = np.zeros(image.shape, np.uint8) - output_band_pass = np.zeros(image.shape, np.uint8) - output_band_stop = np.zeros(image.shape, np.uint8) - - # 边界 - low_pass_threshold = 100 - high_pass_threshold = 100 - band_pass_low_threshold = 100 - band_pass_high_threshold = 200 - band_stop_low_threshold = 100 - band_stop_high_threshold = 200 - - # 遍历图像 - for i in range(image.shape[0]): - for j in range(image.shape[1]): - pixel_value = image[i][j] - - # 低通滤波器 - if pixel_value <= low_pass_threshold: - output_low_pass[i][j] = pixel_value - else: - output_low_pass[i][j] = 0 - - # 高通滤波器 - if pixel_value >= high_pass_threshold: - output_high_pass[i][j] = pixel_value - else: - output_high_pass[i][j] = 0 - - # 带通滤波器 - if band_pass_low_threshold < pixel_value <= band_pass_high_threshold: - output_band_pass[i][j] = pixel_value - else: - output_band_pass[i][j] = 0 - - # 带阻滤波器 - if band_stop_low_threshold < pixel_value <= band_stop_high_threshold: - output_band_stop[i][j] = 0 - else: - output_band_stop[i][j] = pixel_value - - combined = np.hstack((output_low_pass, output_high_pass, output_band_pass, output_band_stop)) - - # 更新 edge 变量 - edge = Image.fromarray(combined) - - # 创建Toplevel窗口 - try: - SelectWin.destroy() - except Exception: - print("NVM") - finally: - SelectWin = Toplevel() - SelectWin.attributes('-topmost', True) - SelectWin.geometry("720x300") - SelectWin.resizable(True, True) # 可缩放 - SelectWin.title("选择性滤波结果") - - # 显示图像 - LabelPic = tk.Label(SelectWin, text="IMG", width=360, height=240) - image = ImageTk.PhotoImage(Image.fromarray(combined)) - LabelPic.image = image - LabelPic['image'] = image - - LabelPic.bind('', lambda event: changeSize(event, combined, LabelPic)) - LabelPic.pack(fill=tk.BOTH, expand=tk.YES) - - # 添加保存按钮 - btn_save = tk.Button(SelectWin, text="保存", bg='#add8e6', fg='black', font=('Helvetica', 14), width=20, - command=savefile) - btn_save.pack(pady=10) - +import tkinter as tk +from tkinter import filedialog, messagebox +from tkinter import Toplevel +from PIL import Image, ImageTk +import numpy as np +import math +import cv2 +import os + +img_path = "" # 全局变量，用于存储图像路径 +src = None # 全局变量，用于存储已选择的图像 +X = None # 用于存储第一张图像 +Y = None # 用于存储第二张图像 +img_label = None # 全局变量，用于存储显示选择的图片的标签 + +GeomeanWin = None +SortstatWin = None +SelectWin = None + +def select_image(root): + global img_path, src, img_label, edge + + img_path = filedialog.askopenfilename(filetypes=[("Image files", "*.jpg;*.png;*.jpeg;*.bmp")]) + if img_path: + # 确保路径中的反斜杠正确处理，并使用 UTF-8 编码处理中文路径 + img_path_fixed = os.path.normpath(img_path) + + # 图像输入 + src_temp = cv2.imdecode(np.fromfile(img_path_fixed, dtype=np.uint8), cv2.IMREAD_UNCHANGED) + if src_temp is None: + messagebox.showerror("错误", "无法读取图片，请选择有效的图片路径") + return + src = cv2.cvtColor(src_temp, cv2.COLOR_BGR2RGB) + + # 检查 img_label 是否存在且有效 + if img_label is None or not img_label.winfo_exists(): + img_label = tk.Label(root) + img_label.pack(side=tk.TOP, pady=10) + + img = Image.open(img_path) + img.thumbnail((160, 160)) + img_tk = ImageTk.PhotoImage(img) + img_label.configure(image=img_tk) + img_label.image = img_tk + + # 定义 edge 变量为 PIL.Image 对象，以便稍后保存 + edge = Image.fromarray(src) + else: + messagebox.showerror("错误", "没有选择图片路径") + +def changeSize(event, img, LabelPic): + img_aspect = img.shape[1] / img.shape[0] + new_aspect = event.width / event.height + + if new_aspect > img_aspect: + new_width = int(event.height * img_aspect) + new_height = event.height + else: + new_width = event.width + new_height = int(event.width / img_aspect) + + resized_image = cv2.resize(img, (new_width, new_height)) + image1 = ImageTk.PhotoImage(Image.fromarray(resized_image)) + LabelPic.image = image1 + LabelPic['image'] = image1 + +def savefile(): + global edge + + filename = filedialog.asksaveasfilename(defaultextension=".jpg", filetypes=[("JPEG files", "*.jpg"), ("PNG files", "*.png"), ("BMP files", "*.bmp")]) + if not filename: + return + # 确保 edge 变量已定义 + if edge is not None: + try: + edge.save(filename) + messagebox.showinfo("保存成功", "图片保存成功！") + except Exception as e: + messagebox.showerror("保存失败", f"无法保存图片: {e}") + else: + messagebox.showerror("保存失败", "没有图像可保存") + +#几何均值滤波 +def geo_mean_filter(root): + global src, GeomeanWin, edge + + # 判断是否已经选取图片 + if src is None: + messagebox.showerror("错误", "没有选择图片！") + return + + image = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY) + + # 待输出的图片 + output = np.zeros(image.shape, np.uint8) + # 遍历图像，进行均值滤波 + for i in range(image.shape[0]): + for j in range(image.shape[1]): + # 计算均值,完成对图片src的几何均值滤波 + ji = 1.0 + + # 遍历滤波器内的像素值 + for k in range(-1, 2): + if 0 <= j + k < image.shape[1]: + ji *= image[i, j + k] + + # 滤波器的大小为1*3 + geom_mean = math.pow(ji, 1 / 3.0) + output[i, j] = int(geom_mean) + + # 更新 edge 变量 + edge = Image.fromarray(output) + + # 创建Toplevel窗口 + try: + GeomeanWin.destroy() + except Exception: + print("NVM") + finally: + GeomeanWin = Toplevel() + GeomeanWin.attributes('-topmost', True) + GeomeanWin.geometry("720x300") + GeomeanWin.resizable(True, True) # 可缩放 + GeomeanWin.title("几何均值滤波结果") + + # 显示图像 + LabelPic = tk.Label(GeomeanWin, text="IMG", width=360, height=240) + image = ImageTk.PhotoImage(Image.fromarray(output)) + LabelPic.image = image + LabelPic['image'] = image + + LabelPic.bind('', lambda event: changeSize(event, output, LabelPic)) + LabelPic.pack(fill=tk.BOTH, expand=tk.YES) + + # 添加保存按钮 + btn_save = tk.Button(GeomeanWin, text="保存", bg='#add8e6', fg='black', font=('Helvetica', 14), width=20, + command=savefile) + btn_save.pack(pady=10) + + return + +#排序统计类滤波 +def sort_stat_filter(root): + global src, SortstatWin, combined, edge + + # 判断是否已经选取图片 + if src is None: + messagebox.showerror("错误", "没有选择图片！") + return + + image = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY) + + # 待输出的图片 + output_max = np.zeros(image.shape, np.uint8) + output_median = np.zeros(image.shape, np.uint8) + output_min = np.zeros(image.shape, np.uint8) + + # 遍历图像 + for i in range(image.shape[0]): + for j in range(image.shape[1]): + # 用于存储3x3邻域像素值 + neighbors = [] + for m in range(-1, 2): + for n in range(-1, 2): + if 0 <= i + m < image.shape[0] and 0 <= j + n < image.shape[1]: + neighbors.append(image[i + m, j + n]) + + # 最大值滤波 + output_max[i, j] = max(neighbors) + # 中值滤波 + output_median[i, j] = np.median(neighbors) + # 最小值滤波 + output_min[i, j] = min(neighbors) + + combined = np.hstack((output_max, output_median, output_min)) + + # 更新 edge 变量 + edge = Image.fromarray(combined) + + # 创建Toplevel窗口 + try: + SortstatWin.destroy() + except Exception: + print("NVM") + finally: + SortstatWin = Toplevel() + SortstatWin.attributes('-topmost', True) + SortstatWin.geometry("720x300") + SortstatWin.resizable(True, True) # 可缩放 + SortstatWin.title("排序统计类滤波结果") + + # 显示图像 + LabelPic = tk.Label(SortstatWin, text="IMG", width=360, height=240) + image = ImageTk.PhotoImage(Image.fromarray(combined)) + LabelPic.image = image + LabelPic['image'] = image + + LabelPic.bind('', lambda event: changeSize(event, combined, LabelPic)) + LabelPic.pack(fill=tk.BOTH, expand=tk.YES) + + # 添加保存按钮 + btn_save = tk.Button(SortstatWin, text="保存", bg='#add8e6', fg='black', font=('Helvetica', 14), width=20, + command=savefile) + btn_save.pack(pady=10) + + return + +#选择性滤波 +def selective_filter(root): + global src, SelectWin, combined, edge + + # 判断是否已经选取图片 + if src is None: + messagebox.showerror("错误", "没有选择图片！") + return + + image = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY) + + # 待输出的图片 + output_low_pass = np.zeros(image.shape, np.uint8) + output_high_pass = np.zeros(image.shape, np.uint8) + output_band_pass = np.zeros(image.shape, np.uint8) + output_band_stop = np.zeros(image.shape, np.uint8) + + # 边界 + low_pass_threshold = 100 + high_pass_threshold = 100 + band_pass_low_threshold = 100 + band_pass_high_threshold = 200 + band_stop_low_threshold = 100 + band_stop_high_threshold = 200 + + # 遍历图像 + for i in range(image.shape[0]): + for j in range(image.shape[1]): + pixel_value = image[i][j] + + # 低通滤波器 + if pixel_value <= low_pass_threshold: + output_low_pass[i][j] = pixel_value + else: + output_low_pass[i][j] = 0 + + # 高通滤波器 + if pixel_value >= high_pass_threshold: + output_high_pass[i][j] = pixel_value + else: + output_high_pass[i][j] = 0 + + # 带通滤波器 + if band_pass_low_threshold < pixel_value <= band_pass_high_threshold: + output_band_pass[i][j] = pixel_value + else: + output_band_pass[i][j] = 0 + + # 带阻滤波器 + if band_stop_low_threshold < pixel_value <= band_stop_high_threshold: + output_band_stop[i][j] = 0 + else: + output_band_stop[i][j] = pixel_value + + combined = np.hstack((output_low_pass, output_high_pass, output_band_pass, output_band_stop)) + + # 更新 edge 变量 + edge = Image.fromarray(combined) + + # 创建Toplevel窗口 + try: + SelectWin.destroy() + except Exception: + print("NVM") + finally: + SelectWin = Toplevel() + SelectWin.attributes('-topmost', True) + SelectWin.geometry("720x300") + SelectWin.resizable(True, True) # 可缩放 + SelectWin.title("选择性滤波结果") + + # 显示图像 + LabelPic = tk.Label(SelectWin, text="IMG", width=360, height=240) + image = ImageTk.PhotoImage(Image.fromarray(combined)) + LabelPic.image = image + LabelPic['image'] = image + + LabelPic.bind('', lambda event: changeSize(event, combined, LabelPic)) + LabelPic.pack(fill=tk.BOTH, expand=tk.YES) + + # 添加保存按钮 + btn_save = tk.Button(SelectWin, text="保存", bg='#add8e6', fg='black', font=('Helvetica', 14), width=20, + command=savefile) + btn_save.pack(pady=10) + return \ No newline at end of file