Python：使用 openCV 保存（cv2.imwrite）和讀取（cv2.imread）過程中的隱寫問題

Question

我有一個將圖像隱藏在另一個圖像中的隱寫術代碼。

我通過此代碼將水印注入到我的圖像中。

原理很簡單。

我使用source_image和watermark_images插入水印。

這將隨機分配watermark_images 。

首先，使用隨機種子分散水印圖像的 x 和 y。

然后，使用快速傅里葉變換將source_image轉換為頻率區域。

最后，將watermark_layer與source_image的頻率區域結合起來。

此編碼過程運行良好。 但是，在解碼的過程中存在問題。

解碼代碼是按照相同的原理將隨機種子分散在一個地方的像素收集起來。

這是解碼的結果：

這個問題，如果我嘗試將圖像編碼到保存（cv2.imwrite）並調用（cv2.imread），解碼不起作用。

如果我按原樣使用已編碼的 object，則沒有問題。 保存和調用過程中像素是否損壞？

這是我的完整代碼：

import cv2 as cv
import numpy as np
import random
import time


class Watermark:
    def __init__(self):
        self.watermark_image = cv.imread('../Watermark/google_logo.png')
        self.result_image_path = '../Watermark/result.jpg'
        self.random_seed = 2021
        self.alpha = 5

    def encoding(self, image_path):
        # Code Start
        start_time = time.time()

        # Read Image
        source_image = cv.imread(image_path)
        source_height, source_width, _ = source_image.shape
        watermark_height, watermark_width, _ = self.watermark_image.shape

        print('source height : ', source_height, ', source_width : ', source_width)
        print('watermark height : ', watermark_height, ', watermark width : ', watermark_width)

        # Convert image to frequency area with Fast Fourier Transform (image -> frequency)
        source_frequency = np.fft.fft2(source_image)

        # Get random seed
        y_random_indices, x_random_indices = list(range(source_height)), list(range(source_width))
        random.seed(self.random_seed)
        random.shuffle(x_random_indices)
        random.shuffle(y_random_indices)

        print('y random seed : ', y_random_indices)
        print('x random seed : ', x_random_indices)

        # Injection watermark
        watermark_layer = np.zeros(source_image.shape, dtype=np.uint8)
        for y in range(watermark_height):
            for x in range(watermark_width):
                watermark_layer[y_random_indices[y], x_random_indices[x]] = self.watermark_image[y, x]

        # Encoding frequency area + watermark layer
        result_frequency = source_frequency + self.alpha * watermark_layer

        # Apply Inverse Fast Fourier Transform (frequency -> image)
        result_image = np.fft.ifft2(result_frequency)
        result_image = np.real(result_image)
        result_image = result_image.astype(np.uint8)

        # Show elapsed time
        end_time = time.time()
        print('Encoding elapsed time : ', end_time - start_time, '\n')

        # Visualization
        cv.imshow('source_image', source_image)
        cv.imshow('watermark', self.watermark_image)
        cv.imshow('watermark_layer', watermark_layer)
        cv.imshow('result_image', result_image)

        # Save and Close
        cv.imwrite(self.result_image_path, result_image)
        cv.waitKey(0)
        cv.destroyAllWindows()

        return result_image

    def decoding(self, source_image_path, encoded_image):
        # Code Start
        start_time = time.time()

        # Read Image
        source_image = cv.imread(source_image_path)

        source_height, source_width, _ = source_image.shape
        print('original_height : ', source_height)
        print('original_width : ', source_width)

        encoded_height, encoded_width, _ = encoded_image.shape

        # Convert image to frequency area with Fast Fourier Transform (image -> frequency)
        source_frequency = np.fft.fft2(source_image)
        encoded_frequency = np.fft.fft2(encoded_image)

        # Convert frequency area to image (frequency -> image)
        watermark_layer = (source_frequency - encoded_frequency) / self.alpha
        watermark_layer = np.real(watermark_layer).astype(np.uint8)

        # Get random seed
        y_random_indices, x_random_indices = [list(range(encoded_height)), list(range(encoded_width))]
        random.seed(self.random_seed)
        random.shuffle(x_random_indices)
        random.shuffle(y_random_indices)

        print('y random seed : ', y_random_indices)
        print('x random seed : ', x_random_indices)

        # Restore watermark
        result_image = np.zeros(watermark_layer.shape, dtype=np.uint8)

        for y in range(encoded_height):
            for x in range(encoded_width):
                result_image[y, x] = watermark_layer[y_random_indices[y], x_random_indices[x]]

        # Show elapsed time
        end_time = time.time()
        print('Encoding elapsed time : ', end_time - start_time, '\n')

        # Visualization
        cv.imshow('original image', source_image)
        cv.imshow('target image', encoded_image)
        cv.imshow('watermark layer', watermark_layer)
        cv.imshow('result image', result_image)
        cv.waitKey(0)
        cv.destroyAllWindows()


if __name__ == '__main__':
    source_path = '../Watermark/jennie.jpg'

    # good work
    protected_image = Watermark().encoding(source_path)
    Watermark().decoding(source_path, protected_image)

    # doesn't work
    result_path = '../Watermark/result.jpg'
    result_image = cv.imread(result_path)
    Watermark().decoding(source_path, result_image)

請給我一些建議。

Answer 1

Carlos Melus 有一個很好的觀點。

您的代碼不適合處理 jpg 圖像。

如果你使用 png 格式，效果會很好。