Contrast Limited Adaptive Histogram Equalization
Histogram Equalization (히스토그램 평활화)/CLAHE
Histogram Equalization은 이미지의 픽셀이 특정 범위 값 주변에 분포해 있을 때, 양쪽 끝으로 히스토그램을 펼쳐서 Contrast 조정하는 방법이다. 예제는 이미지를 histogram equlization을 사용해서 Contrast..
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cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
| clipLimit | Threshold for contrast limiting. |
| tileGridSize | Size of grid for histogram equalization. Input image will be divided into equally sized rectangular tiles. tileGridSize defines the number of tiles in row and column. |
Image Blur/Smoothing/Gaussian Blur/Median Blur/Bilateral Filter/Motion Blur
Image Blur def blur(image, ksize = 3): blur_image = cv2.blur(image, (ksize, ksize)) return blur_image Bilateral Filtering def bilateral_blur(image, d, sigmaColor, sigmaSpace): retur..
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Image Blurring/ Gaussian Blur/ Median Blur / Bilateral Filter / Motion Blur (Horizontal, Vertical)
3. Random Contrast / Random Gamma / Random Brightness
image gamma 값 조정 (gamma correction)
def gamma_correction(image, gamma=1.0): invGamma = 1.0 / gamma table = np.zeros((256, 1), dtype='uint8') for i in range(256): table[i] = ((i / 255.0) ** invGamma) * 255 return cv..
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3.2 Adjust Brightness and Contrast
Image Brightness and Contrast 변경
image = cv2.imread("Lenna.png", cv2.IMREAD_COLOR) dst_1 = cv2.convertScaleAbs(image, alpha=1.2, beta=-20) dst_2, alpha, beta = automatic_brightness_and_contrast(image) #자동으로 brightness와 co..
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Image Sharpening / Unsharp Image
def sharpen(image): kernel = np.array([[-1, -1, -1], [-1, 9, -1], [-1, -1, -1]]) sharpened_image = cv2.filter2D(image, -1, kernel) return sharpened_image kernel의 element 정보 [[..
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Image Flip (Horizontal/Vertical)
def horizontalFlip(image): return cv2.flip(image, 1) def verticalFlip(image): return np.flipud(image) Horizontal/Vertical Flip
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